🌎🌡️ Contesting Climate Futures: mapping misinformation narratives and networks on Telegram

Team Members

FACILITATORS
Giulia Tucci, João Guilherme Bastos dos Santos and Bia Carneiro

DESIGN FACILITATOR
Luca Bottani

PARTICIPANTS
Piibe Lukkats, Letizia Sacco, Pavel Cihlář, Anders Puck Nielsen, Lamia Putri Damayanti, and Chiara Caterina Arena

Links

➡️ Contesting Climate Futures poster.

➡️ Set of terms used to filter climate-related messages.

➡️ List of channels that spread climate misinformation messages. LINK

Contents

1. Introduction

Social media platforms are often described as “standing at a crossroads” – facing pressures between aggressive deregulation and stringent moderation. Yet this metaphor conceals the reality that many platforms have already made their choice: dismantling content standards in pursuit of scale, profit, and influence. Telegram historically exemplifies this tension, offering minimal content moderation and fostering unregulated information ecosystems. More recently, platforms like X (formerly Twitter) and Meta's Facebook and Instagram have begun migrating toward this same deregulatory approach, relaxing their content policies.

When mainstream platforms were still enforcing moderation measures and banning extremist users who violated their policies, Telegram emerged as an attractive alternative destination, offering features valued by these deplatformed users, such as protected speech and content archiving (Rogers, 2020).

Telegram characteristics (see Figure 1) allowed the deplatformed extremist actors to rapidly reestablish their audiences and regain prominence within digital networks (Urman & Katz, 2022). Hence, Telegram became an ideal environment for conspiracist communities (Rogers, 2020; Tucci, 2024), significantly impacting perceptions and attitudes towards global challenges such as human-induced climate change through the circulation of misinformation.

Figure 1. Information flow spaces in Telegram. Visualisation adapted from Tucci (2024).

Climate change is currently one of humanity's most pressing crises, with robust scientific consensus establishing human-induced greenhouse gas emissions as its primary cause (Calvin et al., 2023). However, widespread climate misinformation threatens collective responses by undermining public trust in scientific evidence, disrupting informed policy debates, and polarizing communities (Lewandowsky et al., 2017; Treen et al., 2020). Such misinformation circulates rapidly on platforms like Telegram, where limited moderation allows conspiracist narratives to thrive unchecked, ultimately obstructing global climate action and governance.

Recognizing the escalating threat posed by misinformation about climate change, the Brazilian government and the United Nations, through UNESCO, jointly launched the Global Initiative for Information Integrity on Climate Change in November 2024 (SECOM, 2024; UNESCO, 2024). This groundbreaking global partnership aims to counter misinformation by promoting rigorous research, advocating for transparent information practices, and strengthening policy interventions at national and international levels.

This commitment will be evidenced at COP30, taking place in the Brazilian Amazon, which will have as some of its goals to raise climate awareness and political momentum around nationally determined contributions, to promote information integrity about climate change, and to foster public mobilization.

Aligned with these global efforts, our project leverages digital methods (Rogers, 2013) to systematically access, filter, and visualize data from conspiracist Telegram channels, mapping climate disinformation narratives. Analyzing these narratives will help to understand their dissemination mechanisms and platform-specific affordances that facilitate misinformation, contributing directly to international strategies for maintaining information integrity.

Critically, this understanding is not only academic; it is essential for policymakers, governments, and international institutions. Clarifying how climate disinformation spreads, evolves, and exploits platform vulnerabilities provides vital knowledge, enabling policymakers to craft effective, targeted interventions to protect public discourse, enhance climate governance, and support urgent global climate goals.

2. Research Questions

1. How are climate change narratives represented within conspiracist Telegram channels?

2. What specific disinformation narratives emerge, and how do they exploit Telegram’s unique affordances (e.g., traceability of forwarded messages, channels vs. groups)?

3. Does Telegram function as a repository for conspiracist climate content, storing materials, messages, and links to external platforms?

4. Who are the main characters that bring out the conspiracy theories or that are most mentioned by other users?

3. Methodology and initial datasets

3.1 Initial dataset

Initially, a dataset containing 2,000 public Telegram channels (Tucci, 2025a), categorized into politics (1,000 channels) and news & media (1,000 channels), was aggregated from the Telemetr.io repository.

The list of Telegram channels was loaded on TeleCatch (Ruscica et al., 2025), and a specific filter was applied using key terms associated with climate misinformation. The terms and the description of the disinformation narrative are listed below.

• HAARP: The High-frequency Active Auroral Research Program (HAARP) is a real scientific facility in Alaska designed to study the ionosphere (University of Alaska, n.d.). However, conspiracy narratives falsely claim that HAARP can control or weaponize the weather by manipulating atmospheric conditions with radio waves. In reality, HAARP’s radio emissions are far too weak and operate in a region of the atmosphere (the ionosphere) that does not influence weather, which occurs in the troposphere and stratosphere (Erokhin & Komendantova, 2023; Seitter, 2013).

• Chemtrails: This narrative asserts that the visible trails left by airplanes are actually “chemtrails,” or deliberate releases of chemicals for weather control, climate manipulation, or population control. Scientific studies and expert reviews have found no evidence supporting the existence of chemtrails; airplane contrails are simply water vapor and trace gases formed under specific atmospheric conditions (Johnson et al., 2021; Seitter, 2013)

• Weather Weapon Project: The weather weapon narrative posits that governments or secret organizations possess technology that can intentionally cause natural disasters or extreme weather events for military or political purposes. This idea often combines elements of the HAARP and chemtrail conspiracies, despite a complete lack of scientific evidence that any such technology exists or is operationally feasible (Erokhin & Komendantova, 2023).

• Weather Modification: While limited weather modification techniques like cloud seeding (to induce rain) do exist, conspiracy theories exaggerate their scope and effectiveness, claiming that large-scale or targeted weather events are the result of deliberate human intervention rather than natural variability or climate change. These claims are often used to deny the role of greenhouse gas emissions in extreme weather, even though scientific consensus attributes most such events to global warming, not geoengineering (Smith, 2025).

• Climate Lockdown: This recent narrative claims that governments and/or global elites plan to impose lockdowns similar to those during the COVID-19 pandemic, but justified by climate change. The theory suggests that climate action will be used as a pretext to restrict personal freedoms. There is no evidence supporting this claim. It is a misrepresentation of discussions about climate policy and emergency preparedness, amplified by groups opposed to both public health and climate interventions (Murphy, 2024).

Sets of messages were extracted for each of these filtered terms. The channels from which messages about these topics were forwarded were then identified.

Next, a further snowball sampling method was applied. Channels identified as original sources of these forwarded messages were explored, and their content was collected and further filtered based on the same key terms. Again, the channels from which these messages were forwarded were identified. This iterative snowball approach (Peeters & Willaert, 2022) enabled the identification of additional channels, capturing less publicly visible sources disseminating climate-related conspiracy theories and misinformation.

This methodological workflow (see Figure 2) ensures comprehensive mapping of misinformation narratives around climate change on Telegram, contributing to a nuanced understanding of misinformation ecosystems.

After three rounds of data filtering, collection, and identification of sources of content related to the selected climate disinformation narratives, the resulting list of channels was compiled.

Figure 2. Identification of channels that spread climate disinformation messages

3.2. Climate-related messages: dataset processing

The original corpus of 1,417,253 messages was filtered using a controlled vocabulary of 393 unique terms organized into 30 climate-related categories, plus one special category (“DMI2025”) comprising the misinformation-related keywords. Messages were retained for inclusion in the dataset if they contained any of the 393 terms—either a climate-related keyword or a category title (which itself functions as a keyword). For the DMI2025 category, these keywords served primarily to filter and construct the channel dataset; although they may not inherently occur in every message, they formed the basis for channel selection.

The full list of categories and climate-associated terms can be found in this table.

This procedure produced two complementary outputs:

• Unique-message dataset (38,557 messages): All messages containing at least one of the 393 terms, regardless of which category the term belongs to.

• Message–category dataset (56,730 entries): Each instance represents a message–category match, capturing overlap when messages mention multiple keywords from different categories.

→ List of 30 climate-related categories:
Climate change; Climate adaptation; Climate mitigation; Sea level rise; ITCZ; El Niño; Extreme weather event; Flooding; Frost; Temperature; Heat stress; Wind; Drought; Dry spell; Rainfall; Storm; Cyclone; Hurricanes; Climate security; Natural disaster; Natural hazard; Evapotranspiration; Environmental degradation; Deforestation; Erosion; Land degradation; Pollution; Desertification; Acidification.

→ Special category (DMI2025) terms: Haarp; Chemtrails; Climate; Weather weapon; Weather modification.

3.3 Exploratory analysis

Dataset overview

To generate a dataset overview, we used Telegram Analytics (Tucci, 2025b), R-based pipeline for analyzing Telegram message datasets (CSV/TSV). We analyzed to 38,557 climate-related messages drawn from 83 public Telegram channels between January 1, 2024 (00:27 UTC) and June 29, 2025 (23:14 UTC). By combining temporal, sentiment, network, and topic modeling techniques, the report elucidates how conspiracist climate narratives originate, spread, and amplify in minimally moderated environments. This framework supports ongoing monitoring and targeted interventions to uphold information integrity in climate discourse.

The data and scope of the messages shared are presented below:

• Time frame: 18 months (Jan 1, 2024–Jun 29, 2025)

• Total messages: 38,557

• Channels analyzed: 83

• Aggregate views: 291.4 million

• Media attachments: 18,928 (49 % of messages)

• Forwarded messages: 16,223 (42 %)

• Replies: 637

Topic modeling

Network analysis

Hierarchical clustering analysis

After that, we applyed the Reinert method for hierarchical clustering through the R rainette package (6 clusters with 15 as the minimum segment size and 20 as the minimum text size), useful to identify different vocabularies and topics inside a corpus without any previous category. The method was used to: identify different languages inside the corpus; find vocabularies not big enough to be relevant to our analysis, normally the ones representing less than 5% of the entire corpus; identify the main topics and vocabularies to be analysed; identify the sub-vocabularies shaping the internal divisions inside each of the clusters found.

It was made both considering the entire corpus (after 16 rounds of recursive cdh) and separately in the datasets corresponding to each group of keywords (from the 43, 37 were big enough to enable a proper cdh analysis), ranging from 1 to 52 rounds of analysis to reach the final dendrograms in each, with a total of 563 rounds of cdh).

After reaching a cdh dendorgram with six topics, we checked subtopics inside each of them and turned it into plots (dendrograms and wordclouds) to help the team exploring the specificities of each discussion found, its vocabularies, topics of interest and relation with terms related with recurring false information involving climate emergency and its impacts.

3.4 Qualytative analysis

For the qualitative part we decided for a different approach (see Figure 3 bellow). To identify the most pertinent climate disinformation narratives circulating within our dataset, we implemented a multi-stage sampling strategy designed to capture most representative content with the highest engagement and thematic relevance within the platform's affordance structure.

Figure 3: Qualitative sampling strategy

First, we focused exclusively on forwarded messages (25,005 from the total dataset), as these represent content that users deemed worthy of amplification and redistribution, indicating higher resonance and engagement within Telegram's sharing mechanisms.

Second, we applied a thematic co-occurrence filter requiring messages to appear across at least three analytical categories (such as keywords “climate change”, “hurricane”, “drought” etc.), combined with a visibility threshold of more than 5,000 views (equal to 40 % of most viewed messages), thereby identifying content with the strongest signals for climate disinformation themes while ensuring our sample captured content with demonstrated reach and audience engagement.

We then focused specifically on the most climate-relevant topics (Topics 3 and 4 from our topic analysis), yielding 107 messages for detailed examination. Through manual review to retain only messages containing the most relevant climate disinformation content, we arrived at a final sample of 62 messages originating from just 15 of the original 83 channels.

This concentration demonstrates that forwarded content with high thematic co-occurrence and substantial viewership represents a distinct form of platform-mediated engagement, revealing how certain channels serve as key nodes in climate disinformation amplification networks. The fact that our rigorous filtering process concentrated the most resonant climate disinformation content within less than 20% of the original channels suggests that while the broader dataset encompasses channels with varying engagement patterns, our focus on forwarded messaging captures a specific type of platform influence where content amplification through redistribution creates different engagement dynamics compared to original posts.

The resulting sample therefore represents the most widely circulated and thematically robust climate disinformation content within our dataset, providing an optimal foundation for detailed narrative analysis of the most resonant messaging strategies operating within Telegram's affordance ecosystem.

4. Results and Discussion

4.1 Time-varying and event based analysis

Identifying the peak of activity and accompanying queries

Visuals from the Telegram Analysis showed a peak of messages around October-November of 2024. A preliminary exploratory scan of the data, starting from October, revealed most messages were collected by queries related to hurricanes and cyclones and discussed hurricane-related issues. The date with most messages in the dataset was extracted – October 9, 2024 – is the date when hurricane Milton hit land in the United States.

After combining 7 rounds of descending hierarchical clustering and cleaning with the messages from these queries, we got to six subclusters involving mainly:

1. tornado warnings, the seek for shelter and events in Indiana

2. weather modification, use of Haarp antennas as military warfare weapons generating disasters intentionally

3. small talk, how little people know about reality and events like the election.

4. international relations, NATO, US military, Russia, Ukraine, China and the possibility of nuclear attacks

5. disaster assistance, hurricane helene, North Carolina, FEMA aid, Biden-Harris administration funding

6. tsunami, earthquake, more about natural disasters and in more neutral terms, also in Japan

Therefore, after visualising the most common queries of messages from the specific date were visualised, on the one hand, the results showed that the highest occurring queries were ‘cyclone’ and ‘hurricanes’; this confirmed that the peak was related to the topic. On the other hand, this debate also brings posts about other countries (like Japan) and events (US election), and an ongoing production of messages on a much smaller scale. Other query which we called DMI2025 (containing the five terms described in the Initial Data Sets session, whose resulting messages were also split into six sub clusters), contained more“disinformation-related” terms (bringing most of the results analysed), was added to explore the connections of the specific natural disasters with dominant climate change disinformation narratives.

A heatmap combining the three queries, the dates of the messages and the amount per month displays the diversity of messages inside each group, even considering the ones specifically mentioning hurricanes and cyclones, but also a high concentration of the messages related to these topics on October 9, 2024 in some clusters as distinct outliers dealing with the event, while others just faced a small increase.

Dates and queries_vocabularies heatmap

DMI2025 cluster 1 peaked in October 2024, including discussions around Haarp, weather modification, and cloud seeding. As the dataset contains Telegram groups that create and distribute climate disinformation, it is noteworthy that the rate of messaging was amplified during natural disasters, as moments are created for climate conspiracies to spread to the groups affected by the events. In times of people searching for urgent information and news updates, when online media includes disinformation, the focus shifts and vulnerable communities might find comfort from sensationalist blame-focused .

Climate change disinformation is employed to fuel broader conspiracies. Disinformation that furthers political agendas is especially important in the context at-hand being predominantly based on US narratives, with the timeframe of the data collected being the lead up to the 2024 presidential elections and its aftermath. More broadly, LDA topic modeling in the specific month showed the connection to crisis relief and humanitarian aid, criticising the Biden-Harris administration through Topic 1 and deep state weather control through Topic 3. But a significant Topic 6 formed around a conspiracy of child trafficking by Disney. The ideas circulated about the hurricanes in Florida form a story about “the elites”, who can control the weather, creating the hurricanes to flood tunnels under Disney World in order to capture children for trafficking. This serves as an example of climate disinformation employed to instill larger conspiracy theories, in this case the QAnon Disney grooming conspiracy.

https://iopscience.iop.org/article/10.1088/2515-7620/ad1b67/meta

The Deletes

Qualitative exploratory reading of messages in this time period also led to discovering a term “the Deletes”, which appeared 66 times in the dataset referring to weather manipulation by the elite class. As the term is accompanied by an idea that the 1%. The term is not widely spread outside these conspiracist circles based on preliminary online research. However, it remains relevant in our study to exemplify how a smaller channel, like @Eys2C (2 293 subscribers) begins using the term, bigger channels like @AgentsOfTruth (26 082 subscribers) start forwarding those messages and eventually bringing the term into their own vocabulary. Therefore, Telegram serves as a place that fosters subcultures and new perspectives within larger conspiracies.

https://www.theguardian.com/commentisfree/2024/oct/10/hurricane-conspiracy-theories-marjorie-taylor-greene

4.2 Channels behaviour and disinformation hubs

Telegram as a repository of climate disinformation

To further explore how Telegram serves as a place where conspiracy theories develop, we delved into the question of how the platform and specific channels function as repositories of climate disinformation. For this purpose, we explored a hypothesis that the forwarding feature in Telegram could reveal different groups of channels, where some generate original content, and others mainly repost content from others.

This was done using a Jupyter notebook in the Cursor IDE on the basis of the list of 38.557 climate related posts mentioned in section 4.1. The central parameter was the relationship between given and received forwards between these channels. There was a total of 16,223 forwarded posts, but this included a high number of posts from channels that were not included in the data set. This distorted the statistics because these external channels appeared as purely receiving forwards while giving none. External channels were therefore filtered out, leaving a total of 864 forwards between the channels in the data set. In total, 46 channels received at least one forward from one of the other channels, 22 channels gave a forward, and 49 channels either received or gave a forward.

This approach of looking only at forwards given or received between the channels in our original seed list gave the results shown in the illustration below.

It shows three distinct categories of channels, namely Pure Sources, Pure Amplifiers, and Hybrid Nodes. The assumption was that Pure Sources would be the generators of original content, whereas the Pure Amplifiers would be those that generate almost no original content but function as aggregators of links to content generated by others.

However, a look at the two most pronounced examples – @stormypatriotjoe21 and @defenderoftherepublic22 – revealed that this assumption didn’t hold under scrutiny. Despite their very different position in the scatter plot, it turns out that they are very similar in practical terms. The assumed original content by @stormypatriotjoe21 turned out to be almost exclusively screenshots and links to external platforms such as Truth Social or Rumble. @defenderoftherepublic22 has similar content but just includes more links to Telegram including those channels on our seed list.

In other words, it turned out that an extreme position on either axis in the plot actually revealed what can be characterized as bot-like behavior with excessive reposts of external content.

A very different profile was found with the channel that showed the most pronounced position in the Hybrid category. @blackhelicopters turned out to be a very active channel with multiple daily posts and a lot of original content. The posts included references to a range of conspiracy theories including climate related narratives such as HAARP as climate warfare, chemtrails, and climate weapons. It was also a channel that demonstrated high ambitions in terms of wanting to support arguments with references to scientific sources. Posts regularly included links to seemingly reputable sources, and some posts contained comprehensive bibliographies following the Harvard author-date style guide with links to “doi.org”.

The channels discussed here all display behavior that support the hypothesis that Telegram functions as a repository for climate-related conspiracy theories, but they do it in very different ways. Channels with an extreme position on either axis display bot-like behavior but serve as hubs of links to social media posts and memes from external sources that people with an interest in climate-related conspiracies might find interesting. The channel with the most pronounced hybrid position was clearly a more ambitious undertaking with a high number of original posts, independent thought, and links to seemingly scientific sources.

In that sense, @blackhelicopters also functions as a repository but for more intellectually sophisticated climate-related conspiracy content. One could speculate that this channel would be more dangerous in a broader ecosystem of misinformation. Interestingly, the @blackhelicopters channel appears to have been blocked or closed down during the first week of the 2025 DMI Summer Schoolworkshop. It was available at the start of the week but became inaccessible toward the end. Fortunately we had scraped and screen captured most of the contents before the channel disappeared.

Using a different approach, we found two other channels worth exploring. All channels in the data set would post about more topics than the climate, and there was a big difference between the proportion of climate- related material in each channel. To identify the channels most devoted to the climate debate, we calculated the proportion of posts containing climate- related keywords compared to the total number of posts.

This revealed two channels with a much higher proportion of climate- related posts compared to all other channels, namely @reai_jfk_jr (32.3% posts with climate keywords) and @dutchsinsefans (25.8%). These two channels appear highly devoted to climate- related conspiracy content. Both contain a lot of original content that explores different agendas. @reai_jfk_jr writes rather long and fairly rambling posts with news summaries but a low number of outgoing links.

@dutchsinsefans is different in that it appears to be related to research on earthquakes. It contains a lot of data about seismic activity, and at first glance it looks convincing and fact based. It also contains links to other sources by the same author, particularly Twitch livestreams where the reader can get additional information on the earthquakes. However, on closer look it becomes clear that the author is deeply devoted to conspiratorial thinking and believes he has found evidence that earthquakes are man made and related to climate conspiracy topics such as HAARP.

Both of these channels exhibit behavior that supports the understanding of Telegram as a repository of climate conspiracy material. They contribute to the ongoing development of conspiracies and interpretation of ongoing events, and they present the readers with a coherent narrative over time that, at least on the surface, appears to come from an author with expertise on the topic. Furthermore, @dutchsinsefans functions as a supporting platform for a similar Twitch channel, which creates an archive of the livestreams and gives some resilience against the moderation practices on that platform.

Together, these five channels – @stormypatriotjoe21, @defenderoftherepublic22, @blackhelicopters, @reai_jfk_jr, and @dutchsinsefans – demonstrate different types of behavior that can be characterized as fulfilling functions as repositories of climate disinformation. Some of them are related to development of new conspiratorial narratives, while others provide legitimacy or function as aggregators of links or memes that users can share on other platforms. They do, however, only provide examples of the diversity of behavior that channels can exhibit, and to get an overview of the broader ecosystem of misinformation, it was necessary with a more systematic mapping of a larger number of channels.

4.3 The network of channels and its main clusters

To explore how climate-related disinformation circulates across Telegram, we conducted a social network analysis based on forwarded messages, replies, and retweets. This allowed us to capture structural relations between users and to detect key actors in terms of content amplification. We used Gephi to visualize the graph, applying the Force Atlas 2 layout to highlight structural proximities, and we calculated modularity to identify user communities. Node size was scaled based on the number of times a message from a user was forwarded. This analytical process helped us detect not only influential nodes but also the major thematic clusters shaping the circulation of disinformation.

Through this network, we identified a first group of high-impact users strongly focused on conspiracy theories involving weather manipulation and technological control. For instance, @thepatriot17 (link), a Christian evangelist known for linking faith with political empowerment, and @tironianae (link), whose identity blends spiritual, military, and entrepreneurial rhetoric, both promote narratives on HAARP, geoengineering, and institutional deception. Similar narratives were reinforced by @australiaoneparty_official (link), the official channel of a populist Australian party skeptical of climate policies, and by @dotconnectinganons (link), which aggregates alternative content to encourage followers to “connect the dots” and distrust mainstream explanations.

Another cluster centers on health and climate denial, led by actors such as @worlddoctorsalliance (link), which spreads disinformation on both public health and environmental science. In this group, @robinmg (link) stands out for rejecting anthropogenic climate change in favor of narratives about solar cycles and abiotic oil theories. Meanwhile, @geopoliticsandempire (link) connects climate skepticism to broader geopolitical distrust, presenting climate governance as an extension of elite manipulation. Other figures, such as @AGENT_A1 (link) and @ThePatriotAU (link), use dramatic or satirical tones to reinforce anti-globalist and anti-media messaging.

In addition to the network analysis conducted for RQ1, we employed targeted keyword searches and thematic exploration to identify further relevant actors in the ecosystem. Among these, @Eys2C (link) emerged as a politically oriented channel promoting critical engagement with dominant climate narratives. Furthermore, through RQ2, we found additional channels overlapping with those from the network analysis (e.g., @tironianae, @toresaysPlus (link), @redpillpharmacist (link), @worlddoctorsalliance, and @australiaoneparty_official) as well as others that were not previously detected.

These include @captkylepatriots (link), who blends spiritual awakening with anti-establishment and climate-skeptic messages; @vigilantfox (link), who downplays climate urgency and emphasizes the benefits of CO₂; @lauraabolichannel (link), a spiritual activist who critiques climate narratives as tools for elite control; and @qthestormrider777 (link), whose content links deep state conspiracy theories with climate disinformation. These four actors often forward each other’s content, forming a tightly knit community of climate skepticism with high engagement.

Additional channels emerged from RQ3, particularly those directly referencing climate themes. @BlackHelicopters, for instance, focused on climate as a cover for global weather manipulation, though it was blocked on July 3rd. @DutchsinseFans (link) is more technically oriented, providing real-time seismic alerts with limited ideological framing. @Real_JFK_Jr_ (link), tied to QAnon ideologies, circulates climate denial as part of a broader rejection of institutional legitimacy.

Through this multi-step, mixed-methods approach, we identified not only isolated narratives but also structural communities and recurring amplification circuits that reveal the coordinated nature of climate disinformation on Telegram.

Link to a spreadsheet about the different actors found here

4.4 Thematic analysis

a) From Discrete Narratives to Grand Conspiratorial Ecosystem

Initial analysis sought to identify distinct climate disinformation narratives, but the frequency data reveals a more complex reality. Rather than separate stories, we discovered an interconnected grand conspiratorial ecosystem where climate disinformation operates as one component of a larger apocalyptic meta-narrative.

Grand-Conspiracy as Meta-Framework

The "Grand-conspiracy" theme emerged as a central organizing principle throughout the coded messages, operating as an overarching narrative structure that absorbs and integrates what initially appeared to be discrete disinformation themes. It ranks third (F: 25) in frequency confirming this assumption. The thematic analysis reveals how this conspiracy framework transcends specific climate topics by connecting seemingly unrelated elements: messages link Hurricane Helene to government weather modification programs, frame carbon reduction policies as elite population control schemes, and present climate data as fabricated by tech companies working with shadow government agencies. For example, a single message might claim that "they" are using HAARP technology to intensify hurricanes, while simultaneously arguing that climate scientists are paid by globalist elites to manufacture crisis narratives that justify increased surveillance and control over ordinary citizens. ​​

Integrated Anti-Establishment Ecosystem

The analysis identified how anti-institutional themes weave together multiple conspiratorial threads: global elite demonization, government-tech doom, Deep State coordination, anti-state sentiment, and anti-woke cultural messaging. Rather than discrete grievances, these represent facets of a single oppositional worldview that positions climate action as part of a broader authoritarian overreach orchestrated by global elites using big-tech surveillance and deepstate coordination.

b) Emotional Architecture

Suspicion-Fear-Distrust Triangle

The emotional codes show sophisticated psychological targeting: "Suspicion", "Fear", and "Distrust" form the core emotional framework. This creates a defensive psychological state where climate information is automatically suspect. "Outrage" then channels this defensive posture into active opposition, framing climate action as an existential threat to personal freedom rather than environmental protection. The consistent frequency across different climate contexts suggests standardized emotional manipulation regardless of topic.

In-Group/Out-Group Boundary Construction

The emotional appeals consistently serve to heighten engagement and reinforce community boundaries, creating a defensive posture that channels into active opposition. The thematic analysis reveals how these emotional strategies build group identity around shared threats and enemies.

c) Tactical Ecosystem

Community Mobilization as Primary Strategy

The most prominent tactical theme centers on community building and group mobilization, showing how climate disinformation prioritizes building identity and group belonging over simple persuasion. Messages consistently include calls to join groups, share content, and engage in collective action, suggesting community formation as a core strategic objective.

Epistemic Warfare Tactics

A significant thematic pattern involves systematic attempts to delegitimize climate science through creating alternative knowledge frameworks. The analysis reveals how messages don't simply deny climate science but actively construct counter-epistemic authority through selective deployment of scientific-sounding arguments and cherry-picked evidence presentation. Together with the “call for tribe” this epistemic warfare indicates this isn't just about opposing science but creating alternative reality networks.

Commercialization and Professionalization

A consistent theme throughout the dataset involves the integration of commercial elements - advertisements, subscription calls, and monetization strategies - suggesting that these narratives operate within a professionalized media ecosystem rather than organic grassroots communication. Ads for supplements or doomsday prepping equipment indicate systematic monetization, while the sensationalist tone, and click-bait headlines drive engagement and show sophisticated attention-capture technique. Personal testimony and tokenized examples provides an authenticity veneer, while cherry picking data and presenting selective empirics creates pseudo-scientific credibility.

d) Weather Modification as Central Theme

The general belief in the manipulation or modification of weather, with or without mentioning HAARP emerges as one of the central themes. This suggests weather modification isn't just another conspiracy theory but the primary vehicle for connecting climate events to grand conspiracy narratives. "Hurricane Helene" provides the specific focal point for this broader theme, with strong co-occurrence patterns with anti-state messaging, this suggests that again government technology is being used to control not only the weather but also “us”.

Climate-Change-Hoax Integration

Many narratives generally claim climate change to be a hoax and are even going so far to take a “Pro-CO2” stance. In the thematic analysis we identified that these two narratives work together to create alternative climate narratives. The "Pro-CO2" includes beneficial “CO2 fertilisation claims" and show systematic inversion of climate science, positioning carbon emissions as beneficial rather than harmful.

e) Word Tree

To examine how the disinformation narratives appear in the 62 messages, we used 4CAT to generate a Word Tree. The word tree illustrates the narrative patterns that emerged from the 62 curated messages. The visualization reveals that climate discourse is closely intertwined with the concept of climate change, which is frequently framed as a phenomenon perceived to be unreal or not occurring.

4.5 Implications: Understanding the Ecosystem

This thematic analysis began by seeking to identify discrete climate disinformation narratives but uncovered something far more complex: a grand conspiratorial ecosystem where climate disinformation operates as one component of a profitable apocalyptic meta-narrative. Rather than standalone climate skepticism, the analysis revealed how messages systematically weave together deepstate theories, big-tech doom scenarios, weather manipulation claims, and anti-establishment sentiment into coherent worldviews that transcend any single issue domain.

The dominant narratives center on three interconnected themes: epistemic warfare that positions climate science as elite deception, weather modification conspiracies that frame natural disasters like Hurricane Helene as artificially created events, and community mobilization that builds group identity around shared threats and enemies. These narratives operate through sophisticated emotional architecture—suspicion, fear, and distrust—that creates defensive psychological states where climate information becomes automatically suspect and climate action represents existential threats to personal freedom.

Telegram's platform affordances prove crucial to this ecosystem's functionality. The platform's group-based structure enables rapid community formation and migration, while forwarding mechanisms amplify cross-referencing patterns that seamlessly blend hurricane footage with HAARP theories and commercial advertisements. Minimal content moderation provides space for apocalyptic meta-narratives to develop uninterrupted, while encrypted messaging reinforces the "insider knowledge" positioning that characterizes the millenarian conspiracist voice throughout the dataset.

The commercial integration reveals perhaps the most significant finding: this operates as a profitable meaning-making system where apocalyptic narratives directly feed business strategies. Messages warning of climate manipulation by global elites seamlessly transition into advertisements for emergency preparedness supplies, creating coherent experiences where "buying the narrative of climate war grants you reality and supplements for doomsday survival." This business model validates conspiracy frameworks while ensuring ecosystem sustainability beyond ideological motivation.

Ultimately, the analysis demonstrates that climate disinformation cannot be understood in isolation but must be recognized as part of a broader apocalyptic business ecosystem that provides profitable explanations for complex global changes. The thematic integration creates self-reinforcing interpretive systems where any event—floods, hurricanes, or seemingly unrelated topics—becomes evidence for pre-existing conspiracy structures, suggesting that traditional fact-checking approaches prove insufficient against this coordinated narrative warfare that transcends environmental concerns entirely.

4.6 Common influencers and narratives found

The most prominent finding is the existence of a central group of actors who appear not only in the network analysis (RQ1) but also across additional search strategies and research questions (RQ2 and RQ3), highlighting their structural and thematic relevance. Among these, @tironianae and @australiaoneparty_official stand out for their consistent focus on HAARP and climate engineering, blending populist and conspiratorial messaging. @worlddoctorsalliance, although originally focused on health misinformation, plays a central role in integrating climate skepticism into broader anti-scientific discourse.

@toresaysPlus and @redpillpharmacist are similarly relevant, promoting distrust in institutions and regulatory frameworks, often framing climate policies as tools of surveillance or control. Another key figure is @captkylepatriots, who mixes spiritual and political language to frame climate action as a threat to individual freedom. This channel also connects frequently with @vigilantfox, @lauraabolichannel, and @qthestormrider777—all of whom appeared in the RQ2 results and are part of a content-sharing ecosystem reinforcing climate disinformation from different narrative angles.

Finally, @Eys2C provides an example of a more politically analytical tone, yet still promotes critical takes on mainstream climate discourse. Its inclusion across different methods confirms its relevance within the broader disinformation ecosystem.

These actors not only repeat similar narratives but actively amplify each other's content, making them key nodes in the network of climate denial and conspiracy, and validating their strategic importance across methods.

5. Conclusions

6. References

Rogers, 2020 Rogers R (2020) Deplatforming: Following extreme Internet celebrities to Telegram and alternative social media. European Journal of Communication 35(3): 213–229. https://doi.org/10.1177/0267323120922066

Intergovernmental Panel on Climate Change (IPCC). (2023). Climate Change 2023: Synthesis Report. Retrieved from https://www.ipcc.ch/report/sixth-assessment-report-cycle/

Lewandowsky S, Ecker UKH and Cook J (2017) Beyond Misinformation: Understanding and Coping with the “Post-Truth” Era. Journal of Applied Research in Memory and Cognition 6(4): 353–369. https://doi.org/10.1016/j.jarmac.2017.07.008

UNESCO. (2024). Global Initiative for Information Integrity on Climate Change. Retrieved from https://www.unesco.org/en/information-integrity-climate-change

Treen KM d’I., Williams HTP and O’Neill SJ (2020) Online misinformation about climate change. WIREs Climate Change 11(5): e665. http://dx.doi.org/10.1002/wcc.665

Urman, A., & Katz, S. (2022). What they do in the shadows: Examining the far-right networks on Telegram. Information, Communication & Society, 25(7), 904–923. https://doi.org/10.1080/1369118X.2020.1803946

Santos, M., Park, C. S., Santos, J. G. B., Cavalini, A. & Gil de Zúñiga, H. (2025). Latent Bombs of Disinformation. Information, Communication & Society. https://doi.org/10.1080/1369118X.2025.2492575.

Tucci, G. (2025a). Telegram Public Channels [Politics; News & Media—English language] [Dataset]. Zenodo. https://zenodo.org/records/15427948.

Tucci, G. (2025b). Telegram Analytics (Version 1.0.0) [R]. https://doi.org/10.5281/zenodo.15645166.

Ruscica, G., Tucci, G., & Carneiro, B. (2025). TeleCatch: An open-access software for visualizing, filtering and extracting Telegram messages data. Software Impacts, 23, 100736. https://doi.org/10.1016/j.simpa.2024.100736