Quantifying echo chamber effects in information spreading over political communication networks

Echo chambers in online social networks, in which users prefer to interact only with ideologically-aligned peers, are believed to facilitate misinformation spreading and contribute to radicalize political discourse. In this paper, we gauge the effects of echo chambers in information spreading phenomena over political communication networks. Mining 12 million Twitter messages, we reconstruct a network in which users interchange opinions related to the impeachment of the former Brazilian President Dilma Rousseff. We define a continuous {political position} parameter, independent of the network's structure, that allows to quantify the presence of echo chambers in the strongly connected component of the network, reflected in two well-separated communities of similar sizes with opposite views of the impeachment process. By means of simple spreading models, we show that the capability of users in propagating the content they produce, measured by the associated spreadability, strongly depends on their attitude. Users expressing pro-impeachment sentiments are capable to transmit information, on average, to a larger audience than users expressing anti-impeachment sentiments. Furthermore, the users' spreadability is correlated to the diversity, in terms of political position, of the audience reached. Our method can be exploited to identify the presence of echo chambers and their effects across different contexts and shed light upon the mechanisms allowing to break echo chambers.Comment: 9 pages, 4 figures. Supplementary Information available as ancillary fil

Analyzing Ideological Communities in Congressional Voting Networks

We here study the behavior of political party members aiming at identifying how ideological communities are created and evolve over time in diverse (fragmented and non-fragmented) party systems. Using public voting data of both Brazil and the US, we propose a methodology to identify and characterize ideological communities, their member polarization, and how such communities evolve over time, covering a 15-year period. Our results reveal very distinct patterns across the two case studies, in terms of both structural and dynamic properties

Exploring the democratic potential of online social networking: The scope and limitations of e-participation

Copyright © 2012 by the Association for Information Systems.The availability and promise of social networking technologies with their perceived open philosophy has increasingly inspired citizens around the world to participate in political activity on the Web. Recent examples range from opposing public policies, such as government funding cuts, to organizing revolutionary social movements, such as those in the Middle East and North Africa. Although online spaces create remarkable opportunities for various forms of political action, there are concerns over the power of existing institutions to control and even censor such interaction spaces. The objective of this article is to draw together different insights on the online engagement phenomenon, highlighting both its potential and limitations as a mechanism for fostering democratic debate and influencing policy making. We examine recent examples from Europe, the Middle East and Latin America. Finally, we summarize the implications of our work and outline directions for further research

Identifying communicator roles in Twitter

Twitter has redefined the way social activities can be coordinated; used for mobilizing people during natural disasters, studying health epidemics, and recently, as a communication platform during social and political change. As a large scale system, the volume of data transmitted per day presents Twitter users with a problem: how can valuable content be distilled from the back chatter, how can the providers of valuable information be promoted, and ultimately how can influential individuals be identified?To tackle this, we have developed a model based upon the Twitter message exchange which enables us to analyze conversations around specific topics and identify key players in a conversation. A working implementation of the model helps categorize Twitter users by specific roles based on their dynamic communication behavior rather than an analysis of their static friendship network. This provides a method of identifying users who are potentially producers or distributers of valuable knowledge

Analyzing Polarization on Social Media: A Case Study of the 2022 Brazil Presidential Election

Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceSocial Media has become a big part of our society and has now a significant role in the relationships between inter and intra-communities. Twitter is now an important communication platform for political campaigns: in the last years, politicians, campaigners, and general users have been extensively using Twitter to promote campaigns and engage in political discussions. Some studies argue that social media can create filter bubbles by limiting the flow of online information, and therefore creating communities where exposure to political diversity is rare. This selective exposure can build echo chambers where individuals only interact with those who have the same opinions as they have and by doing that, they build a polarized community. Identifying, understanding, and mitigating polarization is very important for the democratic process. People should be exposed to different ideas and opinions so they can choose their representatives without being influenced by some portion of the information. This project analyzed political polarization on social media using data from Twitter. Brazil’s presidential election in 2022 was used as a case study. Tweets from the two main candidates were extracted. A Topic Modeling algorithm was used to cluster tweets in topics. An Engagement Graph was built based on the interactions between users, candidates, and topics and was used to compute the Topic Centrality measures. A pre-trained Sentiment Analysis model was used to measure the sentiment polarity of each tweet. In the end, the project analyzed the extracted features and identified which topics were more central to each candidate and how users interact with them. The major conclusion of this work is that polarization in Brazil is more affective than ideological since the user’s sentiments towards topics are not as relevant as the sentiments towards the candidates

Live Blogging and Social Media Curation: Challenges and Opportunities for Journalism

Blogging and social media’s contribution to a realignment of the relationship between journalists and their audiences is discussed by Einar Thorsen in Live Blogging and Social Media Curation. Journalists are facing challenges to preserve traditional standards, such as verification of information and sources, whilst also capitalising on the opportunities afforded by the immediacy, transparency and interactive nature of online communication. Thorsen analyses these issues through two case studies: one focuses on ‘live’ blogging and elections, and a second looks at the role of social media in the Arab Spring. He demonstrates how journalists face new challenges in relation to social media curation, whilst the emergent forms and practices also present a wealth of opportunities