Concerns have reached the mainstream about how social media are affecting political outcomes. One trajectory for this is the exposure of politicians to online abuse. In this paper we use 1.4 million tweets from the months before the 2015 and 2017 UK general elections to explore the abuse directed at politicians. This collection allows us to look at abuse broken down by both party and gender and aimed at specific Members of Parliament. It also allows us to investigate the characteristics of those who send abuse and their topics of interest. Results show that in both absolute and proportional terms, abuse increased substantially in 2017 compared with 2015. Abusive replies are somewhat less directed at women and those not in the currently governing party. Those who send the abuse may be issue-focused, or they may repeatedly target an individual. In the latter category, accounts are more likely to be throwaway. Those sending abuse have a wide range of topical triggers, including borders and terrorism.
Whilst online fora have attracted much attention as a way of exploring political dynamics @cite_15 @cite_4 @cite_8 @cite_12 @cite_16 @cite_13 , and the effect of abuse and incivility in these contexts has been explored @cite_7 @cite_19 @cite_3 @cite_2 , little work exists regarding the abusive and intimidating ways people address politicians online; a trend that has worrying implications for democracy. collected tweets centred around candidates for the European Parliament election in 2014 from Spain, Germany, the United Kingdom and France posted in the month surrounding the election. They find that the extent of the abuse and harrassment a politician is subject to correlates with their engagement with the medium. Their analysis focuses on the way in which uncivil behaviour negatively impacts on the potential of the medium to increase interactivity and positively stimulate democracy. Stambolieva studies online abuse against female Members of Parliament (MPs) only; in studying male MPs as well, we are able to contrast the level of abuse they each receive. Furthermore, we contrast proportional with absolute figures, creating quite a different impression from the one she gives.
@cite_4 @cite_7 @cite_8 @cite_3 @cite_19 @cite_2 @cite_15 @cite_16 @cite_13 @cite_12
2926293302 2079373549 1976267568 2312324132 2220275476 2396708059 1692960356 2122003588 91442942 1982558964 2563692779 153654188 2336439626 2048702049 1542344929 2786315637 1986316755 2095655043 2184009014 2073775149
Disengagement and disenchantment with the Parliamentary process is an important concern in today's Western democracies. Members of Parliament (MPs) in the UK are therefore seeking new ways to engage with citizens, including being on digital platforms such as Twitter. In recent years, nearly all (579 out of 650) MPs have created Twitter accounts, and have amassed huge followings comparable to a sizable fraction of the country's population. This paper seeks to shed light on this phenomenon by examining the volume and nature of the interaction between MPs and citizens. We find that although there is an information overload on MPs, attention on individual MPs is focused during small time windows when something topical may be happening relating to them. MPs manage their interaction strategically, replying selectively to UK-based citizens and thereby serving in their role as elected representatives, and using retweets to spread their party's message. Most promisingly, we find that Twitter opens up new avenues with substantial volumes of cross-party interaction, between MPs of one party and citizens who support (follow) MPs of other parties. Transmitting messages in the most efficient way as possible has always been one of politicians’ main concerns during electoral processes. Due to the rapidly growing number of users, online social networks have become ideal platforms for politicians to interact with their potential voters. Exploiting the available potential of these tools to maximize their influence over voters is one of politicians’ actual challenges. To step in this direction, we have analyzed the user activity in the online social network Twitter, during the 2011 Spanish Presidential electoral process, and found that such activity is correlated with the election results. We introduce a new measure to study political sentiment in Twitter, which we call the relative support. We have also characterized user behavior by analyzing the structural and dynamical patterns of the complex networks emergent from the mention and retweet networks. Our results suggest that the collective attention is driven by a very small fraction of users. Furthermo... Is social media a valid indicator of political behavior? There is considerable debate about the validity of data extracted from social media for studying offline behavior. To address this issue, we show that there is a statistically significant association between tweets that mention a candidate for the U.S. House of Representatives and his or her subsequent electoral performance. We demonstrate this result with an analysis of 542,969 tweets mentioning candidates selected from a random sample of 3,570,054,618, as well as Federal Election Commission data from 795 competitive races in the 2010 and 2012 U.S. congressional elections. This finding persists even when controlling for incumbency, district partisanship, media coverage of the race, time, and demographic variables such as the district's racial and gender composition. Our findings show that reliable data about political behavior can be extracted from social media. ABSTRACTAlthough conceptual efforts have often suggested that the Internet harbors considerable possibilities to revolutionize political participation, empirical studies have often presented rather limited impacts in this regard. Nevertheless, novel online services such as Twitter are still pointed to as having potential to be employed by citizens and politicians alike. Utilizing state-of-the-art data collection methods, this study builds on the suggestions of previous research and gauges the degree to which EU parliamentarians make use of Twitter for so-called permanent campaigning. Specifically, the paper seeks to assess the degree to which Twitter use by European Parliament representatives can be described as being characterized by permanence—a concept related to the professionalization of political campaigns. Thus, by examining these uses outside of election periods, the study provides useful insights into the day-to-day uses of Twitter, contributing to the limited body of work focusing on the everyda... Existing studies focusing on politicians' adoption of Twitter have found that they use it primarily as a broadcasting tool. We argue that citizens' impolite and or uncivil behavior is one possible explanation for such decisions. Social media conversations are rife with harassment and politicians are a prime target. This alters the incentive structure of engaging in dialogue on social media. We use Spanish, Greek, German, and U.K. candidates' tweets sent during the run-up to the recent European Parliament elections, and rely on automated text analysis and machine learning methods to measure their level of civility. Our contribution is an actor-oriented theory of political dialogue that incorporates Twitter's specific affordances, clarifying how and why Twitter's democratic promise may be limited. Social media play an increasingly important part in the communication strategies of political campaigns by reflecting information about the policy preferences and opinions of political actors and their public followers. In addition, the content of the messages provides rich information about the political issues and the framing of those issues during elections, such as whether contested issues concern Europe or rather extend pre-existing national debates. In this study, we survey the European landscape of social media using tweets originating from and referring to political actors during the 2014 European Parliament election campaign. We describe the language and national distribution of the messages, the relative volume of different types of communications, and the factors that determine the adoption and use of social media by the candidates. We also analyze the dynamics of the volume and content of the communications over the duration of the campaign with reference to both the EU integration dimension of the debate and the prominence of the most visible list-leading candidates. Our findings indicate that the lead candidates and their televised debate had a prominent influence on the volume and content of communications, and that the content and emotional tone of communications more reflects preferences along the EU dimension of political contestation rather than classic national issues relating to left-right differences. We analyze the network of relations between parliament members according to their voting behavior. In particular, we examine the emergent community structure with respect to political coalitions and government alliances. We rely on tools developed in the Complex Network literature to explore the core of these communities and use their topological features to develop new metrics for party polarization, internal coalition cohesiveness and government strength. As a case study, we focus on the Chamber of Deputies of the Italian Parliament, for which we are able to characterize the heterogeneity of the ruling coalition as well as parties specific contributions to the stability of the government over time. We find sharp contrast in the political debate which surprisingly does not imply a relevant structure based on establised parties. We take a closer look to changes in the community structure after parties split up and their effect on the position of single deputies within communities. Finally, we introduce a way to track the stability of the government coalition over time that is able to discern the contribution of each member along with the impact of its possible defection. While our case study relies on the Italian parliament, whose relevance has come into the international spotlight in the present economic downturn, the methods developed here are entirely general and can therefore be applied to a multitude of other scenarios. As more and more people use social media to communicate their view and perception of elections, researchers have increasingly been collecting and analyzing data from social media platforms. Our research focuses on social media communication related to the 2013 election of the German parliament [translation: Bundestagswahl 2013]. We constructed several social media datasets using data from Facebook and Twitter. First, we identified the most relevant candidates (n=2,346) and checked whether they maintained social media accounts. The Facebook data was collected in November 2013 for the period of January 2009 to October 2013. On Facebook we identified 1,408 Facebook walls containing approximately 469,000 posts. Twitter data was collected between June and December 2013 finishing with the constitution of the government. On Twitter we identified 1,009 candidates and 76 other agents, for example, journalists. We estimated the number of relevant tweets to exceed eight million for the period from July 27 to September 27 alone. In this document we summarize past research in the literature, discuss possibilities for research with our data set, explain the data collection procedures, and provide a description of the data and a discussion of issues for archiving and dissemination of social media data. In this study we investigate how social media shape the networked public sphere and facilitate communication between communities with different political orientations. We examine two networks of political communication on Twitter, comprised of more than 250,000 tweets from the six weeks leading up to the 2010 U.S. congressional midterm elections. Using a combination of network clustering algorithms and manually-annotated data we demonstrate that the network of political retweets exhibits a highly segregated partisan structure, with extremely limited connectivity between left- and right-leaning users. Surprisingly this is not the case for the user-to-user mention network, which is dominated by a single politically heterogeneous cluster of users in which ideologically-opposed individuals interact at a much higher rate compared to the network of retweets. To explain the distinct topologies of the retweet and mention networks we conjecture that politically motivated individuals provoke interaction by injecting partisan content into information streams whose primary audience consists of ideologically-opposed users. We conclude with statistical evidence in support of this hypothesis. ABSTRACTWith the advances in interpersonal communication of the “Web 2.0” era, questions about the importance of civility are perhaps more important than ever. Mass digital interaction between strangers has become an everyday occurrence, bound by few behavioral norms. I argue that the widespread presence of incivility in online political communication limits the deliberative potential of online interactions. To test this hypothesis, I manipulate exposure to uncivil political discourse in an online discussion forum. I find that exposure to disagreeable uncivil political talk induces feelings of anger and aversion, which in turn reduces satisfaction with the message board discourse. On the other hand, exposure to like-minded incivility increases the use of uncivil behavior in political comments by message board posters. Notably, these effects mainly occur when histrionic, emotional incivility is present. I discuss why like-minded and disagreeable incivility have different effects, and reflect on what the pr... ABSTRACTMembers of the European Parliament (MEPs) struggle to connect with European publics. Few European Union (EU) citizens feel connected to their MEPs. Levels of turnout for European Parliament (EP) elections are low, and EU citizens rarely retain EP-related news. For these and other reasons, we might expect MEPs to embrace social media platforms, like Twitter, that facilitate interactivity, spontaneity, personality, and informality. In reality, however, significant variation characterizes the timing and nature of MEPs’ engagement with Twitter. In this article, we document and seek to explain elements of this variation. We examine five dimensions of MEP engagement with Twitter: Do MEPs establish Twitter accounts? Are they early adopters? How frequently do they tweet? And how, exactly, do they use Twitter – do they engage in direct conversations via Twitter's @-reply functionality and or refer followers to other content via retweeting? We find that MEPs’ approaches to Twitter are conditioned by specifi... Using social media for political discourse is becoming common practice, especially around election time. One interesting aspect of this trend is the possibility of pulsing the public’s opinion about the elections, and that has attracted the interest of many researchers and the press. Allegedly, predicting electoral outcomes from social media data can be feasible and even simple. Positive results have been reported, but without an analysis on what principle enables them. Our work puts to test the purported predictive power of socialmedia metrics against the 2010 US congressional elections. Here, we applied techniques that had reportedly led to positive election predictions in the past, on the Twitter data collected from the 2010 US congressional elections. Unfortunately, we find no correlation between the analysis results and the electoral outcomes, contradicting previous reports. Observing that 80 years of polling research would support our findings, we argue that one should not be accepting predictions about events using social media data as a black box. Instead, scholarly research should be accompanied by a model explaining the predictive power of social media, when there is one. Using 414,322 tweets drawn from 143,404 individual Twitter users located in all 435 U.S. congressional districts, this study employed big data and automated content analysis techniques to explore the degree to which socioeconomic status SES, social capital potential the degree to which a congressional district has the potential for interconnected citizen networks, and in-district partisan polarization were associated with incivility on Twitter during the 2012 presidential election. Broadly speaking, and with some exceptions, the results indicated that election oriented incivility on Twitter was highest in districts that had low SES indicators, low levels of social capital potential, and low levels of partisan polarity. In its sum, this study shows how large social data sets i.e., the Census can be combined with big data to explain social phenomena. Members of the European Parliament (MEPs) typically follow one of two career paths, either advancing within the European Parliament itself or returning to higher offices in their home states. We argue that these different ambitions condition legislative behavior. Specifically, MEPs seeking domestic careers defect from group leadership votes more frequently and oppose legislation that expands the purview of supranational institutions. We show how individual, domestic-party, and national-level variables shape the careers available to MEPs and, in turn, their voting choices. To test the argument, we analyze MEPs’ roll-call voting behavior in the 5th session of the EP (1999–2004) using a random effects model that captures idiosyncrasies in voting behavior across both individual MEPs and specific roll-call votes. While the newspaper industry is in crisis and less time and resources are available for newsgathering, social media turn out to be a convenient and cheap beat for (political) journalism. This article investigates the use of Twitter as a source for newspaper coverage of the 2010 British and Dutch elections. Almost a quarter of the British and nearly half of the Dutch candidates shared their thoughts, visions, and experiences on Twitter. Subsequently, these tweets were increasingly quoted in newspaper coverage. We present a typology of the functions tweets have in news reports: they were either considered newsworthy as such, were a reason for further reporting, or were used to illustrate a broader news story. Consequently, we will show why politicians were successful in producing quotable tweets. While this paper, which is part of a broader project on how journalists (and politicians) use Twitter, focuses upon the coverage of election campaigns, our results indicate a broader trend in journalism. In the future, the reporter who attends events, gathers information face-to-face, and asks critical questions might instead aggregate information online and reproduce it in journalism discourse thereby altering the balance of power between journalists and sources. Hate speech, offensive language, sexism, racism and other types of abusive behavior have become a common phenomenon in many online social media platforms. In recent years, such diverse abusive behaviors have been manifesting with increased frequency and levels of intensity. This is due to the openness and willingness of popular media platforms, such as Twitter and Facebook, to host content of sensitive or controversial topics. However, these platforms have not adequately addressed the problem of online abusive behavior, and their responsiveness to the effective detection and blocking of such inappropriate behavior remains limited. In the present paper, we study this complex problem by following a more holistic approach, which considers the various aspects of abusive behavior. To make the approach tangible, we focus on Twitter data and analyze user and textual properties from different angles of abusive posting behavior. We propose a deep learning architecture, which utilizes a wide variety of available metadata, and combines it with automatically-extracted hidden patterns within the text of the tweets, to detect multiple abusive behavioral norms which are highly inter-related. We apply this unified architecture in a seamless, transparent fashion to detect different types of abusive behavior (hate speech, sexism vs. racism, bullying, sarcasm, etc.) without the need for any tuning of the model architecture for each task. We test the proposed approach with multiple datasets addressing different and multiple abusive behaviors on Twitter. Our results demonstrate that it largely outperforms the state-of-art methods (between 21 and 45 improvement in AUC, depending on the dataset). Abstract Considering the integral relationship between public relations and democracy ( Martinelli, 2011 ) coupled with the growing use of social media for democratic aims ( Smith, 2011 ) the current study examines the effectiveness of Twitter as a public relations communications tool for congressional campaigns. Specifically, as a means of testing Twitter's effectiveness in informing and engaging voters, congressional candidate and political party Twitter use for all 435 U.S. House of Representatives races ( N = 1284) are compared with 2010 election outcomes. Results indicate that candidates’ Twitter use significantly increased their odds of winning, controlling for incumbency and Party ID. Additionally, significant differences between incumbents’ and challengers’ Twitter use during the election cycle emerged, which has important implications for public relations practices aimed at achieving democratic outcomes. Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have hindered their use in political science research. Here lies the promise of automated text analysis: it substantially reduces the costs of analyzing large collections of text. We provide a guide to this exciting new area of research and show how, in many instances, the methods have already obtained part of their promise. But there are pitfalls to using automated methods—they are no substitute for careful thought and close reading and require extensive and problem-specific validation. We survey a wide range of new methods, provide guidance on how to validate the output of the models, and clarify misconceptions and errors in the literature. To conclude, we argue that for automated text methods to become a standard tool for political scientists, methodologists must contribute new methods and new methods of validation. Language is the medium for politics and political conflict. Candidates debate and state policy positions during a campaign. Once elected, representatives write and debate legislation. After laws are passed, bureaucrats solicit comments before they issue regulations. Nations regularly negotiate and then sign peace treaties, with language that signals the motivations and relative power of the countries involved. News reports document the day-to-day affairs of international relations that provide a detailed picture of conflict and cooperation. Individual candidates and political parties articulate their views through party platforms and manifestos. Terrorist groups even reveal their preferences and goals through recruiting materials, magazines, and public statements. These examples, and many others throughout political science, show that to understand what politics is about we need to know what political actors are saying and writing. Recognizing that language is central to the study of politics is not new. To the contrary, scholars of politics have long recognized that much of politics is expressed in words. But scholars have struggled when using texts to make inferences about politics. The primary problem is volume: there are simply too many political texts. Rarely are scholars able to manually read all the texts in even moderately sized corpora. And hiring coders to manually read all documents is still very expensive. The result is that We present a generic approach to real-time monitoring of the Twitter sentiment and show its application to the Bulgarian parliamentary elections in May 2013. Our approach is based on building high quality sentiment classification models from manually annotated tweets. In particular, we have developed a user-friendly annotation platform, a feature selection procedure based on maximizing prediction accuracy, and a binary SVM classifier extended with a neutral zone. We have also considerably improved the language detection in tweets. The evaluation results show that before and after the Bulgarian elections, negative sentiment about political parties prevailed. Both, the volume and the difference between the negative and positive tweets for individual parties closely match the election results. The later result is somehow surprising, but consistent with the prevailing negative sentiment during the elections. In this paper we introduce the novel problem of understanding visual persuasion. Modern mass media make extensive use of images to persuade people to make commercial and political decisions. These effects and techniques are widely studied in the social sciences, but behavioral studies do not scale to massive datasets. Computer vision has made great strides in building syntactical representations of images, such as detection and identification of objects. However, the pervasive use of images for communicative purposes has been largely ignored. We extend the significant advances in syntactic analysis in computer vision to the higher-level challenge of understanding the underlying communicative intent implied in images. We begin by identifying nine dimensions of persuasive intent latent in images of politicians, such as "socially dominant, " "energetic, " and "trustworthy, " and propose a hierarchical model that builds on the layer of syntactical attributes, such as "smile" and "waving hand, " to predict the intents presented in the images. To facilitate progress, we introduce a new dataset of 1, 124 images of politicians labeled with ground-truth intents in the form of rankings. This study demonstrates that a systematic focus on visual persuasion opens up the field of computer vision to a new class of investigations around mediated images, intersecting with media analysis, psychology, and political communication.