Populist linguistic tone in recent U.S. presidential campaign discourse: a DICTION analysis

ABSTRACT

This study analyzed the tone of public campaign remarks of right- and left-wing populist (Donald Trump and Bernie Sanders, respectively) and right and left-wing non-populist (Mitt Romney and Hillary Clinton, respectively) U.S. presidential candidates using DICTION 7.0. Findings suggest that populists tended to use a linguistic tone that is high in pessimism, group abstractness, and exclusion. Pessimism and group abstractness were positively associated with immigration language in right-wing populist speech. Commonality and “we-ness” were positively associated with populist language in left-wing populist speech.     

Where populist citizens get the news: An investigation of news audience polarization along populist attitudes in 11 countries

This article presents a secondary analysis of two multi-national cross-sectional surveys conducted in 2015 (11 countries, N?=?10,570) and 2017 (4 countries, N?=?2165) to examine the relationship between populist attitudes and media use. The results indicate that populist citizens are more likely to consume news than non-populist citizens. Specifically, populist citizens exhibit a preference for commercial television (TV) news, as well as a tendency to read tabloid newspapers. While they use fewer quality newspapers, public TV news are not systematically avoided. Regarding the online news environment, populist citizens prefer Facebook over Twitter as a source of political information. This selective pattern will be discussed in light of the debates on news audience polarization and political polarization.     

Engagement with news on Twitter: insights from Australia and Korea

ABSTRACT

This study examines the patterns of news engagement among news consumers with different political affiliation and cultural background. We use computational methods and data from Twitter in a cross-country comparison of engagement with six online news sources in Australia and South Korea. For our analysis, we used a subset of Twitter users who retweeted at least one political story during the period of collection, and for whom we were able to predict political affiliation using correspondence analysis and data on Twitter follower ties to politicians. We find that right-wing Australian retweeters are more intense in their news engagement, compared with their left-wing counterparts, whereas in South Korea it was the opposite. Australian right-wing political retweeters have more diverse information sources, while there was no difference in information diversity between the right and left in South Korea. We discuss how the political situation in South Korea at the time of data collection may have affected our analysis. We emphasise the methodological contributions of our research and its connection to on-going research into the behavioural foundations of ‘filter bubbles’.     

Right-Wing Pirate Radio Broadcasting in Israel: The Political Discourse About Channel 7, 1993–2003

This study examines an Israeli right-wing pirate radio station, Channel 7. Channel 7 was established in 1988 as a sea-based pirate radio station of the right-wing block in the religious-Zionist movement. Three questions were posed in the research: (a) What is the social representation of right-wing pirate radio station in the Knesset (Israeli parliament) discussions? (b) Did Yitzhak Rabin (Israeli Prime Minister) assassination influence the social representation of Channel 7 in the Knesset discussions? and (c) How does right-wing Knesset Members' social representation of Channel 7 differ from that of left-wing Knesset Members? An analysis of 115 parliamentary debates held in Israel between 1993 and 2003 referring to Channel 7 suggests the Knesset tended to affirm right-wing argumentation, Rabin's assassination strengthened right-wing as well as left-wing contentions, both right-wing and left-wing MKs tended to preserve the status quo and avoid changes, and right-wingers turned down left-wing demands for regulation.     

Reinforcing attitudes in a gatewatching news era: Individual-level antecedents to sharing fact-checks on social media

Despite the prevalence of fact-checking, little is known about who posts fact-checks online. Based upon a content analysis of Facebook and Twitter digital trace data and a linked online survey (N?=?783), this study reveals that sharing fact-checks in political conversations on social media is linked to age, ideology, and political behaviors. Moreover, an individual’s need for orientation (NFO) is an even stronger predictor of sharing a fact-check than ideological intensity or relevance, alone, and also influences the type of fact-check format (with or without a rating scale) that is shared. Finally, participants generally shared fact-checks to reinforce their existing attitudes. Consequently, concerns over the effects of fact-checking should move beyond a limited-effects approach (e.g., changing attitudes) to also include reinforcing accurate beliefs.     

The Appeal of Media Populism: The Media Preferences of Citizens with Populist Attitudes

Although a growing body of literature points to the particular media diet of populist voters, we know too little about what specific media preferences characterize citizens with populist attitudes. This article investigates to what extent citizens with antiestablishment and exclusionist populist attitudes are attracted to attitudinal-congruent media content. We collected survey data using a nationally representative sample (N = 809) and found that citizens’ preferences for media content are in sync with their populist attitudes. Beyond having a tabloidized and entertainment-based media diet, populist voters self-select media content that actively articulates the divide between the “innocent” people and “culprit” others. These findings provide new insights into the appeal of different types of media populism among citizens with populist attitudes on different dimensions.     

Examining government cross-platform engagement in social media: Instagram vs Twitter and the big lift project

As governments are increasingly turning to social media as a means of engaging the public, questions remain as to how they are actually using various social media platforms. Do specific platforms engender specific types of messages? If so, what are they, and how do they affect civic engagement, co-participation, and address citizen concerns? In this paper, we compare the use of Instagram and Twitter by ‘The Big Lift’, a bridge re-decking project completed by Halifax Harbour Bridges. Based on a content analysis of Instagram (n = 248) and Twitter (n = 1278) public posts, we found that Instagram was used as a more ‘informal’ narrative platform that promoted a clicktivist type of responses from the audience, whereas Twitter was a more ‘formal’ news platform that supported greater two-way communication between the organization and the audience. We conclude that by building and maintaining their active presence and following base on social media, and especially on Twitter, organizations can develop a capacity to address social concerns during disruptive events or infrastructure projects like ‘The Big Lift’.     

The Effects of Darkness and Lightness Cues in the Visual Depiction of Political Actors Involved in Scandals: An Experimental Study

Reports about political scandals have increased lately. Yet the general impact of news visuals and the specific role of lightness and darkness cues in images of scandalized politicians remain unclear. With the help of an experiment, the present pilot study examined the influence of candidate images and the effects of particular image backgrounds (light versus dark). While the foreground of the image depicting a politician involved in a scandal remained unchanged, the background was systematically altered. The results revealed that a light background had a positive effect on recipients’ attitudes toward the politician. In contrast, participants exposed to a dark image background demanded a more severe punishment for the politician.     

The use of twitter by mayors in Turkey: Tweets for better public services?

This article aims to provide an overall picture of the use of Twitter as a significant social media tool by mayors in Turkey and to investigate, using content analysis and tweet categorization, whether Twitter is used by mayors in Turkey to offer better public services. Thus, this study focuses on the impact of Twitter in Turkey on transparent, participatory and citizen-oriented local public services. Our analysis has revealed that mayors in Turkey use Twitter especially to share information, send personal messages and share their location and activities. The use of Twitter for transparent, participatory and citizen-oriented public service delivery is not common among mayors. Twitter is adopted and used by mayors mostly for the purposes of self-promotion and political marketing in Turkey.     

Predicting elections from social media: a three-country,three-method comparative study

ABSTRACT

This study introduces and evaluates the robustness of different volumetric, sentiment, and social network approaches to predict the elections in three Asian countries – Malaysia, India, and Pakistan from Twitter posts. We find that predictive power of social media performs well for India and Pakistan but is not effective for Malaysia. Overall, we find that it is useful to consider the recency of Twitter posts while using it to predict a real outcome, such as an election result. Sentiment information mined using machine learning models was the most accurate predictor of election outcomes. Social network information is stable despite sudden surges in political discussions, for e.g. around elections-related news events. Methods combining sentiment and volume information, or sentiment and social network information, are effective at predicting smaller vote shares, for e.g. vote shares in the case of independent candidates and regional parties. We conclude with a detailed discussion on the caveats of social media analysis for predicting real-world outcomes and recommendations for future work.     

Generating and Framing Content: Strategic Multi-Platform Content Marketing in Academic Libraries

This column is adapted from a presentation given at the 2018 Library Marketing and Communications Conference. In it, we describe our marketing team’s approach to developing sustainable marketing practices with our library’s strategic goals in mind. In an effort to create reusable, platform-flexible content, we developed social media posts that highlighted concepts from the ACRL Framework for Information Literacy. Our success on social media inspired us to consider how this content could be implemented on additional platforms. With this column, we invite you to engage with new ways of developing content for use on multiple marketing platforms.     

Susceptibility to Deception in a Political News Interview: Effects of Identification,Perceived Cooperativeness,and Ingroup Vulnerability

This article explores people’s susceptibility to political deception. Participants watched a news interview in which a politician either answered all the questions or deceptively evaded a question. In Study 1 (n = 202), deception is perceived through the dodge being irrelevant for voters who do not identify with the politician. In Study 2 (n = 618), partisan voters consider the politician more deceptive, and acting more deceptively, when the politician has their opposing party affiliation, independent of whether he dodges. When the politician shares their party identification, voters identify with the politician more and consider his responses more relevant. Findings are consistent with theoretical positions of identification, the cooperative principle, and social identity.     

How Age Affects Journalists’ Adoption of Social Media as an Innovation

American newsrooms are adopting social media as an innovation for greater engagement. However, several organizational and individual factors may affect the extent to which news outlets adopt social media innovations. In particular, there is assumed to be a divide among different age groups of journalists in embracing social media. Utilizing a structural equation modeling (SEM) analysis, the study seeks to understand how social media culture in newsrooms affects journalists’ strategies of taking social media as an innovation, and how journalists of different age groups differ in the SEM model fit. The analyses indicated Twitter engagement mediates social media culture and journalists’ attitude toward social media. However, that was not the case with Facebook. Additionally, while younger journalists favored Twitter, older journalists embraced Facebook and middle-aged journalists adopted both Facebook and Twitter. The analyses showed the more that middle-aged journalists interacted on Twitter, the more they tended to have a positive attitude toward social media. However, the more that younger and older journalists engaged on Twitter, the more they tended to have a negative attitude toward social media. Journalists from all three age groups tended to hold a negative attitude toward social media if they engaged more on Facebook.     

Using word embeddings in Twitter election classification

Word embeddings and convolutional neural networks (CNN) have attracted extensive attention in various classification tasks for Twitter, e.g. sentiment classification. However, the effect of the configuration used to generate the word embeddings on the classification performance has not been studied in the existing literature. In this paper, using a Twitter election classification task that aims to detect election-related tweets, we investigate the impact of the background dataset used to train the embedding models, as well as the parameters of the word embedding training process, namely the context window size, the dimensionality and the number of negative samples, on the attained classification performance. By comparing the classification results of word embedding models that have been trained using different background corpora (e.g. Wikipedia articles and Twitter microposts), we show that the background data should align with the Twitter classification dataset both in data type and time period to achieve significantly better performance compared to baselines such as SVM with TF-IDF. Moreover, by evaluating the results of word embedding models trained using various context window sizes and dimensionalities, we find that large context window and dimension sizes are preferable to improve the performance. However, the number of negative samples parameter does not significantly affect the performance of the CNN classifiers. Our experimental results also show that choosing the correct word embedding model for use with CNN leads to statistically significant improvements over various baselines such as random, SVM with TF-IDF and SVM with word embeddings. Finally, for out-of-vocabulary (OOV) words that are not available in the learned word embedding models, we show that a simple OOV strategy to randomly initialise the OOV words without any prior knowledge is sufficient to attain a good classification performance among the current OOV strategies (e.g. a random initialisation using statistics of the pre-trained word embedding models).     

State of the library and information science blogosphere after social networks boom: A metric approach

A metric analysis of blogs on library and information science (LIS) between November 2006 and June 2009 indexed on the Libworm search engine characterizes the community's behavior quantitatively. An analysis of 1108 personal and corporate blogs with a total of 275,103 posts is used to calculate survival rate, production (number of posts published), and visibility via such indicators as links received, Technorati authority, and Google's PagePank. Over the study period, there was a 52% decrease in the number of active blogs. Despite the drop in production over this period, the average number of posts per blog remained constant (14 per month). The most representative blogs in the discipline are identified. The emergence of such platforms as Facebook and Twitter seems to have meant that both personal and corporate blogs have lost some of their prominence.     

Are You Talking to Me?

Social media has become a key medium for discussion and dissemination of news stories, fuelled by the low barrier to entry and the ease of interaction. News stories may be propagated through these networks either by official news organisation accounts, by individual journalists or by members of the public, through link sharing, endorsing or commenting. This preliminary research aims to show how computational analysis of large-scale data-sets allows us to investigate the means by which news stories are spread through social media, and how the conversation around them is shaped by journalists and news organisations. Through the capture of more than 11 million tweets relating to 2303 Twitter accounts connected to journalism and news organisations, we are able to analyse the conversation within and around journalism, examining who spreads information about news articles and who interacts in the discussion around them. Capturing the tweets of news organisations and journalists and the replies and retweets of these micro-blogs allows us to build a rich picture of interaction around news media.     

AMERICAN SPORTS WRITERS’ SOCIAL MEDIA USE AND ITS INFLUENCE ON PROFESSIONALISM

American sports writers' use of social media as a newsgathering tool has influenced journalism practice, further complicating the industry's abstract definition of “professionalism.” This study builds on a pilot study published in the fall 2011 issue of Journal of Sports Media, which assessed print sports journalists' use of social media. In the current study, a survey was administered to 77 full-time print sports journalists who cover professional sports. This paper seeks to extend the pilot study and previous professional research in two ways: firstly, to assess how this specific subgroup of sports writers use Facebook and Twitter to gather information; and secondly, to analyze how these sports writers define “professionalism” and what industry factors correlate with chosen definitions, such as newspaper circulation and work superiors' attitudes toward social media. Cross-tabulations and chi-square tests were used to test hypotheses. Cramer's V or Phi, depending upon the cross-tabulation, were used to measure relationship strength. Results suggest this subset of sports writers more often uses Twitter for newsgathering purposing than Facebook. There is also a strong relationship between the frequency of Twitter usage and the definition of professionalism chosen; circulation size and instances of directly quoting from athletes' social media accounts; and age and Twitter usage.     

Collective Trolling as a Form of Organizational Resistance: Analysis of the #Justiceforbradswife Twitter Campaign

This case study analyzed Twitter posts from the #JusticeForBradsWife campaign against the Cracker Barrel (CB) restaurant chain. Participants in the counterinstitutional movement employed diverse message strategies of humor and resistance in using social media as a site for discourse. Thematic analysis of the most influential users revealed humor strategies including: connecting to popular culture, political comic relief and using hyperbole. Participants’ resistance strategies included: making calls for action, critiquing CB products and business partners, attacking CB patrons, critiquing CB’s social media management, and offers of support from outside organizations. These strategies reflected collective trolling, where trolling behaviors created a hidden and public hybrid form of collective resistance from nontraditional stakeholders who had contradictory goals. Implications and directions for future research are discussed.     

The dream of statehood and the reality of conflict: local and international coverage of the Palestinian United Nations bid for statehood

This paper examines whether or not media coverage is biased by the political orientation of the journalists’ country, specifically illustrated by the 2011 bid for statehood by the Palestinian Authority in the United Nations. This bid represents a symbolic step toward international recognition of a Palestinian state, an important event in the Israeli-Palestinian conflict. A quantitative analysis was conducted on 1577 news reports from American, European, and Middle Eastern outlets to determine the differences in media coverage of the Palestinian bid for statehood among the channels. The findings suggest that Israeli channels broadcasted a relatively low number of items in which the Palestinian declaration itself was the main theme. The BBC broadcasted a relatively high rate of such items, and offered balanced coverage of both Israeli and Palestinian positions, while coverage by American FOX News channel reflected a pro-Israel bias. The findings also suggest that media outlets may be biased toward specific leaders. This work builds on a growing body of research on media framing of political conflicts and the effect of the political context of a country on its media outlets’ coverage.     

Citizen reactions to municipalities’ Instagram communication

In this paper, we explore how local governments are using Instagram as a communication tool to engage with their citizens, using data from the municipalities of Andalusia (Spain). We seek to identify the determinants of local government use of Instagram, the determinants of activity in this channel and the determinants of citizen reactions in order to understand the influence of media types (picture, video or album) used in municipality posts, and to understand content type (what the post is about). Instaloader, an open source intelligence (OSINT) tool for Instagram, was applied. It made it possible to automatically extract all posts of the analysed municipalities (14,742 posts). These were later automatically analysed using R, an open source software. It was determined that of the 29 Andalusian local governments with the highest populations, only those that maintain an account on Instagram, totalling 17 municipalities (58.62%), would be part of the final analysis. Our findings demonstrate that when local governments have a high level of debt, they do not maintain and actively use Instagram accounts. We also found that quality of posts’ content is more important than quantity of followers, since there is no significant relationship between citizen reactions and the number of inhabitants of a municipality or the number of followers (audience), while there is a significant negative relationship between the number of posts (activity) and reactions. Our results also highlight that the level of reactions can be stimulated by certain media and content types.