We study the cohesion within and the coalitions between political groups in the Eighth European Parliament (2014–2019) by analyzing two entirely different aspects of the behavior of the Members of the European Parliament (MEPs) in the policy-making processes. On one hand, we analyze their co-voting patterns and, on the other, their retweeting behavior. We make use of two diverse datasets in the analysis. The first one is the roll-call vote dataset, where cohesion is regarded as the tendency to co-vote within a group, and a coalition is formed when the members of several groups exhibit a high degree of co-voting agreement on a subject. The second dataset comes from Twitter; it captures the retweeting (i.e., endorsing) behavior of the MEPs and implies cohesion (retweets within the same group) and coalitions (retweets between groups) from a completely different perspective. We employ two different methodologies to analyze the cohesion and coalitions. The first one is based on Krippendorff’s Alpha reliability, used to measure the agreement between raters in data-analysis scenarios, and the second one is based on Exponential Random Graph Models, often used in social-network analysis. We give general insights into the cohesion of political groups in the European Parliament, explore whether coalitions are formed in the same way for different policy areas, and examine to what degree the retweeting behavior of MEPs corresponds to their co-voting patterns. A novel and interesting aspect of our work is the relationship between the co-voting and retweeting patterns.
Lazer @cite_1 highlights the importance of network-based approaches in political science in general by arguing that politics is a relational phenomenon at its core. Some researchers have adopted the network-based approach to investigate the structure of legislative work in the US Congress, including committee and sub-committee membership @cite_5 , bill co-sponsoring @cite_15 , and roll-call votes @cite_19 . More recently, Dal @cite_2 examined the community structure with respect to political coalitions and government structure in the Italian Parliament. @cite_11 examined the constituency, personal, and strategic characteristics of MEPs that influence their tweeting behavior. They suggested that Twitter's characteristics, like immediacy, interactivity, spontaneity, personality, and informality, are likely to resonate with political parties across Europe. By fitting regression models, the authors find that MEPs from incohesive groups have a greater tendency to retweet.
@cite_1 @cite_19 @cite_2 @cite_5 @cite_15 @cite_11
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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. Whatare the relational dimensions of politics? Does theway that people and organizations are connected to each other matter? Are our opinions affected by the people with whom we talk? Are legislators affected by lobbyists? Is the capacity of social movements to mobilize affected by the structure of societ al networks? Powerful evidence in the literature answers each of these questions in the affirmative. However, compared to other paradigmatic foci, political science has invested tiny amounts of capacity in the study of the relevance of networks to political phenomena. Far more attention has been paid to the psychology of howpeople process information individually as opposed to collectively, and to the role that institutions play in structuring politics as opposed to the relational undergirdings of politics. A review of the flagship journals in political science reveals a dearth of articles on networks. Few, if any, doctoral programs include courses for which the primary focus is network-related ideas, and even the notion of a relational dependence in data is rarely mentioned in discussions of the assumptions embedded in the statistical methods that dominate political science. This gap is arguably the result of the boundaries among social sciencedisciplines thatemerged inthe1950s,whensocial networkideasfoundtheirhomelargely insociologyandanthropology while political science leaned toward statistical methods that assumed away interdependence among observations. Ironically, there is now awave of interest in networks in political science thathasoriginatedpartly in sociologyandpartly in thatmost distant of disciplines frompolitical science, physics. The objective of this article is to provide an intellectual history of the study of social networks and political networks in particular, as well as the current trajectory of such work. 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... 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...