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Patterns of Type and Content in an Online Policy Controversy392would be the neutral, which applies a neutral discourse aiming more to inform than to defend a position.We first designed queries representing pro-exploration, anti-exploration and neutral positions. Based on Hopke and Simis (2017), we adopted the three keywords: ‘fracking’, to represent the anti-position (opponents); ‘shale gas’, as a pro-position (proponents); and ‘hydraulic fracturing’ as a neutral expression.7 We opted to use Google to identify a source list of actors that debated it online. This search engine also operates as a ranker for actors (websites) in each social issue (keywords queried), which points to the trends of dominant voices online and their concerns (Rogers, 2017, 2019). Using the tool Googlescraper (Lippmannian Device)8, we scraped top-ranked URLs per country, querying different searches for each keyword. We scraped the 15 most relevant results according to Google’s rank algorithm (duplicates resulted in fewer data points). Then, we merged the outputs per search in a single list of the most significant actors and URLs per country.The second step was manually classifying the URLs as an informant (a general website mentioning actors, news webpages like bbc.com) or an actor itself (an active person or organisation on the debate, like www.greenpeace.org). For informants, we registered the name of actor(s) mentioned, then merged the actors from original URLs with those referred by informants in one single list of actors. Finally, after entering each website and checking for direct declarations, two independent researchers (for validation and bias control) classified them as pro (proponent or supporter), anti (opponent or against) or neutral on shale gas exploration.Our third step involved using the Google Image Scraper9 tool to extract up to 20 top-ranked images connected to the shale gas controversy from their websites with the previously used queries. Obtaining the visual repertoire used by actors in shale gas controversy allows us to understand more about the connection with their positioning and the visuals they chose to adopt. In this step, we identified 7 The three keywords were also investigated in Spanish, in consideration to Mexican publications8 Also known as ‘The Search Engine Scraper’, this tool allows scraping the search results for a given query. It has as output a list of results the search engine returned for the query, algorithmically ranking considered. You can choose which search engine you want to scrape. For this study, we searched on Google. See https://tools.digitalmethods.net/beta/searchEngineScraper.9 This tool uses images.google.com to query specific sites for images connected to particular tags. For each URL given, Google is asked if a keyword occurs on each URL. Creators alert that Google uses its algorithms for determining if a particular image belongs to a specific keyword, so it is by no means exhaustive, correct or complete. See https://tools.digitalmethods.net/beta/googleImages.Efrat.indd 39 19-09-2023 09:47