By being embedded in everyday life, social networking sites (SNSs) have altered the way campaign politics are understood and engaged with by politicians and citizens alike. However, the actual content of social media has remained a vast but somewhat amorphous and understudied entity. The study reported here examines public sentiment as it was expressed in just over 1.42 million social media units on Facebook and Twitter to provide broad insights into dominant topics and themes that were prevalent in the 2012 U.S. election campaign online. Key findings include the fact that contrary to what one might expect, neither presidential candidate was framed in an overly critical manner in his opponent’s Facebook space nor on Twitter’s dedicated nonpartisan election page. Beyond this, similarities and divergences in sentiment across social media spaces are observed that allow for a better understanding of what is being communicated in political social media.
This study analyzes mainstream media (MSM) coverage of fake news discourse and compares it with social networking sites (SNS) users who reference the term “fakenews” in their tweets. The study employs computational methods by analyzing over 8 million tweets and 1,350 news stories using topic modeling. Building on the theory of (networked) gatekeeping and Herman and Chomsky’s propaganda model, the results show that SNS users follow networked gatekeeping practices by mostly associating fake news references to the alleged bias of MSM. On the other hand, MSM coverage tends to link fake news to SNS’s negative role in spreading misinformation. I argue here that there is a networked flak activity on Twitter which is defined as a collective negative response to MSM in order to discipline it, change its tone and editorial stance, or undermine the public’s trust in it.
Purpose-The purpose of this paper is to examine one of the largest data sets on the hashtag use of #fakenews that comprises over 14m tweets sent by more than 2.4m users. Design/methodology/approach-Tweets referencing the hashtag (#fakenews) were collected for a period of over one year from January 3 to May 7 of 2018. Bot detection tools were employed, and the most retweeted posts, most mentions and most hashtags as well as the top 50 most active users in terms of the frequency of their tweets were analyzed. Findings-The majority of the top 50 Twitter users are more likely to be automated bots, while certain users' posts like that are sent by President Donald Trump dominate the most retweeted posts that always associate mainstream media with fake news. The most used words and hashtags show that major news organizations are frequently referenced with a focus on CNN that is often mentioned in negative ways. Research limitations/implications-The research study is limited to the examination of Twitter data, while ethnographic methods like interviews or surveys are further needed to complement these findings. Though the data reported here do not prove direct effects, the implications of the research provide a vital framework for assessing and diagnosing the networked spammers and main actors that have been pivotal in shaping discourses around fake news on social media. These discourses, which are sometimes assisted by bots, can create a potential influence on audiences and their trust in mainstream media and understanding of what fake news is. Originality/value-This paper offers results on one of the first empirical research studies on the propagation of fake news discourse on social media by shedding light on the most active Twitter users who discuss and mention the term "#fakenews" in connection to other news organizations, parties and related figures.
This study examines the news selection practices followed by news organizations through investigating the news posted on social networking sites and, in particular, the Facebook pages of four foreign Arabic language TV stations: The Iranian Al-Alam TV, Russia Today, Deutsche Welle, and BBC. A total of 15,589 news stories are analyzed in order to examine the prominence of references to countries and political actors. The study reveals that social significance and proximity as well as the news organizations’ ideological agenda are the most important elements that dictate the news selection process.
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