Article

Twitter made me do it! Twitter's tonal platform incentive and its effect on online campaigning

Taylor & Francis
Information, Communication & Society
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Abstract

Does Twitter trigger negative tones in politicians' digital communication? On social media direct feedback mechanisms such as retweets or likes signal to politicians which message and tone are popular. Current research suggests that negative language increases the number of retweets a single tweet receives, indicating preferences for negativity in the audience on Twitter. However, it remains unclear whether politicians adapt to the logic of Twitter or simply follow the rules determined by the broader political context, namely the state of their electoral race. We use sentiment analysis to measure the tone used by 342 candidates in 97,909 tweets in their Twitter campaign in the 2018 midterm elections for the US House of Representatives and map the ideological composition of each politician's Twitter network. We show that the feedback candidates receive creates an incentive to use negativity. The size and direction of the tonal incentive is connected to the ideological composition of the candidate's follower network. Unexpectedly, the platform-specific incentive does not affect the tone used by candidates in their Twitter campaigns. Instead we find that the tone is mainly related to characteristics of the electoral race. We show that our findings are not dependent on our sentiment measurement by validating our results using hand coding and machine learning.

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... Towing to the variety of applications and research contexts, CTAM have become an increasingly important tool for studying communication (see Figure 1). For example, previous research utilized CTAM to study integrative complexity of online discussions (Dobbrick et al., 2021), media coverage and news frames (Baden & Tenenboim-Weinblatt, 2017;Eisele et al., 2023), or communication styles of political actors (Mueller & Saeltzer, 2020;Rudkowsky et al., 2018;Stier et al., 2018). ...
... Thus, by rerunning empirical analyses across different settings, consistent findings can provide important evidence that CTAM are robust against various issues. In our review, we observed several robustness checks, such as for how to aggregate scores from lower to higher level (e.g., from sentence to paragraph or document to corpus level) (Boukes et al., 2019), transforming numeric to categorical measures (Baden et al., 2020;Mueller & Saeltzer, 2020), selecting different number of topics in a topic model (Van Der Velden et al., 2018;Yarchi et al., 2021), or choosing a different text-based method (Mueller & Saeltzer, 2020). 10 To foster reproducibility, we advocate for adhering to open science standards, such as publishing all materials including data, code, and nonrestrictive computational environments (e.g. a dockerfile), preregistering studies and submitting registered reports, as well as conducting replication studies to verify computational reproducibility (Dienlin et al., 2021, Schoch et al., 2023. ...
... Thus, by rerunning empirical analyses across different settings, consistent findings can provide important evidence that CTAM are robust against various issues. In our review, we observed several robustness checks, such as for how to aggregate scores from lower to higher level (e.g., from sentence to paragraph or document to corpus level) (Boukes et al., 2019), transforming numeric to categorical measures (Baden et al., 2020;Mueller & Saeltzer, 2020), selecting different number of topics in a topic model (Van Der Velden et al., 2018;Yarchi et al., 2021), or choosing a different text-based method (Mueller & Saeltzer, 2020). 10 To foster reproducibility, we advocate for adhering to open science standards, such as publishing all materials including data, code, and nonrestrictive computational environments (e.g. a dockerfile), preregistering studies and submitting registered reports, as well as conducting replication studies to verify computational reproducibility (Dienlin et al., 2021, Schoch et al., 2023. ...
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... Even though robustness checks do not directly provide evidence that the method applied is able to measure the construct of interest, they still provided relevant accompanying information for the stability of CTAM measures and, thus, evidence for measurement validity, nonetheless. For instance, by rerunning empirical analyses across different settings, stable and consistent findings provided important evidence that the method selected was robust against issues such as aggregating scores (e.g., from sentence to paragraph or document level or across time intervals) (Boukes et al., 2019), transforming numeric to categorical measures (Baden et al., 2020;Mueller & Saeltzer, 2020), or selecting different number of topics in a topic model (Van Der Velden et al., 2018;Yarchi et al., 2021). ...
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... Hansson, 2018). Furthermore, transferring hostility over issues from parliament to an online arena can be beneficial, as negative social media posts by politicians tend to attract the most attention online (Mueller & Saeltzer, 2022;Peeters et al., 2023). Therefore, such possibilities may result in journalists picking up on the story due to the negativity bias (Soroka, 2012), and ultimately disseminating parliamentary issues debated online to the general public. ...
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... Such negative and uncivil communication between politicians can have a profound impact on society. On the one hand, negativity can positively affect the public by increasing their political attention (Mueller and Saeltzer 2022;Mutz 2015;Soroka 2014) and satisfaction with democracy (Ridge 2022;Tuttnauer 2022;Van Elsas and Fiselier 2023). On the other hand, it can also yield adverse consequences, such as lower voter turnout (Nai 2013), heightened public anger (Gervais 2017;Walter and Ridout 2021), increased resentment toward politics (Van't Riet & Van Stekelenburg 2022), and the amplification of affective polarization (Druckman et al. 2019;Iyengar et al. 2012;Skytte 2022). ...
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... Types d'attaques (%) par communautéLes tendances mises en avant dans les analyses ci-dessous sont similaires aux tendances observées dans d'autres pays : les attaques, leur type et leur nombre, varient entre acteurs politiques en fonction de leur orientation idéologique, de leur place dans le paysage partisan (parti traditionnel ou « challenger ») et de leur statut (gouvernement ou opposition). Si cette forme de communication n'est pas née avec les réseaux sociaux, Twitter est cependant connu pour être une plateforme particulièrement propice à la prolifération de messages négatifs(Mueller and Saeltzer 2022). ...
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... Moreover, the results provide evidence that when posts are integrated in news articles, political discourse among politicians is represented in a substantially more negative tone. Studies examining the use and spread of negative utterances on X show that posts including attacks or negative emotions spread further as they create more likes and shares than positive posts (Mueller and Saeltzer, 2022;Rozado et al., 2022;Schöne et al., 2021). The negativity on X apparently spills over to news coverage. ...
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... At the same time, since users leave digital traces, they provide advertisers with data that can be exploited for further planning of the ad campaign (Brodnax & Sapiezynski, 2020). Feedback mechanisms such as retweets and likes deliver campaigners information about the popularity of their posts and can, for example, be an incentive for the use of negativity (Mueller & Saeltzer, 2020). ...
Chapter
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... Given the more permissive and adaptable nature of social media compared to legislative speeches, it is plausible to speculate that they provide fertile ground for enhancing rhetorical responsiveness. With social media assuming a pivotal role as a channel for representatives to showcase and deliberate their endeavours (Mueller and Saeltzer, 2022;Saeltzer, 2022), forthcoming research should focus on scrutinizing legislative rhetorical responsiveness as manifested across diverse social media platforms. ...
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... Misleading content that pursues political goals tends to focus on the statements of leaders, especially on Twitter, delving into the personalization of politics that characterizes the current journalism (Carlson, 2018). This fosters a distortion of the value of facts for democracy, which are less relevant in journalistic reporting compared with self-interested quotes (Müller & Sältzer, 2020). These practices are a breeding ground for disinformation (Conroy et al., 2015), undermining political knowledge and, therefore, elections, the prestige of democratic institutions (Lee & Xenos, 2019). ...
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... Fraudulent accounts on the Internet is a common issue across different domains because Twitter, one of the most used platforms in the world, is a popular target for criminals to create fake account or news [12][13][14][15]. Previous studies have been conducted on the problems that are associated with Twitter; the ones that are associated with fake news, fake accounts/users, and fraudulent issues are particularly important to this study. ...
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... This approach uses Markov chain Monte Carlo methods to estimate beliefs on a Left-Right dimension based on the partisan political elites a user follows. Since it can be conceptualized as a measure of political ideology (Francis Havey, 2020;Liang, 2018;Mueller and Saeltzer, 2020), we will henceforth use that terminology to describe it. Tweetscores has been validated against campaign contributions and voting records and provides reliable and consistent estimates when sufficient network data is available (Barberá, 2015). ...
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... Regarding sentiment and persuasion, our findings join work that considers the target of sentiment, particularly in an era of political microtargeting (e.g., Park et al., 2021). Specifically, we show that not all negativity has "news value" worth sharing (Mueller & Saeltzer, 2020). In our case of IRA operations, while tweets with negative sentiment toward Clinton were associated with more retweets, those with positive sentiment towards Trump also garnered more retweets compared to neutral ones, corresponding to IRA's goal to amplify pro-Trump rhetoric. ...
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... En esta línea, Calvo y Aruguete (2020: 60-70) consideran que la polarización afectiva en las redes constituye «una defensa encendida de creencias propias ante los objetivos comunicacionales del otro» y afirman que «odiar las redes es un acto afectivo, cognitivo y político». Estudios recientes (Mueller & Saeltzer, 2020) también se refieren a este contagio en las redes originado por los mensajes que evocan emociones negativas y apuntan a que la comunicación afectiva negativa surge de manera voluntaria como resultado de campañas estratégicas (Martini et al., 2021). En este contexto, la «incivility» surge como una estrategia comunicativa que, gracias a la generación de emociones negativas mediante el insulto o el desprestigio social, trata de excluir al adversario del debate público (Papacharissi, 2004). ...
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... This is only because, on social media immediate response systems such as retweets or likes indicate to politicians which messages are in trend which make them politician to run their SNS political campaign according to the trends. Research indicates that negative dialect rises the number of retweets of a particular tweet obtains, showing likings for negativity among the Twitter audience (Mueller, Saeltzer, 2020). Thus Social media can open channels for political expression, engagement, and participation for both candidates and voters simultaneously (Tucker et al. 2017). ...
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Chapter
During the COVID-19 pandemic, news stations have used social media platforms such as Twitter to deliver information to the general public. To understand the trends as well as impact of these posts, we analyze 500 k tweets and responses across 15 news outlets from USA, Canada, and UK, through three research questions. The first question is related to topic popularity where a zero-shot classification algorithm is used to determine what type of COVID-19 related tweets users are mostly interacting with. Then, the second question looks to determine how the audiences differ in their responses between news stations within each country by using a sentiment, emotion, and stance analysis algorithm as well as statistical hypothesis test. Lastly, the third question uses the previous analyzes’ results along with the political leanings of each news station to see if there is a correlation in differences. As a result, we discover that the topic of vaccine is the most popular, audiences in the USA and UK have a considerable amount of differences in their responses, and that the differences in political leanings strongly match with differences in audience response.
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This chapter examines the empirical patterns of the politics of legislative debates in thirty-three liberal democracies. There are three take-home messages in this chapter. First, twenty out of the thirty-three legislatures analyzed experience some sort of gender imbalance. Even controlling for potential confounders such as seniority, position in the legislative party, and committee chairs, empirical evidence suggests that women tend to have less access to the floor than men. Second, we find that seniority plays a role in determining floor access. More senior legislators tend to speak more often. Third, against our expectations, comparative results suggest that roughly half of the countries analyzed in this volume do not privilege party leaders in floor access. In addition to discussing comparative empirical patterns, the chapter discusses the road ahead in research on legislative debates.
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Legislative debates are a thriving field in comparative politics. They make representation work by offering legislators the opportunity to take the floor and represent their constituents. In this paper, we review the key theoretical concepts and empirical findings in a maturing field. We begin by addressing what legislative debates are and why we should study them to learn about inter‐ and intra‐party politics. Next, we look at the contributions springing from Proksch and Slapin's groundbreaking model. In so doing, our review suggests that recent work extends the original model to include further dimensions of legislative debates. Third, we examine the role of legislative debates as mechanisms of representation, focusing on gender. Four, we examine the challenges of the comparative analysis of legislative debates. Finally, we map the road ahead by discussing four avenues of future research and some key questions that remain unanswered. This article is protected by copyright. All rights reserved
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A re legislators responsive to the priorities of the public? Research demonstrates a strong correspondence between the issues about which the public cares and the issues addressed by politicians, but conclusive evidence about who leads whom in setting the political agenda has yet to be uncovered. We answer this question with fine-grained temporal analyses of Twitter messages by legislators and the public during the 113th US Congress. After employing an unsupervised method that classifies tweets sent by legislators and citizens into topics, we use vector autoregression models to explore whose priorities more strongly predict the relationship between citizens and politicians. We find that legislators are more likely to follow, than to lead, discussion of public issues, results that hold even after controlling for the agenda-setting effects of the media. We also find, however, that legislators are more likely to be responsive to their supporters than to the general public.
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quanteda is an R package providing a comprehensive workflow and toolkit for natural language processing tasks such as corpus management, tokenization, analysis, and visualization. It has extensive functions for applying dictionary analysis, exploring texts using keywords-in-context, computing document and feature similarities, and discovering multi-word expressions through collocation scoring. Based entirely on sparse operations, it provides highly efficient methods for compiling document-feature matrices and for manipulating these or using them in further quantitative analysis. Using C++ and multithreading extensively, quanteda is also considerably faster and more efficient than other R and Python ackages in processing large textual data. The package is designed for R users needing to apply natural language processing to texts, from documents to final analysis. Its capabilities match or exceed those provided in many end-user software applications, many of which are expensive and not open source. The package is therefore of great benefit to researchers, students, and other analysts with fewer financial resources. While using quanteda requires R programming knowledge, its API is designed to enable powerful, efficient analysis with a minimum of steps. By emphasizing consistent design, furthermore, quanteda lowers the barriers to learning and using NLP and quantitative text analysis even for proficient R programmers.
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Although considerable research has concentrated on online campaigning, it is still unclear how politicians use different social media platforms in political communication. Focusing on the German federal election campaign 2013, this article investigates whether election candidates address the topics most important to the mass audience and to which extent their communication is shaped by the characteristics of Facebook and Twitter. Based on open-ended responses from a representative survey conducted during the election campaign, we train a human-interpretable Bayesian language model to identify political topics. Applying the model to social media messages of candidates and their direct audiences, we find that both prioritize different topics than the mass audience. The analysis also shows that politicians use Facebook and Twitter for different purposes. We relate the various findings to the mediation of political communication on social media induced by the particular characteristics of audiences and sociotechnical environments.
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This essay explores the changing character of public discourse in the Age of Twitter. Adopting the perspective of media ecology, the essay highlights how Twitter privileges discourse that is simple, impulsive, and uncivil. This effect is demonstrated through a case study of Donald J. Trump's Twitter feed. The essay concludes with a brief reflection on the end times: a post-truth, post-news, President Trump, Twitter-world.
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In this article, we examine the relationship between metrics documenting politics-related Twitter activity with election results and trends in opinion polls. Various studies have proposed the possibility of inferring public opinion based on digital trace data collected on Twitter and even the possibility to predict election results based on aggregates of mentions of political actors. Yet, a systematic attempt at a validation of Twitter as an indicator for political support is lacking. In this article, building on social science methodology, we test the validity of the relationship between various Twitter-based metrics of public attention toward politics with election results and opinion polls. All indicators tested in this article suggest caution in the attempt to infer public opinion or predict election results based on Twitter messages. In all tested metrics, indicators based on Twitter mentions of political parties differed strongly from parties’ results in elections or opinion polls. This leads us to question the power of Twitter to infer levels of political support of political actors. Instead, Twitter appears to promise insights into temporal dynamics of public attention toward politics.
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J/47Te address the effects of negative campaign advertising on turnout. Using a unique jfjJ \ experimental design in which advertising tone is manipulated within the identical X V t audiovisual context, we find that exposure to negative advertisements dropped intentions to vote by 5%. We then replicate this result through an aggregate-level analysis of turnout and campaign tone in the 1992 Senate elections. Finally, we show that the demobilizing effects of negative campaigns are accompanied by a weakened sense of political efficacy. Voters who watch negative advertisements become more cynical about the responsiveness of public officials and the electoral process. It is generally taken for granted that political campaigns boost citizens' involvement-their in- terest in the election, awareness of and informa- tion about current issues, and sense that individual opinions matter. Since Lazarsfeld's pioneering work (Berelson, Lazarsfeld, and McPhee 1954; Lazarsfeld, Berelson, and Gaudet 1948), it has been thought that campaign activity in connection with recurring elec- tions enables parties and candidates to mobilize their likely constituents and "recharge" their partisan sen- timents. Voter turnout is thus considered to increase directly with "the level of political stimulation to which the electorate is subjected" (Campbell et al. 1966, 42; Patterson and Caldeira 1983). The argument that campaigns are inherently "stim- ulating" experiences can be questioned on a variety of grounds. American campaigns have changed dra-
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The greater power of bad events over good ones is found in everyday events, major life events (e.g., trauma), close relationship outcomes, social network patterns, interpersonal interactions, and learning processes. Bad emotions, bad parents, and bad feedback have more impact than good ones, and bad information is processed more thoroughly than good. The self is more motivated to avoid bad self-definitions than to pursue good ones. Bad impressions and bad stereotypes are quicker to form and more resistant to disconfirmation than good ones. Various explanations such as diagnosticity and salience help explain some findings, but the greater power of bad events is still found when such variables are controlled. Hardly any exceptions (indicating greater power of good) can be found. Taken together, these findings suggest that bad is stronger than good, as a general principle across a broad range of psychological phenomena.
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This article explores a selection of the tweets of President Donald Trump, specifically in relation to his use of negativity as a rhetorical political strategy. The study is guided by a corpus-based comparative keyword analysis and the analytical framework of APPRAISAL, from Systemic Functional Linguistics, which is concerned with the language of evaluation. The study reveals that in order to carry out an approach of 'going negative', Trump utilises the APPRAISAL system in a variety of ways, with the ultimate aim to attack and undermine the character of his political opponent.
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We examine the interaction between partisan affect and elite polarization in a behavioral voting model. Voting is determined by affect rather than rational choice. Parties are office-motivated; they choose policies to win elections. We show that parties bias their policies toward their partisans if voters exhibit ingroup responsiveness, i.e., they respond more strongly to their own party’s policy deviations than to policy deviations by the other party. Our results suggest that affective polarization is a driver of the growing elite polarization in American politics. Importantly, this observation does not assume any shifts in the voters’ bliss points and is therefore orthogonal to the controversy over whether the American electorate has become more polarized in ideology.
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This study inductively develops a new conceptual framework for analyzing strategic campaign communications across different social media platforms through an analysis of candidate social media strategies during the 2016 U.S. presidential election cycle. We conducted a series of open-ended, in-depth qualitative interviews with campaign professionals active during the 2016 presidential cycle. Our analysis revealed that scholars need to account for the ways that campaigns perceive their candidates in addition to the audiences, affordances, and genres of different social media platforms, as well as the timing of the electoral cycle, in order to effectively study strategic social media communication. Our findings reveal that campaigns proceed from perceptions of their candidates’ public personae and comfort with engagement on social media. Campaigns perceive that social media platforms vary according to their audiences, including their demographics and other characteristics; with respect to their affordances, actual and perceived functionalities; the genres of communication perceived to be appropriate to them; and the timing of the electoral cycle, which shapes messaging strategies and the utility of particular platforms. These factors shape how campaigns use social media in the service of their electoral goals. We conclude by developing these findings into an analytic framework for future research, arguing that researchers should refrain from automatically generalizing the results of single-platform studies to “social media” as a whole, and detailing the implications of our findings for future political communication research.
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Humans evolved to attend to valence and group membership when learning about their environment. The political domain offers a unique opportunity to study the simultaneous influence of these two broad, domain-general features of human experience. We examined whether the pervasive tendency for negatively valenced frames to “stick” in the mind applies to both intergroup and intragroup political contexts. In a preregistered experiment, we tested the effects of negative-to-positive (vs. positive-to-negative) reframing on people’s candidate preferences, first in the absence of party cue information and then in two partisan contexts: an intergroup context (analogous to a U.S. general election between opposing political parties) and an intragroup context (analogous to a U.S. primary election between candidates of the same party). We observed a persistent negativity bias in reframing effects, even in the presence of party cues. The results pave the way for future research at the intersection of psychology and political science.
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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.
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What drives candidates to “go negative” and against which opponents? Using a unique dataset consisting of all inter-candidate tweets by the 17 Republican presidential candidates in the 2016 primaries, we assess predictors of negative affect online. Twitter is a free platform, and candidates therefore face no resource limitations when using it; this makes Twitter a wellspring of information about campaign messaging, given a level playing-field. Moreover, Twitter’s 140-character limit acts as a liberating constraint, leading candidates to issue sound bites ready for potential distribution not only online, but also through conventional media, as tweets become news. We find tweet negativity and overall rate of tweeting increases as the campaign season progresses. Unsurprisingly, the front-runner and eventual nominee, Donald Trump, sends and receives the most negative tweets and is more likely than his opponents to strike out against even those opponents who are polling poorly. However, candidates overwhelmingly “punch upwards” against those ahead of them in the polls, and this pattern goes beyond attacks against those near the top. Sixty of 136 dyads are characterized by lopsided negativity in one direction and only one of these 60 involves a clearly higher status candidate on the offensive.
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Twitter has become a pervasive tool in election campaigns. Candidates, parties, journalists, and a steadily increasing share of the public are using Twitter to comment on, interact around, and research public reactions to politics. These uses have met with growing scholarly attention. As of now, this research is fragmented, lacks a common body of evidence, and shared approaches to data collection and selection. This article presents the results of a systematic literature review of 127 studies addressing the use of Twitter in election campaigns. In this systematic review, I will discuss the available research with regard to findings on the use of Twitter by parties, candidates, and publics during election campaigns and during mediated campaign events. Also, I will address prominent research designs and approaches to data collection and selection.
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One of the most important developments affecting electoral competition in the United States has been the increasingly partisan behavior of the American electorate. Yet more voters than ever claim to be independents. We argue that the explanation for these seemingly contradictory trends is the rise of negative partisanship. Using data from the American National Election Studies, we show that as partisan identities have become more closely aligned with social, cultural and ideological divisions in American society, party supporters including leaning independents have developed increasingly negative feelings about the opposing party and its candidates. This has led to dramatic increases in party loyalty and straight-ticket voting, a steep decline in the advantage of incumbency and growing consistency between the results of presidential elections and the results of House, Senate and even state legislative elections. The rise of negative partisanship has had profound consequences for electoral competition, democratic representation and governance.
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We estimated ideological preferences of 3.8 million Twitter users and, using a data set of nearly 150 million tweets concerning 12 political and nonpolitical issues, explored whether online communication resembles an "echo chamber" (as a result of selective exposure and ideological segregation) or a "national conversation." We observed that information was exchanged primarily among individuals with similar ideological preferences in the case of political issues (e.g., 2012 presidential election, 2013 government shutdown) but not many other current events (e.g., 2013 Boston Marathon bombing, 2014 Super Bowl). Discussion of the Newtown shootings in 2012 reflected a dynamic process, beginning as a national conversation before transforming into a polarized exchange. With respect to both political and nonpolitical issues, liberals were more likely than conservatives to engage in cross-ideological dissemination; this is an important asymmetry with respect to the structure of communication that is consistent with psychological theory and research bearing on ideological differences in epistemic, existential, and relational motivation. Overall, we conclude that previous work may have overestimated the degree of ideological segregation in social-media usage. © The Author(s) 2015.
Book
This book offers a framework for the analysis of political communication in election campaigns based on digital trace data that documents political behavior, interests and opinions. The author investigates the data-generating processes leading users to interact with digital services in politically relevant contexts. These interactions produce digital traces, which in turn can be analyzed to draw inferences on political events or the phenomena that give rise to them. Various factors mediate the image of political reality emerging from digital trace data, such as the users of digital services’ political interests, attitudes or attention to politics. In order to arrive at valid inferences about the political reality on the basis of digital trace data, these mediating factors have to be accounted for. The author presents this interpretative framework in a detailed analysis of Twitter messages referring to politics in the context of the 2009 federal elections in Germany. This book will appeal to scholars interested in the field of political communication, as well as practitioners active in the political arena.
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We investigate the amount of negative campaigning in the 1998 senatorial primaries and the ramifications of negative campaigning on primary turnout and general election outcomes. A large literature has developed to show whether primary divisiveness has significant consequences for electoral outcomes, though we do not have much knowledge about what primary divisiveness entails (Bernstein 1977: 540). We employ a holistic measure of campaign negativity measured by coding newspaper articles three months prior to the primary to uncover how much negativity exists in senatorial primaries, which campaigns turn negative, and the relationship between primary negativity and several campaign factors. We find that primary divisiveness is strongly related to campaign negativity, negativity boosts primary turnout, while divisiveness depletes a nominee's general election fortunes.
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Does negative campaigning influence the likelihood of voting in elections? Our study of U.S. Senate campaigns indicates the answer is "yes." We find that people distinguish between useful negative information presented in an appropriate manner and irrelevant and harsh mudslinging. As the proportion of legitimate criticisms increases in campaigns, citizens become more likely to cast ballots. When campaigns degenerate into unsubstantiated and shrill attacks, voters tend to stay home. Finally, we find that individuals vary in their sensitivity to the tenor of campaigns. In particular, the tone is more consequential for independents, for those with less interest in politics, and for those with less knowledge about politics.
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Research into social media and social networking sites has focused on its advantages for organization–public relationships. Potential risks to corporate reputation have been largely glossed over, but inappropriate strategies can create or fuel social media crises. This article is based on an in-depth analysis of three multinational profit-making organizations experiencing social media crises after 2010. It was found that each organization employed different engagement strategies with varied outcomes. Authenticity of voice and transparency were crucial factors for success, whereas engaging indiscriminately with emotional individuals could potentially escalate an issue. The article offers strategies for engagement during social media crises.
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Disagreements over whether polarization exists in the mass public have confounded two separate types of polarization. When social polarization is separated from issue position polarization, both sides of the polarization debate can be simultaneously correct. Social polarization, characterized by increased levels of partisan bias, activism, and anger, is increasing, driven by partisan identity and political identity alignment, and does not require the same magnitude of issue position polarization. The partisan-ideological sorting that has occurred in recent decades has caused the nation as a whole to hold more aligned political identities, which has strengthened partisan identity and the activism, bias, and anger that result from strong identities, even though issue positions have not undergone the same degree of polarization. The result is a nation that agrees on many things but is bitterly divided nonetheless. An examination of ANES data finds strong support for these hypotheses.
Article
The debate over the effect of negative campaigns on vote turnout has not been settled. At present, studies demonstrating a mobilization effect seem to have the upper hand. However, neither side has offered a compelling theory of the causal mechanisms that connect nega- tive campaigns and voter turnout. This paper identifies three mechanisms of voter moti- vation—republican duty, candidate threat, and perceived closeness of the election—and tests the influence of negative ads on each. The findings suggest that each works to plau- sibly translate exposure to negative advertisement into increased participation. Since Ansolabehere and his colleagues' groundbreaking evidence of the demobilizing effects of negative campaigns (Ansolabehere, Iyengar, Simon, & Valentino, 1994), new research has begun to point in the opposite direction (Goldstein & Freedman, 2002). Negativity in campaigns is increasingly thought to mobilize rather than demobilize citizens, with a few important exceptions. Even so, the causal mechanisms of both the demobilization and mobilization hypothe- ses are underdeveloped. This paper explores three different explanations for why negative campaigns encourage rather than discourage turnout—stimulation of republican duty, anxiety toward the candidates, and perceptions of increased closeness of the race. Ultimately, all three paths for mobilization bear fruit.
Article
The growing intrusion of media into the political domain in many countries has led critics to worry about the approach of the "media-driven republic," in which mass media will usurp the functions of political institutions in the liberal state. However, close inspection of the evidence reveals that political institutions in many nations have retained their functions in the face of expanded media power. The best description of the current situation is "mediatization," where political institutions increasingly are dependent on and shaped by mass media but nevertheless remain in control of political processes and functions.
Article
There are vast literatures on the ways in which media content differs from reality, but we thus far have a rather weak sense for how exactly the representation of various topics in media differs from the distribution of information in the real world. Drawing on the gatekeeping literature, and utilizing a new automated content-analytic procedure, this article portrays both media content and “reality” as distributions of information. Measuring these allows us to identify the mechanism by which the distribution of information in the real world is transformed into the distribution of information in media; we can identify the gatekeeping function. Reporting on unemployment serves as a test case. Subsequent analyses focus on inflation and interest rates and on differences across Democratic and Republican presidencies. Results are discussed as they relate to negativity, to economic news, and to the broader study of distributions of information in political communication and politics.
Article
Work in political communication has discussed the ongoing predominance of negative news, but has offered few convincing accounts for this focus. A growing body of literature shows that humans regularly pay more attention to negative information than to positive information, however. This paper argues that we should view the nature of news content in part as a consequence of this asymmetry bias observed in human behavior. A psychophysiological experiment capturing viewers' reactions to actual news content shows that negative news elicits stronger and more sustained reactions than does positive news. Results are discussed as they pertain to political behavior and communication, and to politics and political institutions more generally.
Article
An increasing number of studies in political communication focus on the “sentiment” or “tone” of news content, political speeches, or advertisements. This growing interest in measuring sentiment coincides with a dramatic increase in the volume of digitized information. Computer automation has a great deal of potential in this new media environment. The objective here is to outline and validate a new automated measurement instrument for sentiment analysis in political texts. Our instrument uses a dictionary-based approach consisting of a simple word count of the frequency of keywords in a text from a predefined dictionary. The design of the freely available Lexicoder Sentiment Dictionary (LSD) is discussed in detail here. The dictionary is tested against a body of human-coded news content, and the resulting codes are also compared to results from nine existing content-analytic dictionaries. Analyses suggest that the LSD produces results that are more systematically related to human coding than are results based on the other available dictionaries. The LSD is thus a useful starting point for a revived discussion about dictionary construction and validation in sentiment analysis for political communication.
Article
We show that the demand for news varies with the perceived affinity of the news organization to the consumer’s political preferences. In an experimental setting, conservatives and Republicans preferred to read news reports attributed to Fox News and to avoid news from CNN and NPR. Democrats and liberals exhibited exactly the opposite syndrome—dividing their attention equally between CNN and NPR, but avoiding Fox News. This pattern of selective exposure based on partisan affinity held not only for news coverage of controversial issues but also for relatively ‘‘soft’’ subjects such as crime and travel. The tendency to select news based on anticipated agreement was also strengthened among more politically engaged partisans. Overall, these results suggest that the further proliferation of new media and enhanced media choices may contribute to the further polarization of the news audience.
Article
The past two decades have seen an explosion of social science research on negative political advertising as the number of political observers complaining about its use if not negative campaigning itself has also grown dramatically. This article reviews the literature on negative campaigning what candidates are most likely to attack their opponent, under what circumstances, and most importantly, to what effect. We also discuss the many serious methodological issues that make studying media effects of any kind so difficult, and make suggestions for “best practices in conducting media research. Contrary to popular belief, there is little scientific evidence that attacking one's opponent is a particularly effective campaign technique, or that it has deleterious effects on our system of government. We conclude with a discussion of whether negative political advertising is bad for democracy.
Article
The conventional wisdom about negative political campaigning holds that it works, i.e., it has the consequences its practitioners intend. Many observers also fear that negative campaigning has unintended but detrimental effects on the political system itself. An earlier meta-analytic assessment of the relevant literature found no reliable evidence for these claims, but since then the research literature has more than doubled in size and has greatly improved in quality. We reexamine this literature and find that the major conclusions from the earlier meta-analysis still hold. All told, the research literature does not bear out the idea that negative campaigning is an effective means of winning votes, even though it tends to be more memorable and stimulate knowledge about the campaign. Nor is there any reliable evidence that negative campaigning depresses voter turnout, though it does slightly lower feelings of political efficacy, trust in government, and possibly overall public mood.
Article
Recent controversy over campaign advertising has focused on the effects of negative ads on voters. Proponents of the demobilization hypothesis have argued that negative ads turn off voters and shrink the size of the electorate. We argue that negative campaign charges are just as likely to engage potential voters, leading to a stimulation effect when it comes to turnout. Drawing on a new source of ad–tracking data from the 1996 presidential election, combined with the 1996 National Election Study, we generate estimates of the probability that voters were exposed to positive and negative political advertising. With this new, more precise approach, we find unambiguous evidence that exposure to negative campaign ads actually stimulates voter turnout.
Article
The effect of negative campaigning on voter turnout has been a major focus of research in recent years. In a path-breaking analysis, Stephen Ansolabehere and Shanto Iyengar found that negative campaigning by Senate candidates significantly depresses turnout. Subsequent studies that emerged to challenge their analysis reached more optimistic findings. Determining who is right is difficult to establish because the methodology of these later studies differs so dramatically from the original study and because a strong theoretical case can be made for each type of finding. Through a careful examination and improvement of Ansolabehere and Iyengar’s aggregate analysis of Senate campaigns, this article shows that their initial conclusions regarding the demobilizing effect of campaign attacks were premature. Even using Ansolabehere and Iyengar’s own data, it appears that citizens are resilient to the onslaught of negative campaigning. This paper shows that the findings in the literature are not as contradictory as they initially appear, thereby moving it toward closure on this topic and clearing the way for a series of new research questions.
Conference Paper
Retweeting is the key mechanism for information diffusion in Twitter. It emerged as a simple yet powerful way of disseminating information in the Twitter social network. Even though a lot of information is shared in Twitter, little is known yet about how and why certain information spreads more widely than others. In this paper, we examine a number of features that might affect retweetability of tweets. We gathered content and contextual features from 74M tweets and used this data set to identify factors that are significantly associated with retweet rate. We also built a predictive retweet model. We found that, amongst content features, URLs and hashtags have strong relationships with retweetability. Amongst contextual features, the number of followers and followees as well as the age of the account seem to affect retweetability, while, interestingly, the number of past tweets does not predict retweetability of a user's tweet. We believe that this research would inform the design of sensemaking and analytics tools for social media streams.
Chapter
Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.
Article
The recent emergence of online social media has had a significant effect on the contemporary political landscape, yet our understanding of this remains less than complete. This article adds to current understanding of the online engagement between politicians and the public by presenting the first quantitative analysis of the utilisation of the social network tool Twitter by Australian politicians. The analysis suggests that politicians are attempting to use Twitter for political engagement, though some are more successful in this than others. Politicians are noisier than Australians in general on Twitter, though this is due more to broadcasting than conversing. Those who use Twitter to converse appear to gain more political benefit from the platform than others. Though politicians cluster by party, a relatively 'small world' network is evident in the Australian political discussion on Twitter.
The median voter data set: Voter preferences across 50 democracies
  • J E De Neve
Campaign sentiment in European party manifestos
  • M Golder
  • T Gschwend
  • C Crabtree
  • I Indirdason
How the news media amplify negative messages
  • T Ridout
  • A Walter
Birds of the same feather tweet together: Bayesian ideal point estimation using twitter data
  • P Barberá
Candidate strategy and the decision to go negative
  • D F Damore
Personalized campaigns in party-centred politics
  • G S Enli
  • E Skogerbø