Search

This article analyzes 3 months of online debate during the electoral campaign for the 2016 Italian constitutional referendum. Through supervised sentiment analysis, we assess the extent of support for the referendum within the general public of Twitter users (Twittersphere) by analyzing the voting intentions expressed online in 2,369,333 tweets. Similarly, we exploit the practice of social TV and investigate the support for the referendum expressed by the 160,465 tweets posted by second screeners, that is, the subsample of Twitter users who watched and actively commented on nine political talk shows during the campaign. We compare the mentions and the attitudes of the Twittersphere and the second screeners by means of a lead–lag analysis to test whether the second screeners can act as influencers and trendsetters able to shape or anticipate attention and opinions toward an issue within larger audiences. The results reveal an inverse relationship between the Twittersphere and the second screeners whereby the reactions of the latter diverge from those of the general Twitter public. This finding has implications for the literature on echo chambers and the polarization of social media. [ABSTRACT FROM AUTHOR]

Does the interaction with the opinions of 'friends' and 'followers' affect the behavior of politicians? So far, little attention has been devoted to the effect of social networking sites (SNS) on 'hard politics' choices. Focusing on two case studies related to Italian politics, namely the debate on the civil unions bill and the 'Fertility Day' crisis, in 2016, this paper tries to fill this gap assessing the influence of SNS on the behavior of politicians. For this purpose, supervised aggregated sentiment analysis and time series analysis are used to evaluate whether politicians surrender to the pressure put on them by their followers. The findings highlight some positive effects in terms of accountability/transparency, though in terms of responsiveness politics seems to continue as usual, and the road toward a full 'sentiment democracy' is still far ahead. [ABSTRACT FROM AUTHOR]

Going beyond source and content pluralism, we propose a two-dimensional audience-based measure of perceived pluralism by exploiting the practice of "social TV". For this purpose, 135,228 tweets related to 30 episodes of prime time political talk shows broadcast in Italy in 2014 have been analyzed through supervised sentiment analysis. The findings suggest that the two main TV networks compete by addressing generalist audiences. The public television offers a plural set of talk shows but ignores the anti-political audience. The ideological background of the anchorman shapes the audience's perception, while the gender of the guests does not seem to matter. [ABSTRACT FROM AUTHOR]

Recent studies investigated the effect of e-campaigning on the electoral performance. However, little attention has been paid to the content of e-campaigning. Given that political parties broadcast minute-by-minute the campaign messages on social media, this comprehensive and unmediated information can be useful to evaluate the impact of different electoral strategies. Accordingly, this article examines the electoral campaign for the 2013 Italian general election to assess the effectiveness of positive and negative campaigning messages, measured through content analysis of information published on the official Twitter accounts of Italian parties. We evaluate their impact on the share of unsolicited voting intentions expressed on Twitter, measured through an innovative technique of sentiment analysis. Our results show that negative campaign has positive effects and its impact is stronger when the attacker is meanwhile under attack. Conversely, we only find a circumstantial effect of positive campaign related to clientelistic and distributive appeals. [ABSTRACT FROM AUTHOR]

This article addresses the potential role played by social media analysis in promoting interaction between politicians, bureaucrats, and citizens. We show that in a 'Big Data' world, the comments posted online by social media users can profitably be used to extract meaningful information, which can support the action of policymakers along the policy cycle. We analyze Twitter data through the technique of Supervised Aggregated Sentiment Analysis. We develop two case studies related to the 'jobs act' labor market reform and the '#labuonascuola' school reform, both formulated and implemented by the Italian Renzi cabinet in 2014-15. Our results demonstrate that social media data can help policymakers to rate the available policy alternatives according to citizens' preferences during the formulation phase of a public policy; can help them to monitor citizens' opinions during the implementation phase; and capture stakeholders' mobilization and de-mobilization processes. We argue that, although social media analysis cannot replace other research methods, it provides a fast and cheap stream of information that can supplement traditional analyses, enhancing responsiveness and institutional learning. [ABSTRACT FROM AUTHOR]

The rise of social network sites reopened the debate on the ability of traditional media to influence public opinion and act as an agenda setter. To answer this question, the present paper investigates first-level and second-level agenda-setting effects in the online environment by focusing on two heated Italian political debates (the reform of public funding of parties and the debate over austerity). By employing innovative and efficient statistical methods such as the lead–lag analysis and supervised sentiment analysis, we compare the attention devoted to each issue and the content spread by online news media and Twitter users. Our results show that online media keep their first-level agenda-setting power even though we find a marked difference between the slant of online news and the Twitter sentiment. [ABSTRACT FROM AUTHOR]

What is the relationship between Internet usage and political trust? To answer this question, we performed a cross-sectional analysis of Eurobarometer survey data related to 27 countries and a supervised sentiment analysis of online political information broadcast during the Italian debate on the reform of public funding of parties. The results disclose the differences between Web 1.0 websites and Web 2.0 social media, showing that consumption of news from information/news websites is positively associated with higher trust, while access to information available on social media is linked with lower trust. This has implications for the debate on social media as a public sphere and for the tension between professional and citizen journalism. [ABSTRACT FROM AUTHOR]

In recent years, there has been an increasing attention in the literature on the possibility of analyzing social media as a useful complement to traditional off-line polls to monitor an electoral campaign. Some scholars claim that by doing so, we can also produce a forecast of the result. Relying on a proper methodology for sentiment analysis remains a crucial issue in this respect. In this work, we apply the supervised method proposed by Hopkins and King to analyze the voting intention of Twitter users in the United States (for the 2012 Presidential election) and Italy (for the two rounds of the centre-left 2012 primaries). This methodology presents two crucial advantages compared to traditionally employed alternatives: a better interpretation of the texts and more reliable aggregate results. Our analysis shows a remarkable ability of Twitter to “nowcast” as well as to forecast electoral results. [ABSTRACT FROM AUTHOR]

The growing usage of social media by a wider audience of citizens sharply increases the possibility of investigating the web as a device to explore and track political preferences. In the present paper we apply a method recently proposed by other social scientists to three different scenarios, by analyzing on one side the online popularity of Italian political leaders throughout 2011, and on the other the voting intention of French Internet users in both the 2012 presidential ballot and the subsequent legislative election. While Internet users are not necessarily representative of the whole population of a country’s citizens, our analysis shows a remarkable ability for social media to forecast electoral results, as well as a noteworthy correlation between social media and the results of traditional mass surveys. We also illustrate that the predictive ability of social media analysis strengthens as the number of citizens expressing their opinion online increases, provided that the citizens act consistently on these opinions. [ABSTRACT FROM PUBLISHER]