Birds of a Feather Tweet Together: Integrating Network and Content Analyses to Examine Cross‐Ideology Exposure on Twitter

This study integrates network and content analyses to examine exposure to cross‐ideological political views on Twitter. We mapped the Twitter networks of 10 controversial political topics, discovered clusters – subgroups of highly self‐connected users – and coded messages and links in them for political orientation. We found that Twitter users are unlikely to be exposed to cross‐ideological content from the clusters of users they followed, as these were usually politically homogeneous. Links pointed at grassroots web pages (e.g.: blogs) more frequently than traditional media websites. Liberal messages, however, were more likely to link to traditional media. Last, we found that more specific topics of controversy had both conservative and liberal clusters, while in broader topics, dominant clusters reflected conservative sentiment.     

Political Expression and Action on Social Media: Exploring the Relationship Between Lower‐ and Higher‐Threshold Political Activities Among Twitter Users in Italy

Scholars and commentators have debated whether lower‐threshold forms of political engagement on social media should be treated as being conducive to higher‐threshold modes of political participation or a diversion from them. Drawing on an original survey of a representative sample of Italians who discussed the 2013 election on Twitter, we demonstrate that the more respondents acquire political information via social media and express themselves politically on these platforms, the more they are likely to contact politicians via e‐mail, campaign for parties and candidates using social media, and attend offline events to which they were invited online. These results suggest that lower‐threshold forms of political engagement on social media do not distract from higher‐threshold activities, but are strongly associated with them.     

How political candidates use Twitter and the impact on votes

This study investigates the content characteristics of Twitter during an election campaign, and the relationship between candidates’ style of online campaigning (i.e., politically personalized and interactive communication) and electoral support for those candidates. Thereby, it provides a better understanding of the linkage between the use of Twitter by candidates and effects on preferential votes. Two data sources are used to examine this relationship: first, a quantitative computer-assisted as well as a manual content analysis of tweets posted by political candidates during the Dutch national elections of 2010 (N = 40,957) and second, a dataset containing the number of votes for electable political candidates during that period. The findings show that using Twitter has positive consequences for political candidates. Candidates who used Twitter during the course of the campaign received more votes than those who did not, and using Twitter in an interactive way had a positive impact as well.     

Predicting the ideological orientation during the Spanish 24M elections in Twitter using machine learning

Through the application of machine learning techniques, this paper aims to estimate the importance of messages with ideological load during the elections held in Spain on May 24th, 2015 posted by Twitter’s users, as well as other variables associated with the publication of these types of messages. Our study collected and analysed 24,900 tweets associated to two of the main trending topics’ hashtags (#24M and #Elections2015) used in the election day and build a predictive model to infer the ideological orientation for the messages which made use of these hashtags during Election Day. This approach allows us to classify the ideological orientation of all collected tweets, instead of only tweets that explicitly express their ideological or partisan preferences in the messages. Using the ideological orientation for all tweets predicted by our model, it was possible to identify how messages with a defined ideological load were pushed forward by users with leftist tendencies. We also observed a relationship between these messages and the partisan orientation of those who published them.

     

Does negative campaign advertising stimulate uncivil communication on social media? Measuring audience response using big data

Using the 2012 presidential election as a case study, this work set out to understand the relationship between negative political advertising and political incivility on Twitter. Drawing on the stimulation hypothesis and the notion that communication with dissimilar others can encourage incivility, it was predicted that (1) heightened levels of negative campaign advertising would be associated with increased citizen activity on Twitter, (2) increased citizen activity would predict online incivility, and (3) that increases in citizen activity would facilitate a positive indirect relationship between negative advertising volume and citizen incivility. This theoretical model was tested using data collected from over 140,000 individual Twitter users located in 206 Designated Market Areas. The results supported the proposed model. Additional analyses further suggested that the relationship between negative political advertising and citizen incivility was conditioned by contextual levels of economic status. These results are discussed in the context of political advertising and democratic deliberation.     

Twitter analysis algorithms for Intelligence Circulation System

The convergence of broadcasting and broadband communications network technologies has attracted increasing attention as a means to enrich the television viewing experience of viewers. Toward this end, this study proposes the ‘Intelligence Circulation System (ICS)’, which provides several services, by using newly developed algorithms for analysing Twitter messages. Twitter users often post messages about on-air TV programmes. ICS obtains viewer responses from tweets without requiring any new infrastructure or changes in users’ habits or behaviours, and it generates and provides several outputs to heterogeneous devices based on the analysis results. The algorithms—designed by considering the characteristics of Twitter messages about TV programmes—use auxiliary programme information, similarity between messages, and time series of messages. An evaluation of our algorithms using Twitter messages about all programme genres for a month showed that the accuracy of topic extraction was 85 % for an emphasis on quality (with 56 % of messages processed) and 65 % for an emphasis on quantity (with 95 % of messages processed). The accuracy of message sentimental classification was 66 %. We also describe social recommendation services using the analysis result. We have created a Social TV site for a large-scale field trial, and we have analysed users’ behaviours by comparing four types of social recommendation services on it. The experimental result shows that active and passive communication users had different needs with regard to the recommendations. ICS can generate recommendations for satisfying the needs of both user types by using the analysis result of Twitter messages.     

Speaking their Mind: Populist Style and Antagonistic Messaging in the Tweets of Donald Trump,Narendra Modi,Nigel Farage,and Geert Wilders

The authors in this study examined the function and public reception of critical tweeting in online campaigns of four nationalist populist politicians during major national election campaigns. Using a mix of qualitative coding and case study inductive methods, we analyzed the tweets of Narendra Modi, Nigel Farage, Donald Trump, and Geert Wilders before the 2014 Indian general elections, the 2016 UK Brexit referendum, the 2016 US presidential election, and the 2017 Dutch general election, respectively. Our data show that Trump is a consistent outlier in terms of using critical language on Twitter when compared to Wilders, Farage, and Modi, but that all four leaders show significant investment in various forms of antagonistic messaging including personal insults, sarcasm, and labeling, and that these are rewarded online by higher retweet rates. Building on the work of Murray Edelman and his notion of a political spectacle, we examined Twitter as a performative space for critical rhetoric within the frame of nationalist politics. We found that cultural and political differences among the four settings also impact how each politician employs these tactics. Our work proposes that studies of social media spaces need to bring normative questions into traditional notions of collaboration. As we show here, political actors may benefit from in-group coalescence around antagonistic messaging, which while serving as a call to arms for online collaboration for those ideologically aligned, may on a societal level lead to greater polarization.     

Some of these things are not like the others: Examining motivations and political predispositions among political Facebook activity

Political engagement via social media has evolved, and web sites including Facebook continue to be a place for individuals, especially young ones, to engage politically. Because politics on social media is diverse, it makes sense that the reasons for participating in it vary. In addition, because current events information and political news is accessible via social media, the role of attention to traditional news sources in this type of political engagement is debatable. The study takes up the opportunity to address these questions by examining young people’s attention to television, print, and online news, their engagement with four Facebook political activities, and their psychological motivations for using the website politically just prior to the 2012 U.S. Presidential election. The results suggest that the primary motivations for using Facebook politically are not universal, and indeed vary by activity. They revolve around connecting with others socially, sharing information with others, and presenting oneself to others. In addition, attention to offline and online news largely do not matter. The study moves research forward by describing the variety of psychological predispositions some Facebook users bring to their political engagement with the web site, and how these predispositions vary across different Facebook political behavior.     

How do live-streaming platforms facilitate persuasion in political campaigns? Theory and empirical evidence from the perspective of affordance actualization

Prior research is limited in how live-streaming platforms (LSPs) enable technological features facilitating political persuasion and engagement. Through the theoretical lens of affordance and theory of persuasion and mindfulness, this study (1) identifies persuasion-related affordances on LSPs that afford users with sufficient ability and motivation to process persuasive messages in live streaming, and (2) discovers how the actualization of such affordances fosters political mindfulness and promotes political engagement. We validate the research model using survey data collected from 16 live-streaming campaign rallies for the 2020 presidential election. This study makes significant theoretical contributions to live streaming and e-politics.