Accountability 2.0: traditional media versus pure players and digital platforms

Abstract: 

Criticism in journalism has become a core accountability instrument in recent years (Rodriguez, Mauri & Fedele, 2017; Lasorsa, Lewis & Holton, 2012; Bichler, 2012). The democratization of communication flows (Kovach and Rosenstiel, 2001, Bordevijk and Van Kaam, 1986; Wardle and Derakhshan 2018, Usher, 2019) has open the field to a massive and public input from the audience, key for the business in the roles of reader, subscriber and commentator (Borger, 2016; Simson, 2015; Nielsen, 2014. Deuze & Witschge, 2017; Craft, Vos and Wolfgang, 2016; Boczkowski and Mitchelstein, 2015; Korson, 2014). To delve both into social conversation as an instrument of accountability and the social challenges posed by new media and digital platforms, we analyze in this paper twelve months of social conversation on Twitter around 10 leading news media published in Europe, US and Iberoamerica and 10 pure players and digital platforms (The Huffington Post, Reddit, Buzzfeed, Voxdot.com, Wikitribune, Twitter, Facebook, Global voices, Slashdot, Yahoo News and Google News) to identify global trends and critical issues for each subset (RQ). A twelve-month search using the keyword 'Journalism' produced 344,800 tweets related to both subsets (1), the majority of them related to the first subset (traditional media). Findings show and outstanding flow of social conversation (a total of 308,000 messages) associated to the 10 traditional leading news media from US, Europe and Iberoamerica analyzed in this study Only 36.400 messages related to The Huffington Post, Reddit, Buzzfeed, Voxdot.com, Wikitribune, Twitter, Facebook, Global voices, Slashdot, Yahoo News and Google News were found. Our findings raise concerns about the limited scope of the social conversation on pure players such as Facebook or Twitter and their roles regarding the news, despite their increasing influence on journalism.

(1) The presence of bots/possible bots was established in 1% and 4,7% of the sample respectively by the algorithm integrated in Atribus.