Is for Fake News / Filter Bubbles / Framing Howu Politicians Frame Media (Content) on Facebook & Twitter During the Dutch Tweede Kamer
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‘F’ is for fake news / filter bubbles / framing Howu politicians frame media (content) on Facebook & Twitter during the Dutch Tweede Kamer elections of 2017 M.A. Wieringa, BA (5670705) Utrecht University, the Netherlands Media & Performance Studies / 2016-2017 Research master thesis First reader and supervisor: dr. Mirko Tobias Schäfer Second reader: dr. Ingrid Hoofd July 6th 2017 Abstract With the election of Donald Trump, the Brexit, and the Ukraine referendum in the Netherlands, the relationship between politics and journalism seems altered. This seems to be emphasized by the way in which certain politicians frame their relation to journalists and the media. This thesis concerns itself with the way in which Dutch (aspiring) politicians frame the media and their content. Tweets and Facebook page posts of politicians and political parties were collected during the period January 1st 2017 up to and including the election day, March 15th 2017. These messages were filtered for references to the media, and subsequently a 1% random selection was made which was qualitatively analyzed using a synthesized model. The applied model is based on relational frame theory, framing theory, and the encoding/decoding model. Randomly selected messages were assessed on what kind of encoding strategy was used, and whether the subject of the frame was either the medium itself or its content. It was found that the predominant encoding strategy was a dominant- hegemonic (i.e. endorsing) one (68-72%). In one in five messages a negotiated strategy was used (20-21%), and only in 11-7% of the cases an oppositional strategy was found. The great majority of these messages deals with media content (83-90%), as opposed to a medium as a whole (17-10%). Politicians were found to predominantly make media references which fit their views. Online media are particularly vulnerable to this, as individual articles are now presented as complete products, and not as part of the newspaper bundle, for example. This cherry-picking behavior of politicians, can lead to a dissipation of the adversarial principle within their newsfeeds, which is why the media have to reflect on their ability to reach the constituents of the politicians. Several recommendations to reduce decontextualization are made. Executive summary It was found that the predominant encoding strategy was an endorsing one (68-72%). In one in five messages a negotiated strategy was used With the election of Donald Trump, the Brexit, and the Ukraine (20-21%), and only in 7-11% of the cases an oppositional strategy was referendum in the Netherlands, the relationship between politics and found. The great majority of these messages deals with media content journalism seems altered. The traditional media still play a big role, (83-90%), as opposed to a medium as a whole (10-17%). but now they are used by the politicians to enhance, strengthen, and endorse their own views. In earlier research, commissioned by het Nederlands Genootschap van Hoofdredacteuren (the Dutch Association of Editors- in-chief), we found this prevalent framing behavior. The rise of online articles, for instance, greatly facilitates this. Now, the product is not a newspaper with articles in it: the products are the individual articles, which are separated from their context. This allowed politicians to become editor-in-chiefs of their own feeds, where the adversarial principle no longer holds sway; the gatekeepers of old, are now the ‘gatekept’. In this thesis, I concern myself with an in-depth assessment of what frames were used by politicians in the Dutch elections for the Tweede Kamer (House of Representatives) of 2017, when referring to media. Both the type of frame, and what is framed (the medium in its entirety, or the media content), is inventoried. In total, 240,498 tweets and 24,091 Facebook page posts were collected in the period from January 1st up to and including March 15th 2017 (which was the actual election day). Of these, 44.166 tweets and 5.774 Facebook page posts were found to contain a media reference. 1% of this sample was randomly selected to be qualitatively analyzed (442 tweets and 58 Facebook page posts). These messages, and the material they contained, or linked to, were each analyzed, using a synthesized model. For each message, the encoding strategy – that is the way in which this message was packaged by the sender (endorsement/oppositional/negotiated) was inventoried, as well as whether it only referred to particular content, or the medium in its entirety. About the author Maranke Wieringa (1992) is an rMA student of the media & performance studies program at Utrecht University, and a junior researcher at Utrecht Data School. She specializes in software studies and scholarly data analysis. Maranke holds a BA in cultural studies from Radboud University, and participated in the Radboud Honours Academy. She published several articles on interface analyses, and software practices. Research projects she was involved in focused – among others – on news ecosystems, and social media use by politicians running for the Dutch House of Representatives. Preface Acknowledgements Een facebookpagina of twitteraccount [is] een handig middel voor een Just as it takes a village – and a huge amount of patience - to raise a politicus waarin uiteraard alleen het gewenste geluid wordt gecommuniceerd child, there’s a mass of people who helped give rise to this thesis. met het publiek. Politici zijn hierbij redacteur van hun eigen While the list is by no means complete, I want to extend my thanks to newsfeed,waarbij niet aan hoor en wederhoor hoeft te worden gedaan […]. the following people explicitly: my parents who always stood by me. – Wieringa, De Winkel & Lewis (2017, p. 58)1 My family-in-law, who have accepted me into their family as if I was their own. I thank my dear friends who were always happy to listen, and part with some hugs. I also want to extend my thanks to my colleagues at the Utrecht Data School: my work there has convinced This thesis was preceded by an investigation into the social media me that academia is the place for me – that we can combine practice usage of politicians during the Dutch Tweede Kamer elections by the and theory. That experience helped me to – as the British (and Utrecht Data School. This research was commissioned by the Dutch Gallifreyans) put it – keep calm and carry on. Last, but certainly not Association of Editors-in-chief, which was most interested whether least, I wish to thank my partner, Michel, who always supported me traditional media still played a significant role during these elections. unconditionally, and my fluffy stepdaughter Joy who always managed Together with my colleague Tim de Winkel, and our research assistant to cheer me up by means of a tennis ball. Callum Lewis, I set out to answer these broad questions. The passage quoted above, was the most troubling finding of Wie is de waakhond op sociale media2. Traditional media are still relevant, they are part of the bigger discussion; yet, they do not enter the discussion on their own terms, but rather serve as a means of legitimation for politicians. Online media are vulnerable for politicians’ cherry-picking behavior. So what is a media and data scholar to do? I set out to explore the matter of framing more thoroughly in this thesis. For if we understand the manner in which media are employed to promote one’s political agenda, then it might help us to think of counter measures, eventually. 1 A Facebook page or a Twitter account is a convenient tool for a politician, in which only the preferred message is communicated with an audience. Politicians here are editors of their own newsfeeds, where they do not need to apply the adversarial principle. 2 Our research was titled Wie is de waakhond op sociale media (Who is the ‘guard dog’ on social media). Table of content 3. The context of the frames .................................................................................. 14 1. Introduction ............................................................................................................... 1 3.1. Platform analyses ......................................................................................... 14 1.1. Societal context and relevance .................................................................. 1 Facebook .............................................................................................................. 14 1.2. Research questions ........................................................................................ 2 Twitter .................................................................................................................. 15 1.3. Hypotheses ........................................................................................................ 2 3.2. News on the platforms ............................................................................... 16 1.4. Corpora ............................................................................................................... 3 Facebook .............................................................................................................. 17 1.5. Method ................................................................................................................ 3 Twitter .................................................................................................................. 17 UDS project: Wie is de waakhond op sociale media? .......................... 3 3.3. How politicians use Facebook and Twitter