WHERE THE ETHNONATIONALIST IS MAINSTREAM: THE MIGRANT DISCOURSE IN TURKISH TWITTER

Gamze Ekmekçioğlu, Angeles Briones,
Prof. Dr. Richard Rogers

Poster Link: https://drive.google.com/file/d/1HekalrWjttVP4CKgwtjT2z0QmzNi4OrE/view?usp=drive_link

INTRODUCTION

The Social Impact of Migration in Türkiye Since 2011
Migration, broadly defined as the movement of individuals from one place to another, or the departure of their homelands to establish new homes, has always been a topical issue throughout human history due to its economic, social, and political impacts. While it can stem from various causes such as famine, drought, war, and natural disasters, its intensity and causes vary depending on the region. Whatever the reason, migration is often the result of challenging external factors that diminish individuals’ quality of life and even jeopardize their right to life, not of their own free will. Every migration story reflects the struggle to leave behind a problem that remains unresolved within the existing order.

Migrants forced to leave their city, country, or homeland due to external factors that make it difficult to live in humane conditions are often not welcomed in the regions they migrate due to various concerns and prejudices. Therefore, migrants are protected by international regulations to ensure more humane living conditions in their countries and circumstances. This section will briefly address the migration crisis Türkiye recently faced with the outbreak of the Syrian civil war in 2011.

A report published in 2020 by the United Nations High Commissioner for Refugees stated that the total number of refugees worldwide had reached the highest number recorded since World War II (UNHCR, 2020). The same report also indicated that 6.6 million Syrians were forced to flee their homes due to the Syrian civil war that began in 2011, mostly to neighboring countries such as Lebanon, Jordan, and Türkiye. According to the latest data from the UNHCR, by the end of 2024, the number of individuals subjected to forced migration worldwide had reached 123.2 million, the number of refugees 31 million, and the number of asylum seekers 8.4 million (UNHCR, 2025).

The refugee issue is a perennially relevant topic with profound social implications. Located at the intersection of Europe and Asia, Türkiye, due to its strategic location, has witnessed massive migrations since ancient times (Erdoğan & Kaya, 2015). 2.
Owing to its geopolitical position, Türkiye functions as a transcontinental bridge, making it a natural transit point for many refugees.

The Arab Spring in the Middle East and the subsequent political turmoil led to the outbreak of the Syrian Civil War in 2011, which, when examined in Türkiye’s migration history, led to its most intense mass migration (Karadağ, 2024). Millions of people lost their lives due to the war that began in Syria in 2011 and has not yet officially ended. One-third of the country's population was forced to flee, and the country that experienced the most migration was its neighbor, Türkiye. This mass migration affected numerous countries economically and socially, and as a result, the Syrian refugee crisis turned into a major humanitarian crisis (Tunç, 2015). According to the latest data from the UN High Commissioner for Refugees, Türkiye is the second-largest country hosting refugees worldwide (UNHCR, 2025). According to a statement by the Directorate General of Migration Management, Ministry of Interior, Republic of Türkiye (T.İ.B.G.İ. Presidency, 2024), of the approximately 4 million foreigners of different nationalities residing in Türkiye as of 2024, more than 3.8 million are Syrians, while the remainder are foreigners under international protection.

With the outbreak of the civil war, Syrian refugees began migrating to Türkiye and were initially placed in camps established in regions close to the border. However, due to the ongoing civil war and Türkiye’s "Open Door Policy," the acceptance rate reached 44% in the first four years of the war, proving inadequate for the number of refugees (Tunç, 2015). Many refugees, struggling to find shelter in the camps, migrated to other cities by their own means, causing the refugee crisis to spiral out of control and become a social and economic hardship felt in every city of the country. Factors such as the Open Door Policy, irregular migration, and the fact that Syrian refugees have easier access to many basic needs, such as education and healthcare, than Turkish citizens have made Turkish society increasingly resentful of migrants and immigration policies.

Meanwhile, the granting of Turkish citizenship to many Syrian refugees has increased concerns within Turkish society that Syrians will never return to their country. A statement released by the Directorate of Communications to refute a television program report claiming, "There are 7 million Syrians and 13 million foreigners in Türkiye, and at least 2.5 million Syrians have been granted Turkish citizenship," demonstrates the seriousness of these concerns. The Directorate of Communications stated that as of August 2024, of the 4,425,230 foreigners with legal right to stay in the country, 3,099,524 were Syrians under temporary protection, and that only 238,768 of these Syrians obtained Turkish citizenship (Başkanlığı, 2024). While some Syrian refugees chose to return to their country with the fall of the Assad regime in December 2024, current data suggests that the vast majority of Syrian refugees who settled in Türkiye since the first wave of migration have not returned yet.

When Türkiye’s recent migration history is examined, irregular migration from Afghanistan, in addition to the mass influx of migrants from Syria, is noteworthy. The wave of migration from Afghanistan, which began with the US invasion and the overthrow of the Taliban government following the September 11 attacks in 2001, escalated into a second wave of migration following the US withdrawal from the country in 2021 and the subsequent resumption of power by the Taliban regime, leading to millions of Afghans leaving the country (Tümtaş & Köse, 2023). According to data from the Ministry of Interior, as of July 2025 alone, 23,406 of the 83,458 irregular migrants were Afghan nationals (İçişleri Bakanlığı, 2025). Unlike Syrian refugees, Afghan refugees, who mostly enter the country illegally, have drawn significant public criticism, and the inadequacy of measures taken to address them have drawn strong criticism.

Due to its Open Door Policy, Türkiye was quickly exposed to the largest wave of migration in the Republic's history after the Syrian civil war. Along with this mass migration, it also became the target of a massive influx of irregular migrants from Afghanistan, Turkmenistan, Uzbekistan, Palestine, Iraq, Morocco, Iran, and other countries. This massive influx, which the country has experienced in such a short time, is being felt across all segments of society, including economic, social, and daily life. The government's inadequate immigration policies have drawn harsh criticism from the public, ultimately fueling a strong public backlash against migrants.

The impact of migration on Turkish society has not been limited to demographic transformation; it has also led to deep concerns in social, economic, and cultural spheres. Following the influx of Syrian refugees, irregular Afghan migration and other illegal entries, which have increased particularly since 2021, have combined with security concerns in society and have paved the way for the proliferation of anti-migrant rhetoric. During this period, the government's migration policies have often been the target of intense public criticism, often directed directly at migrants. Perceptions of a deteriorating social fabric, insufficient economic resources, and a threat to public security fuel negative attitudes toward migrants. These concerns are clear not only in everyday discourse but also in mainstream media and particularly on social media platforms. In this context, the increasingly visible anti-migrant hate speech on Turkish Twitter serves as a striking illustration of how ethno-nationalism fuels social exclusion and xenophobic attitudes, intensifying tensions around migration issues in Türkiye.

Hate Speech, Xenophobia, and Social Context: Anti-Migrant Sentiments in Digital Media
While there are many different definitions of hate speech, a common characteristic in nearly all is the directing of hostile, discriminatory, and alienating speech toward a specific individual or group. While researchers note that legal definitions vary across countries, they emphasize that the common thread is the intent or effect of inciting violence and alienation. Parekh (Parekh, 2012) argues that hate speech has three main characteristics. To begin with, it is the isolation and/or marginalization of an individual or group by reference to their specific characteristics. The second characteristic is that hate speech labels the target of the speech with characteristics deemed undesirable by the majority group from which it originates. The final defining trait is that the target of hate speech is deliberately excluded from ordinary patterns of social interactions.

The definition shared by the Committee of Ministers of the Council of Europe in its 1997 recommendation is much more comprehensive. It defines hate speech as “all forms of expression which spread, incite, promote or justify racial hatred, xenophobia, anti-Semitism or other forms of hatred based on intolerance, including intolerance expressed by aggressive nationalism and ethnocentrism, discrimination and hostility against minorities, migrants and individuals of immigrant origin” (Europe, 1997). In this sense, hate speech necessarily includes comments directed at a specific person or group (Weber, 2009, p. 9), particularly when those comments aim to demean, marginalize, or incite hostility against them based on their identity or background

Weber (2009, p. 3), quoting the decision of the Committee of Ministers of the Council of Europe, defined hate speech as ‘any form of expression that spreads, incites, promotes or legitimizes racial hatred, xenophobia, anti-Semitism or other forms of hatred based on intolerance, including religious intolerance, expressed in the form of aggressive nationalism and ethnocentrism, discrimination and hostility towards minorities, migrants and individuals of migrant origin.’ Binark and Çomu (2012) classified hate speech into six categories: political hate speech, misogynistic hate speech, xenophobic hate speech, religious and sectarian hate speech, and hate speech targeting individuals with disabilities and illnesses.

While hate speech is defined differently in law, sociology, and communication sciences, it fundamentally encompasses expressions that promote hostility, discrimination, or violence against specific groups. Nazmine et al. (2021) define hate speech as written, verbal, or behavioral forms of communication that target individuals or groups based on identity-based factors such as race, religion, gender, ethnicity, disability, or sexual orientation. Hate speech, which occurs in all areas of social life, spreads much more rapidly on social media due to the platforms' ability to instantly create and share content, reach large audiences quickly, amplify like-minded views through algorithms, and maintain user anonymity. This accelerated spread, in turn, contributes to polarization, discrimination, and increased social tensions.

This form of harmful expression, which threatens social peace and tranquility, leads to the exclusion of diverse identities and the violation of their rights, is often learned and reproduced from the dominant culture within society or from various cultural structures. Consequently, hateful messages are shaped and interpreted according to cultural and societal factors and passed down from generation to generation (Cortese, 2006, p. 3). One of the most distinctive characteristics of hate speech, which has evolved over centuries through this transmission, is the systematic silencing of its victims.

Such discourse, characterized by prejudiced, hostile, and exclusionary language, can aim to belittle, intimidate, ignore, humiliate, dehumanize, and incite cruelty against target individuals or groups. Thus, the target audience gradually becomes more and more invisible and marginalized within society (İnceoğlu, 2013, p. 79) . As a result, groups that perceive themselves as hierarchically superior maintain their legitimacy by reproducing it. Therefore, hate speech should be considered not only as an individual form of expression but also as a structural mechanism that reinforces and reproduces social inequalities. This multilayered nature necessitates examining the discourse not only through its words but also within the context in which it is produced.

Most initiatives address hate speech not as a legal or criminal definition, but rather as messages that explicitly denigrate marginalized groups. Furthermore, these discussions have largely focused on the linguistic and technical dimensions of hate, and most studies treat hate as a general concept (hateful content directed at anyone) or as directed at a single target (e.g., against migrants) (Calderón et al., 2024). However, focusing solely on linguistic definitions is never sufficient when examining hate speech. Hietanen and Eddebo (2023) also emphasize this point, arguing that hate speech is not limited to overtly aggressive expressions.Based on their perspectives, definitions and assessments taken out of context can overlook more subtle expressions used in everyday life that still produce discriminatory effects. Therefore, hate speech should be considered by considering factors such as context, power relations, and communicative intent.

As stated by Teun van Dijk, hate speech is not limited to the prejudicial expressions of individuals; it is also a tool of ideological domination over minorities by dominant groups at the institutional and societal levels. Van Dijk (1993) defines racist discourse as "a set of meaningful social practices, realized through discourse, directed at racial or ethnic minorities by members of dominant groups." This definition suggests that hate speech should be evaluated not only by the words it contains but also by the social context in which it is produced. He emphasizes that the othering language used against minority groups in the media, politics, and everyday discourse serves to produce an ideological superiority through the distinction between "us" and "them" (van Dijk, 2002).

Based on van Dijk's analysis, hate speech is a tool that reproduces structural problems such as racism, discrimination, and exclusion, and these discourses are often presented under seemingly legitimate guises such as "natural," "reasonable," or "defensive reflex." The use of terms such as "dangerous migrant," "illegal refugee," or "cultural threat," particularly in media discourse, is, according to van Dijk, a reflection not only of individual prejudice but also of broader social and ideological structures (van Dijk, 2005). Therefore, analyzing hateful discourse is not merely a matter of analyzing language; it is also a matter of uncovering social power relations.

Research demonstrates that hate speech is not merely individual discourse but also a form of communication that reproduces social norms and hierarchies. This perspective is critical for policies and regulations, particularly in the digital age. Social media content can offer insights into some of the social events that originate hate speech and/or some of the offline behaviors that result from these discourses. Understanding the social conditions under which such speech is produced requires understanding the historical, economic, and political dynamics of the society in question. This is the only way to better understand why hatred towards a specific group intensifies during a particular period. In this context, hateful rhetoric targeting migrants on social media—in this case, Turkish Twitter—serves as a striking example.

Recently, some racially exclusionary discourse has increased globally, and political correctness on social media has been disregarded, resulting in verbal and sometimes physical violence against refugees and members of minority groups. Considering recent discussions on the rise of hate speech and crimes in Türkiye, it can be argued that such exclusionary and aggressive rhetoric and actions are paralleling a growing unrest stemming from the country's political, social, and economic conditions. Despite having lived in Türkiye since the beginning of the civil war, Syrian refugees, who migrated to Türkiye and Western countries following the Syrian civil war, continue to face significant challenges integrating into Turkish society. This fuels hate speech and crimes directed at Syrian refugees in particular and migrants and minority groups in general.

In the post-2011 period, the mass migration of Syrians, Afghans, Turkmens, and other migrant groups to Türkiye has created various challenges in many areas of social life. Multifaceted dynamics such as inadequate social services, security concerns, the sharing of economic resources, and cultural integration challenges have fostered negative perceptions of migrants in society. In this context, a significant increase in anti-migrant rhetoric and the intensification and circulation of hateful discourse are observed on Turkish social media platforms. The user-centric nature of social platforms, algorithmic content recommendation systems, and weak moderation mechanisms facilitate the rapid spread of such discriminatory and exclusionary discourse.

As a result of these social developments, racism and notions of hierarchical superiority are observed to be reproduced in various forms in Türkiye. Anti-migrant discourses are not only based on economic or cultural concerns, but also emerge as an extension of identity politics constructed through the distinction between "us" and "them." Expressions such as "We've been living here, in our country, for years, they came and took everything," which are frequently encountered on social media, are a reflection of discourse practices that exclude and subordinate migrants. These discriminatory discourses become normalized over time, becoming a part of everyday social life and contributing to the marginalization of migrants. Furthermore, anti-migrant hate speech is not limited to individual prejudices but also manifests itself in institutional and structural forms of racism (Essed, 1991, p. 18). In this context, it can be argued that in crisis environments marked by deepening social inequalities, hate speech targeting migrants and exclusionary identity language become significantly more intense and visible on digital media platforms.

A significant portion of communication research on online hate focuses on major platforms like YouTube, Twitter, and Facebook, or the comment sections of online journalistic outlets. This focus is logically justified given the reach and potential influence of these channels (Rieger et al., 2018). Furthermore, when examining the platforms where hate speech is most frequently circulated in Türkiye, social media platforms such as Twitter, Facebook, and TikTok stand out. In this context, this project aims to map hate speech targeting migrants on Turkish Twitter and examine the dynamics that play a role in its dissemination. As part of the study, a network analysis was conducted that included hashtags categorized as "extreme" and "generic," as well as all hashtags formed by combining these two groups. This analysis aimed to explore the group dynamics, interaction patterns, and discourse clusters among users engaging with these hashtags, in order to develop a more holistic and in-depth understanding of the processes and mechanisms underlying the formation of hate speech.

RESEARCH QUESTIONS

1. What are the dominant frames used in the migration issue space on Turkish Twitter?
2. How do hashtags frame and organize the discussions about migrants?
3. Which political and ideological alliances are on display in the migrant discourse?
4. Which visual materials dominate the various portrayals of migrants?

METHODOLOGY

This research examines Twitter discourse on migration in Türkiye using digital methods. In this context, the following steps were taken to systematically analyze social media content:

1. Hashtag Identification
In this study, in order to understand how anti-migrant discourses are structured on social media in Türkiye, hashtags at the center of migration-themed discussions on X (formerly Twitter) were systematically selected. The selection of hashtags was carried out in two separate groups to reflect both the diversity of content and ideological polarization: “generic” and “extreme.

The Generic group contains hashtags used in broader, mostly neutral, institutional, or news-sharing contexts related to migration issues. The hashtags in this group are: #Düzensizgöçmen (#Irregularmigrant), #Göçmen (#Migrant), #Mülteci (#Refugee) (see Table 1). These hashtags represent a space where both official institutions and social media users participate in discussions (see Table 1).

The Extreme category includes more extreme expressions that include anti-migrant, nationalist, and ethnonationalist rhetoric. The main hashtags used in this category are: #sessisişgaledurde (#Stopthesilentinvasion), #suriyelilersuriyeye (#SyriansbacktoSyria), #Ülkemdemülteciistemiyorum (#Idontwantrefugeesinmycountry), #Ülkemdeoç*istemiyorum (#Idontwantf*inmycountry), #TürkiyeTürklerindir (#TürkiyebelongstoTurks), #Ülkemdesığınmacıistemiyorum (#Idontwantasylumseekersinmycountry) (see Table 1).

These hashtags are often used in the content of specific ideological groups or social media users, reflecting the digital manifestation of anti-migrant mobilization.

A purposive sampling method was employed in the hashtag selection process, creating a sample area that aligned with the research objective and represented discursive diversity. The hashtags were selected based on both previous studies examining trends in anti-migrant digital discourse, in line with existing academic literature, and by reviewing current Twitter usage through preliminary research.

In the final stage, content from hashtags belonging to these two distinct groups was brought together to create a combined issue space (the merged group) that could analyze the interaction between general and extreme opposing discourses. This allowed for the examination of not only the dynamics of the content within its own groups but also the discursive oppositions and/or intersections between them.

2. Data Collection
Data collection based on the identified hashtags was conducted to systematically identify content related to migrant discourse on Twitter. Data collection encompassed both textual and visual content, using digital research tools such as Zeeschuimer and 4CAT. These tools yielded tweets containing relevant hashtags and the accompanying visual materials.

During the data collection process, previously identified generic and extreme hashtag groups were used as queries. Separate data extraction was performed for each hashtag group, preserving the thematic separation necessary for comparative analysis. In collecting tweets, structural information including both textual content and user interactions (such as retweets, replies, and likes) was considered. Additionally, the URLs and associated media files of images included in the tweets were also included in the dataset.

Data collection was conducted within a specific timeframe. This timeframe was chosen to cover the last six months to both obtain a dataset of sufficient size and reflect current trends in migrant discourse. Thus, the dataset used in the study is both current and reflects discursive diversity.

As a result, the dataset generated in this step provides a multi-layered and thematically rich analysis base, encompassing different levels of content representing both general and extreme oppositional discourses on migration.

3. Expanding the Dataset
Following frequency analyses and preliminary analyses of the tweet data collected in the first phase, additional hashtags and keywords prominent in the discussions were identified. This analysis revealed not only the central themes of the migrant discourse but also subcategories within it, such as economic burden, security, and cultural identity. Based on these findings, new queries were added to the dataset, thus enriching the original dataset. This expansion enabled a more comprehensive analysis of the diverse sets of opinions in the digital public sphere.

4. Network Analysis
Based on the collected dataset, two separate co-hashtag networks were created to examine the co-use of hashtags. The first network consists of hashtags classified as "generic" and approaching migration from a more general, institutional, or neutral perspective, while the second network reflects the co-use relationships of hashtags classified as "extreme" and containing explicitly anti-migrant and ethnonationalist rhetoric.

Both networks were constructed and visualized based on data exported through the Zeeschuimer and 4CAT tools. Co-occurrences were modeled through correlations indicating the number of times hashtags appeared together within the same tweet. This structure allowed us to understand which concepts were invoked together and how discursive clusters were formed.

In the next stage of the analysis, the two networks were combined as “merged” network to form a unified intersection network containing both generic and extreme discourses. This network structure made visible not only the interconnections of both discourse groups but also the discursive intersections and potential transition areas that emerged between them.

Preliminary analyses using network visualizations revealed the interaction patterns of different discourse clusters on Turkish Twitter, as well as ideological alignments and intersections. In particular, the centrality of certain hashtags or their role as bridging nodes contributed to a better understanding of the organizational logic of discourse in the digital realm.

5. Visual Analysis
Based on the shared hashtag networks created within the collected data, the most frequently shared and engaged images were identified. No qualitative content analysis was conducted on the images; rather, these materials were simply classified and grouped based on their frequency.

Preliminary assessments at this stage revealed that the visual content used within the generic hashtag network did not exhibit significant thematic density and therefore did not constitute a defining or repetitive visual narrative for the study. Conversely, within the extreme hashtag network, certain themes were found to recur, particularly images featuring nationalist symbols, logos, political figures, and leaders. Therefore, during the visual analysis phase of the study, only images within the extreme hashtag group were listed and exemplified under the heading "Visual Narratives in Extreme Hashtag Networks."

FINDINGS

Overview of Hashtag Clusters
This section provides an overview of the generic and extreme hashtag groups used in this study. Each group is modeled as a distinct network of hashtags used together on Twitter, representing different discourse clusters. The comparative analysis of these structures aims to provide initial observations regarding hashtag co-occurrence patterns, structural densities, and potential areas of interaction.

In the following sections, we will first analyze the networks formed by generic and extreme hashtags separately, and then evaluate the merged network, which is the combination of these two groups. This merged network allows us to examine potential transition points and areas of interaction between different discourse clusters.

The data in the table below shows the distribution of hashtags used in the examined tweet network according to content type. Hashtags were classified into two main groups: generic hashtags (general and neutral hashtags) and extreme hashtags (tags containing extreme and anti-migrant discourse). Both Turkish and English equivalents are provided for each group, and the number of tweets for the respective hashtags is indicated.

Table 1: Number of Tweets by Hashtag Types

The #Göçmen hashtag in the generic hashtag group was the most frequently used hashtag with a total of 1,106 tweets, followed by #Mülteci (312) and #Düzensizgöçmen (275). The general characteristic of this group is that it includes more descriptive, classificatory, and less ideological discourses regarding the phenomenon of migration.

In contrast, the hashtags in the extreme hashtag group clearly convey exclusionary, nationalist, and anti-migrant rhetoric. The highest number of tweets was observed with #Ülkmedemülteciistemiyorum (562 tweets), followed by #TürkiyeTürklerindir (549), #Ülkemdesığınmacıistemiyorum (337), and #Suriyelilersuriyeye (300). These hashtags not only carry direct exclusionary messages but also reflect a political orientation and collective call. Furthermore, even the harsher hashtag #Ülkemdeoç*istemiyorum (166 tweets) gained significant visibility.

This distribution demonstrates that the discourse in the extreme group is both diverse and high-volume, with anti-migrant language holding a strong presence in the digital network. It is also noteworthy that extreme hashtags exhibit greater diversity and broader mobilization. These findings suggest that opposing discourses on Twitter are structurally organized and visible.

This image ranks the hashtags included in the study based on their impressions. Almost all of the top hashtags in the image are tags belonging to the extreme discourse category. For example, hashtags with explicitly anti-migrant and exclusionary language, such as #Ülkemdemülteciistemiyorum, #Ülkemdesığınmacıistemiyorum, #TürkiyeTürklerindir, and #Sessizişgaledurde dominate not only in terms of the number of shares but also in terms of their digital visibility.

This finding becomes significant when considered alongside the tweet count data in the previous table. For example, the hashtag #ÜlkemdeMülteciİstemiyorum has a high share volume with 562 tweets and ranks first in terms of visual impressions. Similarly, the hashtag #TürkiyeTürklerindir displays both quantitative density and high visibility with 549 tweets.

This suggests that extreme discourse is spread through a digital distribution mechanism where it is not only used more frequently but also viewed by a wider audience. In contrast, hashtags like #Göçmen, #Mülteci, or #IrregularMigrant, which belong to the generic hashtag group, are shared more frequently in the previous table, but are not as visible or ranked lower in terms of impression. This difference suggests that neutral or technical terms generate less engagement in social media algorithms or have limited mobilization power.

In conclusion, it is observed that hashtags containing extreme discourse dominated the Turkish Twitter public opinion in terms of both content and visibility during the analyzed period. This is a significant finding regarding the reach of discursive polarization and exclusionary language in digital networks. While the visual quantitatively reveals the structural tendencies and discursive direction of the network, the ideological homogeneity of high-frequency hashtags is particularly striking.

NETWORK ANALYSIS
Generic Co-Hashtag Network Analysis

1. General Structure of the Network and Central Nodes

The generic co-hashtag network reveals the general and moderate framing of migration debates on Turkish Twitter. This structure, composed of tweets containing the hashtags #Düzensizgöçmen, #Göçmen and #Mülteci, allows for the analysis of neutral aspects of digital discourse. The #Göçmen hashtag, positioned at the center of the network, is analytically critical not only for its high number of connections but also for its ability to bridge different discourse clusters. Its connections to global, national, and local thematic clusters reflect the multilayered and geographically polycentric nature of the migration debate.

The network structure is generally dispersed, containing various connections where official, news, or informative tweets are gathered. This suggests a low-density but broad-spectrum discourse universe. Some high-frequency, general-themed hashtags create common points of connection, structuring the discourse. Because the data consists solely of generic (neutral, descriptive) hashtags, a structurally stable distribution is observed across the network. This stability suggests that the discourse is relatively free of polarization and develops within a descriptive-interpretive framework.

In conclusion, the generic co-hashtag network demonstrates that migration is a multi-level, mostly neutral, and only slightly ideologically fluid discourse on Turkish Twitter. Central nodes (#migrant, #refugee) hold the discourse universe together, while clusters that form around them reveal how migration is interpreted across diverse geographical and thematic contexts. This network is characterized not by extreme polarization or intensely exclusionary discourses, but by a discourse structure based on information exchange, observation, identification, and occasional concerns.

2. Clusters in the Generic Co-Hashtag Newtwork
a. European Migration Cluster
This cluster includes hashtags such as #Avrupa (#Europe), #Almanya (#Germany), and #Fransa (#France). It revolves around themes such as border security, integration issues, and rising xenophobia within the European context. It reflects the global dimension of the migration discourse, specifically in Europe, demonstrating transnational connections in the digital sphere.
b. #Göçmen Cluster (Central Connector)
The #Göçmen (#Migrant) hashtag is at the center of the network, acting as a connector between thematic clusters. This network structure, which uses only general hashtags, is more stable than the merged version. While the discourse may appear general, it presents a multilayered structure shaped by global media narratives and local urban tensions.
c. #Mülteci Cluster
This hashtag, which has the most connections after #Göçmen, is associated with terms like #Göç (#migration), #Mülteci (#refugee), #Suriyeli (#syrian), #Türk (#Turkish), and #İranlı (#iranian). This structure reflects a more descriptive and explanatory clustering based on migrant identities and statuses.
d. Local Turkish Cities in the Irregular Migration Discourse Cluster
This cluster includes specific city names in Türkiye and hashtags such as #Kaçakgöç (#illegalmigration) and #Düzensizgöç (#irregularmigration). Topics such as urban-centered migration, human trafficking, and border security are particularly prominent. It demonstrates how migration debates in Türkiye materialize at the local level.
e. U.S.-Oriented Cluster
This cluster of hashtags, consisting of #Trump and #ABD (#USA), demonstrates that Türkiye’s migration discourse also references American migration policies. The presence of Trump-era discourse in Turkish content, in particular, reveals how migration narratives are articulated globally on digital platforms.

3. Thematic Categorization of Generic Hashtag Clusters
One of the most striking thematic areas of the network consists of discourses focusing on the identity and status dimensions of refugee status. Hashtags such as #Göç (#migration), #Sığınmacı (#asylum-seeker), #Suriyeli (#Syrian), #Türk (#Turkish), and #İranlı (#Iranian) stand out within this framework; #mülteci (#refugee), in particular, represents a broad semantic field as the second most-connected hashtag in the network. This theme provides a discursive field that demonstrates how migration is defined according to status (refugee, asylum-seeker), ethnicity (Syrian, Iranian), and civic context (Turkish). The discourse here is primarily definitional and descriptive; it lacks any directly opposing or supporting normative positions.

Another thematic area focuses on the impact of migration on local urban spaces and the security concerns associated with irregular migration. Among the labels are Turkish cities such as Izmir, Adana, and Gaziantep, while issues such as illegal migration, irregular crossing, and border security are also prominent. This discourse demonstrates that migration is framed in the digital realm not merely as an abstract issue but also as a concrete phenomenon affecting daily urban life. The urban dimension of migration is discussed alongside concepts such as social unrest, density, and insecurity.

Furthermore, discourses about Europe also find a unique place within the network. This thematic area, shaped around hashtags like #Avrupa (#Europe), #Almanya (#Germany), and #Fransa (#France), is structured with references to the migration crisis in Europe, integration policies, and rising xenophobia. While Europe's border policies, migrant integration, and security concerns come to the fore, this area reveals how perceptions of European countries—for example, "countries accepting refugees" or "anti-migrant attitudes"—are integrated into Turkish digital discourse. This allows us to understand how global media agendas are conveyed to the Turkish digital public.

Finally, US-centric migration discourses are attracting attention. This theme, particularly represented by the hashtags #Trump and #USA, demonstrates the rhetorical connections being established between US migration policies and Turkish migration debates. Anti-migration rhetoric from the Trump era is being used as a reference point by Turkish Twitter users, and US political debates resonate with the Turkish context. This demonstrates that international migration discourses are being articulated under the influence of digital globalization, and that experiences from different contexts intersect at the discursive level.

4. Conclusion
The generic co-hashtag network reveals "moderate" and "mainstream" discourse structures regarding the digital representation of migration on Turkish Twitter. This network allows for the analysis of thematic clusters shaped by media influence, geographic contexts, and socio-political references related to migration. The #Göçmen (#migrant) hashtag, in particular, is a central and connecting element of this structure.

Extreme Co-Hashtag Network Analysis

Figure 3: Extreme Hashtags Network

1. General Structure of the Network and Central Nodes
The Extreme group is constructed as a co-hashtag network based on the co-occurrence of six hashtags with distinctly anti-migrant and nationalist themes. This network, composed of hashtags used together at higher frequency and intensity, exhibits a tightly connected and clustered structure. While this network exhibits a more dense and polarized structure, its connectivity is divided into subclusters strongly coded for political and ideological reasons. The nodes at the center of the network represent not only hashtags with high engagement but also themes that can establish discursive connections with other clusters. The most notable of these nodes are high-frequency and highly representative hashtags such as #TürkiyeTürklerindir (#TürkiyefortheTurks), #Suriyelilersuriyeye (#SyrianstoSyria), and #Ülkemdesığmacıistemiyorum (#Idontwantasylumseekersinmycountry).

Central nodes not only foster groups clustered around common concepts but also form transition points where different ideological axes intersect. An organized interaction pattern is observed, where numerous similar hashtags and messages from different ideological frameworks are used together. The connections between hashtags are frequent and repetitive, increasing the likelihood of coordinated dissemination of specific messages.

More marginal clusters located on the fringes of the network often feature more discursively aggressive, exclusionary, and abusive language; therefore, they are less connected to other themes and occupy a more isolated position. Hashtag clusters containing profane and racist discourse, in particular, provide examples of this structural exclusion. Despite the divisive and ethnonationalist language, the limited engagement of the extremely racist and abusive discourse in this extreme hashtag group is a significant finding, demonstrating that such content is not legitimized by a wider user base and fails to resonate with surrounding network structures.

The extreme co-hashtag network not only serves as a platform for sharing views on refugees but also reflects broader political polarization in Türkiye. Anti-migrant sentiment frequently intersects with politically oppositional hashtags such as #GovernmentResign and #ErdoganResign. In this context, migration is framed as part of a wider critique of the political system, expressing dissatisfaction with government policies. The discourse within the network predominantly features negative, exclusionary, and hostile language.

2. Clusters in Extreme Co-Hashtag Network
a. Legacy Nationalism and Security Cluster
In the extreme group, the most connected hashtag is #Türkiyetürklerindir (#TürkiyeforTurks), which is strongly linked to #NeMutluTürkümDiyene ("How happy is the one who says, 'I am a Turk' ") and #TürkiyeCumhuriyeti (#RepublicofTürkiye)—both of which also appear in other clusters. A notable aspect of this particular cluster is the presence of some of Türkiye’s most prominent nationalist slogans, such as #ŞehitlerÖlmezVatanBölünmez ("Martyrs never die, the homeland is indivisible"). This is accompanied by related hashtags like #Şehit (“Martyr"), #BenimAdımTürk ("My name is Turk"), #Türkçüyüz ("We are Turkists"), #KahrolsunPKK ("Down with the PKK"), #KahrolsunTerör ("Down with terrorism"), and #ErmeniSoykırımıTarihiBirYalandır ("The Armenian genocide is a historical lie").

Unlike other clusters that focus more directly on anti-migrant or anti-refugee rhetoric, this cluster reflects a more traditional nationalist discourse anchored in Türkiye’s longstanding conflicts, particularly with the PKK terrorist organization and historical debates such as what is referred to by some governments as the Armenian genocide. The emphasis here shifts from contemporary migration issues to themes rooted in national unity, historical memory, and anti-terror sentiment, revealing how nationalist identity is expressed through a continuity of older ideological and security-based concerns.

b. Zafer Partisi (Victory Party) and Solidarity Cluster
The cluster centered around the second most frequently used extreme hashtag, #ÜlkemdeMülteciİstemiyorum is particularly noteworthy. This slogan/hashtag was originally introduced nearly two years ago by Ümit Özdağ, the leader of the right-wing Zafer Party. One of the most prominent co-occurring hashtags within this cluster is #ÜmitÖzdağYalnızDeğildir (“Ümit Özdağ is not alone”), along with #Seninleyiz (“We are with you”) and #ÜmitÖzdağaÖzgürlük (“Free Ümit Özdağ!”), which emerged in response to his detention following his anti-refugee statements.

Within the same cluster, the hashtag #VatanyaHutsilivri (“Homeland or Silivri”) references political prisoners and adds a dimension of solidarity with those imprisoned for political reasons.

Additionally, the cluster includes #SüreciBaltalayacağız (“We will sabotage the peace process”), expressing opposition to the government’s “peace process” with the PKK terrorist organization, and #ApoPiçtirP*çKalacak (“Apo is a bastard and will remain so”), an anti-PKK slogan.

This configuration demonstrates how exclusionary migration rhetoric intertwines with nationalist, anti-terror, and political opposition narratives, creating a highly charged and polarized discourse space.
c. Securitized Migration Cluster
Another relatively smaller cluster is formed around the hashtag #Sessizişgaledurde. Within this cluster, we also observe the presence of high-frequency extreme hashtags such as #ülkemdemülteciistemiyorum and #ülkemdesığınmacıistemiyorum, which align discursively with the central theme of the cluster. The use of militarized language such as "silent invasion" indicates the securitization of migration discourse and reflects the broader dynamics of fear-driven nationalism in online spaces.
d. Return-Oriented Refugee Cluster
A separate cluster is centered around the hashtag #ülkemdemülteciistemiyorum. Within this cluster, we observe the frequent use of slogans that reference the perceived stabilization of the Assad regime, such as #savaşbittievinizedönün ("the war is over, go back home"), #bütünsığınmacılarevinizedönün ("all refugees go back home"), and #sığınmacılarevine ("refugees go home"). This cluster reflects a discourse that frames the continued presence of refugees as unjustified or illegitimate now that the original cause of displacement—namely, the Syrian conflict—is seen as having ended or resolved. The messaging reveals a shift from humanitarian framing toward a return-oriented narrative, reinforcing exclusionary and temporally conditional attitudes toward forced migration.
e. Peripheral Aggressive Cluster
This cluster appears more peripheral in the network due to its use of highly aggressive, profane, and racially charged language, which limits its overlap with other discourse communities. The narrow ideological focus and low co-occurrence of its hashtags with broader narratives reduce inter-cluster connections, causing the algorithm to position it further from the network's core.
i. Another extreme hashtag that stands out due to its highly offensive and profane language is #ülkemdeoçistemiyorum. This hashtag forms the center of two clusters, one relatively large and another smaller. In the main cluster, similarly aggressive and dehumanizing hashtags are present, such as #ülkemdeşerefs*zk*pekistemiyorum (“I don’t want dishonorable dogs in my country”). Alongside these, hashtags that express concerns about the perceived erosion of Türkiye’s ethnic homogeneity are also prominent—for instance, #ülkeyimelezeçevirdiniz (“You turned my country into a mixed-race nation”), #ülkemelezoluyor (“My country is becoming mixed”), and #Türkmilletiuyuyor (“The Turkish nation is asleep”).
ii. These hashtags reveal anxieties about the long-term demographic impact of ongoing refugee flows—particularly in reference to intermarriage between Turkish citizens and Syrian refugees. The discourse suggests a racialized fear of “losing” the “purity of the Turkish nation”, a sentiment commonly found in ultranationalist and ethnonationalist narratives. While the vulgar tone distinguishes this cluster, it reflects broader exclusionary and racial anxieties that resonate with certain segments of the population, even when not expressed in such extreme terms.
f. Political Opposition Cluster
In this cluster, #SuriyelilerSuriyeye emerges as a central node that connects anti-refugee sentiment with anti-government rhetoric. Its co-occurrence with hashtags like #ÜlkemdeSığınmacıİstemiyorum, #Hükümetİstifa, and #Erdoğanİstifa reflects how migration-related grievances are used as a vehicle for broader political dissent. This convergence highlights a political tool of refugee discourse in expressions of political opposition and reveals a polarized narrative where migration is framed not only as a social issue but also as a symptom of governmental failure.
g. Nationalist Identity Concerns Cluster
Another cluster formed around the hashtag #ÜlkemdeSığınmacıİstemiyorum includes hashtags such as #TürkiyeİşgalAltında ("Türkiye is under occupation"), #ÜlkemdeBölücüİstemiyorum ("I don’t want separatists in my country"), #ÜlkemdeArapİstemiyorum ("I don’t want Arabs in my country"), and #ÜlkemdeArapçaTabelaİstemiyorum ("I don’t want Arabic signs in my country"). These hashtags reflect a nationalist narrative that frames refugees, particularly Arabs, as a threat to national unity and territorial integrity. Additionally, they express anxieties about the visibility and perceived dominance of Arabic in public spaces, suggesting that the use of Arabic on shop signs and in daily life is seen as a cultural threat to Turkish language and identity. This cluster illustrates a discourse where concerns about migration are closely tied to fears of cultural erosion and national fragmentation.
h. Patriotic Cluster
Another prominent hashtag within the extreme group is #NemutluTürkümdiyene (“How happy is the one who says ‘I am a Turk’” - one of the most well-known sayings of Mustafa Kemal Atatürk, the founder of the modern Republic of Türkiye), which is one of Mustafa Kemal Atatürk’s most well-known quotes. The cluster formed around this hashtag includes others such as #Atatürk, #AtatürkKırmızıÇizgimizdir (“Atatürk is our red line”), and #Atatamizindeyiz (“We are following Atatürk’s path”). Unlike other extreme clusters, this group does not prominently feature hate speech; rather, it is characterized by hashtags expressing patriotism and adherence to Atatürk’s legacy. This suggests that within the extreme hashtag network, there exists a distinct space where nationalist and pro-Atatürk sentiments are articulated more through patriotic identity than through overtly exclusionary or hateful language.

3. Thematic Categorization of Extreme Co-Hashtag Clusters
The Extreme co-hashtag network contains discourse clustered around various themes. These clusters intertwine not only anti-migrant attitudes but also narratives of Türkiye's national security, identity, and political crisis. The counter-terrorism discourse, which has long been on the national agenda, coupled with the deepening refugee crisis and expressions of discontent with the government, converge on a common discursive ground within this network structure. Thus, different crisis themes converge within the digital realm within a single "domestic threat" framework, producing a discourse of social exclusion.

The most dominant discourse on the digital web revolves around a nationalist and security-focused theme. This discourse is represented by traditional nationalist hashtags such as #TürkiyefortheTurks, #NeMütluTürkümDiyene, #Şehitlerölmezvatanbölünmez, and #Vatanbölünmez and is surrounded by content that includes security-oriented and historical identity references such as #Şehit, #Kahrolsunpkk, and #Ermenisoykırımıtarihibiryalandır. Anti-migrant sentiment is expressed not directly within this theme, but indirectly through discourses such as "national unity" and "the integrity of the homeland," positioning migration within the context of a national threat. In this context, the phenomenon of migration intersects with long-standing counterterrorism discourses, thus converging two distinct security concerns to form a broader national threat narrative. This cluster is shaped by a broader perception of national threat rather than direct anti-refugee sentiment. It reveals the unbroken ideological confluence of historically persistent nationalist sensitivities with contemporary migration debates. Therefore, anti-migrant sentiment appears here not as a specific figure of the other, but rather as a symbolic extension of the multilayered threats (ethnic, sectarian, demographic) directed at the ideal of an "indivisible homeland."

Another prominent discursive strand within the network is the anti-migrant political theme centered around the Zafer Party, which has been shaped around a specific political focus. This theme, exemplified by hashtags such as #Ülkemdemülteciistemiyorum, #ÜmitÖzdağYalnızDeğildir, and #Seninleyiz, generates a clearly anti-migrant and oppositional discourse. This language, developed around Ümit Özdağ's political agenda, constitutes a political critique that positions itself not only against migrants but also against the government. Furthermore, through hashtags such as #Sürecibaltalayacağız and #Apopiçtirp*çkalacak, anti-migration sentiment intersects with anti-PKK rhetoric, reconstructing it on a security-oriented basis. This allows for the presentation of migration as both a demographic and political threat.

Another discursive structure, encompassing more extreme and exclusionary expressions, is woven around the theme of demographic and racist concerns. Hashtags such as #ülkemdeoçistemiyorum, #ülkemdeşerefsizköpekistemiyorum, #ülkemelezoluyor ve #ülkeyimelezeçevirdiniz, within this structure, represent migrants not only as a cultural but also as a biological threat. The perceived threat to racial purity, combined with issues such as marriage and childbearing with refugees, virtually defines the presence of migrants as a "genetic invasion." The structural isolation of this discourse from the rest of the network stems from the extremely radical and exclusionary language used. This demonstrates that hate speech is not central to the digital network, but rather marginalized, yet radicalized.

Another form of expression, situated on a relatively more moderate basis, is the theme of rational discourse focused on return. Shaped around hashtags such as #SuriyelilerSuriyeye, #savaşbittievinizedönün (#warisovergohome) and #bütünsığınmacılarevinizedönün (#allrefugeesgohome), this theme attempts to ground anti-migrant sentiment on more "rational" and "legal" grounds. The argument that the war has ended, and refugee status is no longer valid questions the legitimacy of the temporary protection regime, and supports policies of repatriation. The strengthening of social expectations for Syrians to return to their country, particularly with the end of the Assad regime in December 2024, has led to this theme becoming more visible in digital discourse.

Another area where anti-migrant discourse is concentrated is the concern over cultural assimilation and Arabization. Hashtags such as #ÜlkemdeArapçaTabelaİstemiyorum (“I don’t want Arab signs in my country”), #ÜlkemdeArapİstemiyorum (“I don’t want Arabs in my country”) and #TürkiyeİşgalAltında (“Türkiye is under occupation”) generate a perception of threat through cultural symbols. Arabic signs and the visibility of migrants in public spaces are coded as a threat to assimilation for Turkish identity, and this visibility is represented as a form of "cultural occupation." This discourse reflects societal sensitivities and resistance to preserving cultural affiliation beyond ethnic affiliation.

Finally, another striking structure within the network is the discourse surrounding Pro-Atatürk and national symbols, which offers more positive frameworks but can overlap with anti-migration sentiment. Shaped by hashtags such as #Atatürk, #AtatürkKırmızıKizgımızdir, and #Atatamizinindeyiz, this structure constructs a sense of belonging around secularism, national unity, and republican values. While exclusionary language is not dominant within this theme, it is thematically adjacent to anti-migration and nationalist discourses within the digital network, thus indirectly, if not directly, engaging with exclusionary frameworks. This demonstrates that migration debates resonate not only within racist or conservative circles but also within discourse groups organized around secular and nationalist values.

4. Conclusion
The Extreme co-hashtag network reveals the discursive diversity of anti-migrant sentiment in the digital sphere and its interrelation with political polarization. Themes that characterize the network include nationalism, security concerns, the idea of ethnic purity, fear of cultural assimilation, and political anger. These diverse themes converge around a common idea of "exclusion" and reproduce anti-migrant discourse across different segments of society.

Merged Network Analysis

1. General Structure of the Network and Central Nodes
The merged network is a unified co-hashtag network model constructed from tweets containing both generic and extreme hashtags. This network aims to analyze how hashtags from both categories are used together and which other hashtags they are associated with in common or opposing contexts. This unified network encompassing all hashtags exhibits a highly dense and complex structure, where we can trace both ideological diversity and interdiscursive fluidity. The #Göçmen hashtag, located at the center of the network, has the highest structural connection capacity. This demonstrates how central the issue of migration has become in the digital public sphere, both at the general and political levels.

Another striking aspect of the network is that some hashtags do not belong to a single discourse cluster, but instead bridge discursive fields that can be defined as both "generic" and "extreme." Hashtags such as #SuriyelilerSuriyeye, #mülteci, and #NeMutluTürkümDiyene stand out in this context; circulates across different clusters, functioning as "transitional hashtags." Such hashtags blur ideological boundaries and enable the intermingling of discursive layers.

1. Clusters in the Merged Network
a. Secular-Nationalist Overlap Cluster
#Türkiyetürklerindir appears in the intersection cluster through co-occurrence with #Türkiyecumhuriyeti and #nemutluTürkümdiyene— a well-known quotation by Mustafa Kemal Atatürk. This suggests a discursive overlap between far-right nationalist rhetoric and secular, pro-Atatürk identity, reflecting a blurring of ideological lines and possible mainstreaming of ethno-nationalist narratives.
b. Symbolic Bridge Cluster
Mustafa Kemal Atatürk and Ümit Özdağ related hashtags appear as bridging nodes in the secular-Kemalist and contemporary security-focused nationalism. This shows a rearticulation of Atatürk’s legacy in current migration-related discourse, where historical nationalist symbols are used across ideological lines, blending secular-civic and security-focused nationalist narratives.
c. Flexible Symbolism Cluster
The hashtag #nemutluTürkümdiyene appears both in the intersection cluster and strongly within the extreme cluster, linking pro-Atatürk secular-left slogans and security-focused nationalist narratives. This dual presence reveals the symbolic flexibility of nationalist slogans, which carry different meanings across ideological contexts. It functions as an ideological bridge, enabling discursive overlap between distinct political groups. This underscores the importance of analyzing not just hashtag presence, but also their framing and surrounding discourse to understand their ideological role in digital spaces.
d. Sovereignty Defense Cluster
#Kahrolsunpkk, #Apopiçtirp*çkalacak, and #Ermenisoykırımıyalandır appear in the extreme cluster, reflecting a discourse focused on anti-terorism (PKK) and the rejection of external historical claims (e.g., what is referred to by some governments as the Armenian genocide). This sub-cluster blends security-focused nationalism with historical defense narratives, framing both terrorism and foreign criticism as threats to national unity and sovereignty.
e. Peripheral Aggressive Cluster
#Ülkemdeoç*istemiyorum appears in the extreme cluster but is less connected and more isolated than similar hashtags like #ülkemdemülteciistemiyorum. Its extremely vulgar and dehumanizing tone may limit its circulation, showing how language intensity affects the reach and legitimacy of extreme discourse. Reflects a hierarchy of acceptability within hate-based narratives — more “strategically framed” hashtags spread wider. “This term is cited verbatim for the purposes of academic analysis and does not reflect the author’s endorsement.”
f. Bridge Hashtag Cluster
#Göçmen appears in the generic cluster with the highest connectivity, reflecting its broad and widespread use. #mülteci, though also in the generic cluster, is found in the intersection cluster, indicating it bridges general migration discourse and more politicized or exclusionary narratives. #suriyelilersuriyeye, categorized as anti-migrant, also appears in the intersection cluster, acting as a link between extreme and other thematic groups. This shows how some hashtags serve as bridges between neutral or general discourses and more extreme or ideologically charged narratives, revealing complex patterns of network connectivity.
g. The hashtag #göçmen, which is situated within the generic cluster, exhibits connections to three distinct thematic clusters, reflecting the multifaceted and transnational nature of migration discourse on social media. These connections demonstrate that the hashtag #göçmen functions as a discursive bridge across global, regional, and local contexts. It mediates between different geographic and political narratives of migration, revealing how digital public discourse weaves together diverse framings of the issue—from international policy debates to localized urban tensions. The presence of this hashtag at the intersection of such varied clusters highlights its centrality in shaping and reflecting collective perceptions of migration.
i. The first connected cluster is dominated by hashtags such as #Avrupa, #Almanya, and #Fransa which anchor the conversation in the context of the European migration or refugee crisis. This cluster reflects concerns related to the perceived impact of migrants and asylum seekers on European societies, often invoking narratives around border control, integration challenges, or rising xenophobia within EU member states.
ii. The second cluster revolves around hashtags like #Trump and #ABD (the USA), situating the discourse within the U.S. context. This linkage suggests that users discussing migration in Türkiye also engage with or draw parallels to U.S. migration debates, particularly those shaped by Trump-era policies. This cross-contextual referencing reflects how global migration narratives are interconnected in the digital sphere.
iii. The third cluster is more localized and temporally specific, shaped by recent developments regarding the potential return of Syrian refugees. It includes themes of irregular migration, human smuggling, and discussions framed around specific Turkish cities, where the presence of migrants is perceived as a pressing urban issue. This cluster underscores how national and local dynamics intersect in shaping public discourse on migration, blending broader geopolitical concerns with everyday lived realities.

Finally, in the merged network, the secular and pro-Atatürk cluster gravitates toward the intersection group rather than the extreme one due to its use of nationalist discourse grounded in civic and republican values rather than ethnic hostility. The group occupies an ideologically transitional space, sharing discursive elements with both mainstream and radical narratives, particularly around national identity, cultural preservation, and border security.

2. Thematic Categorization of the Merged Network
The hashtag #Göçmen, at the center of the network, touches upon a wide range of discourses. This hashtag forms the node of a multilayered network by connecting refugee policies in Europe, migration debates in the US, and urban-based tensions in Türkiye. At the discourse level, this demonstrates that digital migration discussions are shaped by mutual references not only at the national but also at the global level. Three subclusters are particularly noteworthy: the Europe-focused discourse theme, the US-focused migration discourse theme, and the local urbanization and irregular migration theme.

The theme of Europe-focused discourse is shaped by hashtags such as #Europe, #Germany, and #France, referencing anti-migrant waves and the integration crisis in Europe. The theme of US-focused migration discourse, through hashtags #Trump and #USA, demonstrates how anti-migration populist discourse resonates in the Turkish Twitter context. The theme of local urbanization and irregular migration encompasses intensifying local grievances regarding the presence of refugees in certain cities in Türkiye and concerns about migrants brought illegally to coastal or border cities through human trafficking. Concepts such as human trafficking, refoulement, and urban security are prominent within this theme.

The theme of national identity and historical nationalism is largely woven around hashtags such as #TürkiyeTürklerindir, #NeMutluTürkümDeyene, #TürkiyeCumhuriyeti, #Kahrolsunpkk. Structurally, it intersects with both right-leaning discourses and secular, pro-Atatürk identity expressions. The #NeMutluTürkümDeyene hashtag is a specific example in this regard: It is used by both ultranationalist and secular and pro-Atatürk groups, gaining "ideological flexibility" across discourses. In this theme, historical themes and contemporary security concerns are intertwined. Counterterrorism discourses are indirectly articulated with migration debates through foreign policy issues and codes such as "nation unity."

The theme of radical exclusion and digital racism discourse includes hashtags such as #Ülkemdeoç*istemiyorum, #Ülkemdemülteciistemiyorum, and #Apopiçtirp*çkalacak; they convey a more aggressive tone both linguistically and discursively. While these types of statements occupy a more marginal position structurally, they resonate with specific subgroups within the network through repetition. This is critical in demonstrating the place of hate speech within the boundaries of social acceptance. The higher dissemination capacity of hashtags that contain more "strategic" or implicit exclusion (e.g., #Suriyelilersuriyeye) reveals how digital racism circulates in more acceptable forms.

The theme of pro-Atatürk and transitional discourses occupies a unique position within the network; while not fully integrated into extreme discourses, it shares certain commonalities with them. Hashtags such as #Atatürk, #Atatürkkırmızıçizgimizdir, and #Atamizindeyiz, while not directly related to anti-migration discourses, can overlap with concepts such as "national unity" and "cultural protection," around which these discourses are constructed. This structure demonstrates the extent to which the pro-Atatürk and secular discourse's position on migration has moved closer to a nationalist and security-focused line. The presence of hashtags associated with Ümit Özdağ within this theme demonstrates the establishment of a discursive bridge between secular nationalism and right-wing. Atatürk's legacy is interpreted differently in contemporary political, and migration debates and becomes operational in various discursive arenas.

3. Hashtag Fluidity and Ideological Complexities
In this network, some hashtags appear to become part of more than one discourse domain, not just their cluster. Hashtags such as #Mülteci, #SuriyelilerSuriyeye, and #NeMutluTürkümDiyene serve as "ideological transitional hashtags" that bridge discourse clusters. This demonstrates that anti-migration discourse is not limited to the extreme; on the contrary, it can also establish discursive contact with more central secular and republican groups. These contacts create a platform that facilitates the spread of nationalist sentiments to broader bases in the digital sphere.

4. Conclusion
The merged network analysis reveals how the digital migration discourse is comprised of intertwined structures at both the ideological and discursive levels. The fact that nationalist discourses, leftist, and secular identities can merge under the same node labels demonstrates that ideological boundaries in the digital public sphere are becoming increasingly permeable.

Consequently, this merged network structure allows for the analysis not only of different discursive fields but also of how discursive relationships are established between them, which themes are transitioned, and which expressions possess ideological flexibility. To analyze the multilayered structure of anti-migration discourse in the digital environment, such network analyses bring not only content but also structure-based understanding.

Visual Narratives in Extreme Hashtag Network

Figure 5: Visuals in Extreme Hashtag Network

This section aims to examine how visual content is integrated into the discursive structure of the extreme hashtag network. Identifying how visuals are concentrated around specific hashtag clusters offers key insights into how anti-migrant and ethnonationalist discourses are reinforced through visual strategies in the digital sphere. The analysis of visual distribution focuses not only on the quantitative presence of these contents but also on their representational relationship to the discourse.

The visual content was categorized into three groups: First, graphic logos specific to anti-migrant discourse demonstrate the systematic production of the discourse for digital mobilization. Second, the widespread sharing of images of Ümit Özdağ, leader of the Victory Party, points to a strong visual representational relationship between the leader figure and the discourse. In the third group, images featuring Özdağ and Atatürk in the same frame demonstrate how the representation of the secular nation-state and contemporary right-wing nationalist discourse visually overlap, establishing a symbiotic relationship.

The images on the Extreme network are grouped into three main groups based on their content. The first group consists of graphic logos specifically designed for these discourses, used alongside hashtags such as #Ülkemdemülteciistemiyorum, #Sessizişgaledurde, and #SuriyelilerSuriyeye. Such images demonstrate that digital mobilization is supported by visual tools and systematically produced to promote a specific discourse.

The second group consists of images of Ümit Özdağ, leader of the Zafer Partisi (Victory Party), which are among the most widely shared images under extreme hashtags, particularly #Ülkemdemülteciistemiyorum. Özdağ, who brought this slogan into public discourse, emerges as a visually prominent figure in this context. The visual content demonstrates the integration of the leader's rhetoric and his visual identity, transforming political discourse into a digital visual narrative.

The images in the third group, particularly centered around the hashtag #TürkiyeTürklerindir and featuring images of both Ümit Özdağ and Mustafa Kemal Atatürk, the founder of the modern Republic of Türkiye. These images demonstrate how nationalist and anti-migrant discourses form a symbiotic relationship on the visual plane. Atatürk's representation of secularism and the nation-state, and Özdağ's contemporary right-wing nationalist discourse, visually overlap in these images, demonstrating the symbolic alliance forged in the digital realm.

Overall, these visual assemblages demonstrate that images within the extreme network are used not only as aesthetic or communication tools, but also as narrative elements that reinforce discourse and facilitate mass mobilization. This function of images complements textual analyses, shedding light on the multilayered structure of the digital discourse field.

This step was undertaken to demonstrate the quantitative presence and distribution of visual content in the digital discourse. Identifying hashtag clusters where images are concentrated offers insights into the role and impact of visual data in ethnonationalist and counter-ethnic discourses and paves the way for further analyses of narrative strategies in the digital public sphere.

DISCUSSION

This research aimed to analyze how discourses on migration are structured and shaped around the themes in the digital public sphere (Twitter) in Türkiye. Co-hashtag network analyses revealed that the phenomenon of migration is addressed in the digital discourse not only through information sharing but also through identity construction, political mobilization, and normative position-taking.

The Generic co-hashtag network demonstrated that the topic of migration is addressed within a more neutral, descriptive, and descriptive framework, presenting a multilayered thematic structure with references to refugee status, ethnic identities, urban influences, and international contexts. Here, the discourse is less ideologically polarized and more descriptive. In contrast, the Extreme and Merged co-hashtag networks demonstrate that discourses shaped around the same thematic clusters are no longer simply informational, but rather intensify with explicit political positions, campaign statements, and polarized stances. In this context, digital platforms function not only as forums for discussion but also as politicized digital public spaces.

The main findings point to the dominance of anti-migrant rhetoric. An analysis of the data reveals that the most viewed hashtags are those based on explicitly exclusionary and nationalist rhetoric, such as #Ülkemdemülteciistemiyorum and #Ülkemdesığınmacıistemiyorum. This demonstrates that migration debates are frequently framed around fear and protectionism, deepening social divisions.

Furthermore, the presence of the #TürkiyeTürklerindir slogan at the intersection of both extreme and generic hashtag clusters demonstrates a discourse plane where nationalist and secular discourses converge. This demonstrates how secular identity, referencing Atatürk, and ethnonationalist security identity form a symbiotic alliance around the issue of migration, thereby blurring ideological boundaries. The fact that hashtags related to Mustafa Kemal Atatürk and Ümit Özdağ function as bridging nodes in the network demonstrates how historical symbols are mobilized across ideological lines and how messages of national unity are integrated with anti-migrant rhetoric.

A visual content analysis conducted to understand how these discursive structures are supported by the visual dimension further revealed the multilayered nature of the digital narrative. While no significant repetition was found in the images used with generic hashtags, it revealed that images associated with anti-migrant and ethnonationalist hashtag clusters recurred and reinforced the digital discourse. These visual narratives are not merely aesthetic but also serve as fundamental tools for establishing discursive unity and fostering mass mobilization.

The inclusion of leaders in images of extreme hashtags, rather than images of migrants or refugees, demonstrates that these leaders have become symbols of the migration crisis, and that the topic is now centered around themes of national unity and solidarity rather than migrants, and that messages are being conveyed in this direction. Thus, the issue of migration is being transformed from an individual or humanitarian issue into a narrative that directly threatens collective identity.

At this point, it becomes clear that hate speech is not merely an expression of individual anger; it has become a phenomenon shared collectively and with a social resonance in the public eye. Hate, as a form of criminal behavior met with public condemnation, not only acquires a social dimension but also reflects the anger and anxiety felt by individuals regarding changing social conditions. Therefore, hate speech emerging in digital media offers clues to both the collective anxieties of a certain segment of society and the individual's own existential crises. The fear of losing credibility regarding national sovereignty becomes particularly pronounced during times of economic and political crisis, making it easier for groups on the margins of society to become visible and vulnerable. Rather than addressing the structural problems of society, such groups serve as easy targets to divert attention.

The mass migration wave following 2011 has created a multifaceted transformation in Turkish society, encompassing social, economic, cultural, and security concerns. This transformation has profoundly impacted not only daily life practices but also collective memory, social belonging, and public perception. The visibility created by the increasing migrant population has fueled various fears, anxieties, and discontentment within the local community, particularly in areas such as urbanization, the labor market, demographic structure, and the distribution of public space. This multilayered discontent has directly impacted the discourse expressed on digital media platforms; particularly on platforms like Twitter, the issue of migration has become an expression of collective uncertainties and perceived threats rather than individual experiences.

CONCLUSION

Digital migration discourses in Türkiye possess a complex structure shaped by multi-centered, context-sensitive, and transnational references. Both textual and visual analyses reveal that migration in digital media is not merely an agenda but also a dense field of discourse generated around identity, belonging, security, and nationhood. This study highlights the importance of examining the rising ethnonationalist discourses in the digital public sphere not only at the content level but also at the form and narrative level and offers a multi-dimensional methodological framework for further studies.

In conclusion, the findings of this study demonstrate that anti-migrant discourses emerging in the digital sphere in Türkiye are not confined to a single ideological domain. On the contrary, these discourses are shared by groups with diverse historical and political backgrounds. Interestingly, certain segments of the secular center-left and the right-wing—such as nation-state-oriented secular actors and Zafer Party supporters—converge when it comes to migration. Themes such as "national unity," "the primacy of the Turkish nation," and "the protection of the state against threats to territorial integrity and national security" are emphasized across these otherwise ideologically distinct groups, indicating a shared securitized and nationalist framing of migration. This convergence illustrates how anti-migrant discourse has evolved into an umbrella narrative that transcends ideological boundaries. The discursive bridging of migration across diverse ideological lines provides valuable insight into the configuration of the Turkish digital public sphere and highlights the need for further in-depth, interdisciplinary research.

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