There is a growing body of documentary evidence showing that the fossil fuel industry knew for decades that CO2 caused climate change, and subsequently cultivated doubt concerning climate science, the solutions, and who bears the responsibility for the harm. The climate sceptics networks in the US has been well documented (e.g. exxonsecrets) and subject to prior research at the DMI summer school.
This project focuses on the question if the agenda of the industry, often represented by trade associations has manifested itself in the digital sphere and in contrast know if there is a response of NGOs around this issue.Introduce the subject matter, and why it is compelling / significant.
1. Business Europe, @BUSINESSEUROPE
2. Confederation of European Paper Industries (CEPI), @EuropeanPaper3. Eurelectric, @EURELECTRIC
4. EUROFER – The European Steel Association @EUROFER_eu
5. Eurometaux – The European Association of Metals
6. European Chemical Industry Council (Cec)
7. FuelsEurope (formerly known as EUROPIA)
8. International Association of Oil and Gas Producers (OGP).Secondary ones:
• International Air Transport Association (IATA)
• International Emissions Trading Association (IETA)
• Glass Alliance Europe
• Biotechnology Industry Organisation (BIO)
• Carbon Capture and Storage Association (CCSA)
• Central Europe Energy Partners (CEEP)
• European Automobile Manufacturers Association (ACEA)
• European Union of the Natural Gas Industry (Eurogas)
• International Chamber of Commerce
• International Fertilizer Industry Association
• International Petroleum Industry Environmental Conservation Association (IPIECA)
• The European Roundtable of Industrialists
• American Chamber of Commerce to the European Union
• European Energy Forum
“Climate Change” Language on Google
In order to know the language used around the topic of “climate Change” our approach was to investigate Google as an “authoring device” (Rogers 86, 2013). First, the “Google harvest” tool was utilized to obtain the top 100 search results for the query [Climate Change]. From this data set the parent URL sites were gathered and manually edited to have an specific set, rather than pages that contained several off-topic information (e.g. News Media). This top sources were then categorized by type of site: Media, Academic, Governmental and Intergovernmental and by geographical location.
From this dataset and the knowledge of the issue expert, we analyzed the most used keywords that could be representative of the pro and con discourse around climate change in Google. The keywords were classified into two groups considering the different actors. Program keywords which include ‘clean` energy groups and NGO’s versus Anti-Program keywords, which include ‘dirty’ energy groups and trade association.Consequently, to further investigate which party’s rhetoric is more present, we scraped the parent top 100 google sites in combination with the set of keywords for “Program” and “Anti-Program” accordingly.
Fig. 1: The list of keywords was identified for the two actors groups in the research.Data gathering tools: Harvester, Google Scraper (Lippmannian Device). Visualization tools: Tableau, Raw.
‘Dirty’ energy more present through hits on Google.
The data analyzed showed the presence or absence of Program and Anti-Program parties in Google Searches. When looking into the total hits, according to google, the keywords associated with the Anti-Program are most dominant.
Fig. 2: Comparison of the presence of keywords from the Program (NGO and Clean Energy) and the Anti-Program (‘Dirty’ Energy Trade Association) in percentage.
Most dominant keywords for program and anti-program
Scoping in on the two actor groups individually, the results showed that the two most dominant keywords presented each their actor group. The Anti-Program had as the most dominant keyword [energy security], while the Program had the second most dominant keyword to be [renewable energy]. These keywords could be interpreted as each other’s counterparts, indicating the core of the online debate is concerned with these two oppositions.
Fig. 3: The most dominating keywords in hits according to Google, divided into program and anti-program.Campaign words had little resonance
The Program's keyword [100% renewable] has been a part of a campaign "Go 100% Renewable Energy" (see: http://www.go100percent.org/cms/). However, the hits on Google, did not indicate the expected resonance in the digital sphere. On the contrary it was among the least prominent of the Programs keywords. It is, however, related to their most dominant keyword [renewable energy]. This also seemed to be the case for the Anti-Program whose keyword [deindustrialisation], a keyword only used by the anti-program associations, was the keyword with the least hits.
Fig. 4: The least dominant keywords in hits according to Google, divided into Program and Anti-Program.Mixed keywords divided by source categories
The parent sites for the top 100 query was categorised according to the expert, which showed interest for the different parent sites. This categorisation ilustrate that "national government" and "academic" sites were mostly dominated by keywords from the Program, whereas "intergovernmental organisations" and "news media" were dominated by keywords from the Anti-Program.
Fig. 5: Keyword diving by parent site categorisation.
The research’s findings should be seen in the context of process and methodology.There are some technical challenges in this research which have created bias’ that should be taken into consideration in case of further research either building upon this research’s findings or approaching the subject scratch. The Google Scraper was set to search globally, meaning more geographically determined searches most likely will cause other sites on top 100 and other keywords will be more important. The Google Scraper also only looked at whether a keyword was present on a site or not, meaning it did not take recurrence in single websites into consideration. Changing the query settings to e.g. the standard of 100 could open up for other interpretation possibilities of the search results. Among the parent sites that have been used in the research, some some turned out to be more broad than participated, increasing the chance of keywords being used in other contexts than climate change. E.g. Washingtonpost.com had by far the most hits on [energy security] leading to the suspecion on whether the data from the site should be used in the research. The high amount of hits indicates that there was deeper access to washingtonpost.com’s archive of news articles than on other sites and that the keyword may had been occurred in other contexts than of climate change. It was, however, not possible to look further into these suspicions and thus the decision to keep the site within the dataset. The Anti-Program would still be the most dominant even without the large amount of hits from washingtongpost.com. The example of the washingtonpost.com incident shows the importance of assuring the relevance of the parent sites to the top 100 searches that will be used in the final query and the importance of understanding how the Google Scraper is working to identify and pre-actively counter such issues. An approach to accommodate to these challenges could be to divide the parent site into several sub-URL’s depending on the structure of the parent site.
Fig. 6: Showing the amount of hits washingtonpost.com gathered from the Anti-Program keywords. Further studies into this would be beneficial to determine whether washingtonpost.com should be determined as a critical error source in the dataset or if other circumstances are the cause for this significant fluctuation.
Fagan-Watson, Ben, Bridget Elliott, and Tom Watson. “Lobbying by Trade Associations on EU Climate Policy.” London: Policy Studies Institute, 2015. Web. 30 June 2016.
Go 100% Renewable Energy. Renewables 100 Policy Institute. n.d. Web. 30 June 2016.Thibaux, Chloe. “Report: European Perceptions of Climate Change - Profiles for France, Germany, Norway and the UK.” Climate Outreach, 29 June 2016. Web. 30 June 2016.