3,932 research outputs found
Trump, Twitter, and news media responsiveness: a media systems approach
How populists engage with media of various types, and are treated by those media, are questions of international interest. In the United States, Donald Trump stands out for both his populism-inflected campaign style and his success at attracting media attention. This article examines how interactions between candidate communications, social media, partisan media, and news media combined to shape attention to Trump, Clinton, Cruz, and Sanders during the 2015–2016 American presidential primary elections. We identify six major components of the American media system and measure candidates’ efforts to gain attention from them. Our results demonstrate that social media activity, in the form of retweets of candidate posts, provided a significant boost to news media coverage of Trump, but no comparable boost for other candidates. Furthermore, Trump tweeted more at times when he had recently garnered less of a relative advantage in news attention, suggesting he strategically used Twitter to trigger coverage.Accepted manuscrip
Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections
Adversarial interactions against politicians on social media such as Twitter
have significant impact on society. In particular they disrupt substantive
political discussions online, and may discourage people from seeking public
office. In this study, we measure the adversarial interactions against
candidates for the US House of Representatives during the run-up to the 2018 US
general election. We gather a new dataset consisting of 1.7 million tweets
involving candidates, one of the largest corpora focusing on political
discourse. We then develop a new technique for detecting tweets with toxic
content that are directed at any specific candidate.Such technique allows us to
more accurately quantify adversarial interactions towards political candidates.
Further, we introduce an algorithm to induce candidate-specific adversarial
terms to capture more nuanced adversarial interactions that previous techniques
may not consider toxic. Finally, we use these techniques to outline the breadth
of adversarial interactions seen in the election, including offensive
name-calling, threats of violence, posting discrediting information, attacks on
identity, and adversarial message repetition
Clustering Memes in Social Media
The increasing pervasiveness of social media creates new opportunities to
study human social behavior, while challenging our capability to analyze their
massive data streams. One of the emerging tasks is to distinguish between
different kinds of activities, for example engineered misinformation campaigns
versus spontaneous communication. Such detection problems require a formal
definition of meme, or unit of information that can spread from person to
person through the social network. Once a meme is identified, supervised
learning methods can be applied to classify different types of communication.
The appropriate granularity of a meme, however, is hardly captured from
existing entities such as tags and keywords. Here we present a framework for
the novel task of detecting memes by clustering messages from large streams of
social data. We evaluate various similarity measures that leverage content,
metadata, network features, and their combinations. We also explore the idea of
pre-clustering on the basis of existing entities. A systematic evaluation is
carried out using a manually curated dataset as ground truth. Our analysis
shows that pre-clustering and a combination of heterogeneous features yield the
best trade-off between number of clusters and their quality, demonstrating that
a simple combination based on pairwise maximization of similarity is as
effective as a non-trivial optimization of parameters. Our approach is fully
automatic, unsupervised, and scalable for real-time detection of memes in
streaming data.Comment: Proceedings of the 2013 IEEE/ACM International Conference on Advances
in Social Networks Analysis and Mining (ASONAM'13), 201
The Digital Architectures of Social Media: Comparing Political Campaigning on Facebook, Twitter, Instagram, and Snapchat in the 2016 U.S. Election
The present study argues that political communication on social media is
mediated by a platform's digital architecture, defined as the technical
protocols that enable, constrain, and shape user behavior in a virtual space. A
framework for understanding digital architectures is introduced, and four
platforms (Facebook, Twitter, Instagram, and Snapchat) are compared along the
typology. Using the 2016 US election as a case, interviews with three
Republican digital strategists are combined with social media data to qualify
the studyies theoretical claim that a platform's network structure,
functionality, algorithmic filtering, and datafication model affect political
campaign strategy on social media
Startup communities: notes on the sociality of tech-entrepreneurs in Manchester
In this contribution I explore the conflicting moralities and practices of technology entrepreneurship through the lenses of Mary Douglas’ Grid-Group Cultural Theory. Starting from the distinction between communitarian, individualistic and hierarchical culture, I explore my empirical material drawn from ethnographic fieldwork in Manchester, UK. In particular, I describe the sociality of young male tech-entrepreneurs at networking events, ‘coffices’ and coworkspaces around an urban ‘creative quarter’. I argue that ‘startup communities’ simultaneously encourage individualistic market-competition, contribute to feelings of local group-belonging and are narrative constructions promoted by entrepreneurs, corporations and the State.Universidad de Sevill
Practitioner perceptions: critical junctures and the global emergence and challenges of fact-checking
Since 2003 and the emergence of FactCheck.org in the United States, fact-checking has expanded both domestically and internationally. As of February, 2016, the Duke Reporter’s Lab identified nearly 100 active initiatives around the world. This research explores why fact-checking is spreading globally at this point in time. Seen as a professional reform movement in the journalistic community (Graves, 2016), historical research on reform movements suggest several possible factors influencing the emergence of fact-checking including a decline in journalism, easy access to technology for the masses, and socio-political strife (McChesney, 2007; Pickard, 2015; Stole, 2006). Using a phenomenological approach, two focus groups were conducted among fact-checkers during the 2015 Global Fact-checking Summit in London, England. Participants shared rich experiences about conditions and contexts surrounding the emergence and challenges facing their organizations. Ultimately, as the purpose of this research is to help future fact-checkers around the world become aware of the circumstances under which fact-checking is most likely to emerge and thrive (or fail), recommendations from current global practitioners are offered.Accepted manuscrip
Effective Social Media Use by Law Enforcement Agencies: A Case Study Approach to Quantifying and Improving Efficacy and Developing Agency Best Practices
In the wake of protests against law enforcement for an array of reasons, law enforcement officers and agencies have a responsibility to recognize and utilize the available mediums of communication with which they may best develop a connection to the communities they serve. Furthermore, law enforcement agencies must be informed that established, traditional methods of news dissemination – such as press conferences and printed articles – are now both ineffective and under-utilized, replaced in large part by social media live-time reports. For that reason, law enforcement agency executives must address both the responsibility to provide appropriately timed updates to critical incidents and events, and utilize the opportunity to engage their community through a widely utilized and accepted medium of communication. Both require an understanding of social media, its application, and its efficacy both literal and perceived
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