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The Bundestagswahl 2017 was an earthquake to Germany's political landscape. With the AfD an illiberal and openly xenophobic party became the third-largest force in parliament. Its rise over just four years is unlike anything seen in Germany before.
The new media landscape has often been touted as a key component of the rise of the AfD. More than any other party the AfD has made frequent use of the "populist playbook" -- stirring controversy through inflammatory rhetoric before back-pedalling and slamming the "Lügenpresse" (mendacious press). More than this, though, no other party has been as successful in directly connecting to and communicating with followers on Facebook to spread their "real" messaging outside mainstream media channels. Likewise, the proliferation of distinctly right-wing, rabble-rousing "news"-blogs and spread of these "news" on social media have given the far right an unfiltered platform to communicate with supporters. This has fundamentally shaken what scholars know about mass communication and agenda setting processes during elections.
Still, despite many analyses and investigations we do not really know what actually went on during the 2017 campaign in Germany. Lots of attention has been devoted to the question if the AfD received too much space for presenting itself vis-a-vis the other parties in mainstream and social media channels. Yet, to our knowledge, no systematic investigation of these dynamics has been undertaken in Germany. We attempt here to undertake this investigation.
Starting in early July of 2017 we used Python-based automated web scraping to access eight German-language "news"-blogs popular within networks of the extreme political right. Between July and September we collected almost 4500 articles from these right-leaning sites. In addition, using the Facebook-Graph-API we collected the shares and likes of each post from the Facebook-presences of those same blogs (where available). Simultaneously, we also collected mainstream media content. Using the Factiva and Lexis-Nexis news databases, we downloaded and parsed almost 6000 texts from both print as well as online media for the same period of time. Finally, to help capture public sentiment during the campaign, we collected all German tweets from Mid-August onward (roughly 90 GBs of data) alongside Google search trends data.
The texts from these three ecosystems - right-wing fringe blogs, mainstream media, and public internet search and sentiment data - serve as data to use automated content analysis, build topic and machine learning models, and run time series cross sectional analyses to understand the possible relationships between and within each area. This allows us to understand the co-integrated processes between media/public spheres and identify what was talked about, when it was talked about, and how it was talked about.
Overall these data allow us to paint picture of campaign discourse in Germany. We can present answers to a number of questions: Did the AfD actually receive a disproportionate amount of attention? Do these separate media ecosystems influence one another? Who leads, who follows? How do political elites interact with the public via old and new media? Who is driving topics? Overall, this project presents a snapshot of the campaigning season for Germany in the year 2017. We unveil the dynamics brought about by new forms of public discourse.
About the researchers who collected and analysed this data:
Alexander Beyer initially attended Eberhard-Karls-University in Tübingen, and is now a PhD-student at <A HREF="http://www.sfu.ca/politics.html">Simon-Fraser-University</A>in Vancouver. His research focuses on the communications strategies of right-wing parties and the strategic responses of mainstream parties to these extremists. He is also interested in automated data collection, as well as network and text analysis.
Denver McNeney (<A HREF="https://twitter.com/denvermcTwitter/">@DenverMc</A>) is a Ph.D. Candidate at the Centre for the Study of Democratic Citizenship at McGill University and works as a data scientist at a language processing startup in Vancouver. McNeney’s research primarily focuses on the sources and consequences of heterogeneity in public opinion. Additional work focuses on automated text analyses and text-as-data approaches alongside time series and panel quantitative methodologies.
<A HREF="http://www.sfu.ca/~sweldon/">Prof. Steven Weldon</A> heads the research team on Political Extremism and Democracy in which Alexander Beyer and Denver McNeney are working. He is a Professor of Political Science and the Director for the Centre for the Study of Public Opinion and Political Representation at Simon Fraser University in Vancouver, Canada. He spent a year as a Fulbright-Scholar in Potsdam. His research focuses on political representation, European integration, political behaviour, and diversity and multiculturalism.