Cross-National Proximity in Online Social Network and Protest Diffusion: An Event History Analysis of Arab Spring

This study examines the role of online social network proximity in cross-national diffusion of offline protests. Drawn upon Valente’s (1995) network diffusion model, the study operationalizes social network proximity-based protest exposure, using the international Facebook friendship share data. One year-long onsite protests during Arab Spring 2011 are examined using event history modeling. The findings offer evidence of an contemporaneous online network exposure effect on cross-national diffusion of protests. An expected lagged diffusion effect was not found, however. The paper presents an innovative approach to the scholarship of global protest diffusion and collective actions.

The viral diffusion of campaign messages about political issues during the 2016 U.S. presidential election

With candidates using social media sites like Facebook and Twitter as part of their campaign strategies, social scientists are trying to understand the diffusion of political messages. Viral events can spread messages fast and far from the source, bringing candidate’s messages to new audiences and bringing new followers to candidates. To date, no studies have focused on understanding specifically what kinds of political issues the public spreads into their own networks. While the kinds of issues that spread will likely change from election to election, this work provides a comparison point for future work and is the first step in more real-time analysis that could be useful for researchers, journalists, and politicians. For this poster abstract we highlight part of our analysis, specifically, the frequency with which presidential candidates tweeted about specific issues and how the public responded by retweeting. To accomplish this, we use data visualization for exploratory data analysis. We find that that candidates and the public are most interested in different topics, but that both the public and candidates are more interested in advocacy messages than attack messages for every topic. For the final poster we will present analysis of both Facebook and Twitter, as well as confirmatory statistical analysis using regression modeling

Visualization Pedagogy in iSchools

iSchools have been offering visualization courses and developing programs in data science. The practice of visualization requires expertise in a diverse range of skills including design, data curation and coding, all of which leverage iSchool strengths. Thus, iSchools have a unique opportunity to develop curricula suited for data scientists that leverage iSchool strengths. During this half day, fishbowl style workshop, conference goers interested in visualization education at information schools will be invited to explore themes related to the inclusion of information and data visualization coursework in iSchool data science curricula. Workshop organizers represent several diverse disciplines with interest in applied visualization practices and collectively have a range of experiences using visualizations in research and teaching visualization in the classroom.ye

Social Media, Opinion Polls, and the Use of Persuasive Messages During the 2016 US Election Primaries

Political campaigns’ use of digital technologies has been a topic of scholarly concern for over two decades, but most studies have been focused on analyzing the use of digital platforms without considering contextual factors of the race, like public opinion polls. Opinion polls are an important information source for citizens and candidates and provide the latter with information that might drive strategic communication. In this article, we explore the relationship between the use of social media in the 2016 US presidential elections and candidates’ standing in public opinion polls, focusing on the surfacing and primary stages of the campaign. We use automated content analysis to categorize social media posts from all 21 Republican and Democratic candidates. Results indicate that a candidate’s performance in the polls drives certain communicative strategies, such as the use of messages of attacks and advocacy, as well as the focus on personal image

Political Messaging Over Time: A Comparison of US Presidential Candidate Facebook Posts and Tweets in 2016 and 2020

Political campaigns have a temporal nature, which means that the strategic environment shapes the nature of candidate communication, especially the stages of campaigning—from surfacing to the general election. As social media platforms have matured and political campaigns have normalized their use of those platforms in this decade, this study examines the 2016 and 2020 US presidential campaign communication on Facebook and Twitter using data from the Illuminating project at Syracuse University. Our objective is to explore how the stages of the campaign cycle shape political communication. We also explore social media platforms as additional factors. Moreover, given the distinct and anti-normative communication style of Donald Trump, we examine whether his communication is an outlier relative to his competition in the primaries and the general election, and while a challenger in 2016 and an incumbent in 2020. Our results suggest that campaign messaging changes over the stages of the campaign, with candidates more likely to advocate for themselves during the crowded primaries, and then engage in high volumes of calls to action in the general election. The 2016 posts were substantially more attack-focused than in 2020. There is some evidence to suggest that the global pandemic affected the ways in which campaigns used their social media accounts. Of note, campaigns seem to heavily rely on Facebook for all types of strategic communication, even as the academic community primarily analyzes Twitter. Finally, Trump’s sum-total of his discourse is less negative than Clinton’s in 2016 and more advocacy-focused, overall

Biological maturation, relative age and self-regulation in male professional academy soccer players: A test of the underdog hypothesis

ObjectivesThe main and interactive effects of biological maturity status and relative age upon self-regulation in male academy soccer players are considered. Consistent with the ‘underdog’ hypothesis, whereby relatively younger players may benefit from competitive play with older peers, it was predicted later maturing and/or relatively younger players would report more adaptive self-regulation.DesignCross-sectional study.MethodPlayers (n = 171, aged 11–16 years) from four English professional soccer academies completed the modified Soccer Self-Regulation Scale. Date of birth, height, weight and parental height were obtained. Relative age was based on birth quarter for the selection year. Maturity status was based upon percentage of predicted adult height attained.ResultsLinear regression models showed later maturation was inversely associated with adaptive self-regulation, while relative age was unrelated to self-regulation.ConclusionsIn partial support of the underdog hypothesis, later maturing players appear to possess a psychological advantage

Introduction to the 2019 International Conference on Social Media & Society

This paper provides an introduction to the Proceedings of the 2019 International Conference on Social Media and Society (#SMSociety). The conference is an annual gathering of leading social media researchers, policy makers, and practitioners from around the world. Now in its 10th year, the 2019 conference is hosted by the Social Media Lab at the Ted Rogers School of Management at Ryerson University in Toronto, Canada. The Proceedings features a total of 26 papers (the acceptance rate is 42%)

Studying the viral growth of a connective action network using information event signatures

The Arab spring and Occupy Wall Street movements demonstrated that networks of individuals who share interests or grievances could quickly form on social media. There is a reciprocal relationship between the growth of these networks and the information that flows through them. This study examines this relationship by using viral information event signatures, which show the changing rate of sharing of a specific message over a period of time. The Occupy movement and the digital interactions of its participants provides a context and rich corpus of data from which to study the relationship between the signatures of information flows and the growth the Occupy network. Using exploratory data analysis and multivariate regression to analyze Occupy related tweets drawn from a corpus of over 64 million tweets, this study first provides a parameterized signature model and then uses regression to show that a relationship exists between the shape of the signature and the rate at which key actors gain followers. This work also finds a quadratic decline, over the life cycle of the movement, in the rate at which the actors gain followers. The contributions of this work include the parameterized signature model, a demonstration of its usefulness, and a new perspective on the growth of the Occupy movement

Studying Network Structural Changes Using Information Event Signatures

Thesis (Ph.D.)--University of Washington, 2014The diffusion of information is important: It impacts commerce. It influences government. It connects people in new ways. The distributed nature of our digital social networks means that traditional gatekeepers (newspapers, radio, television, and governments) lose some control over the flow of information, while new gatekeepers emerge quickly in networks of individuals who share interests or grievances. Using exploratory data analysis and confirmatory statistics to analyze over 64 million Occupy movement tweets, this dissertation makes four essential contributions that enhance our understanding of the relationship between the flow of information and the dynamics of social networks. First, based on a large set of Twitter data related to the Occupy Wall Street movement, it introduces a parameterized signature model of individual information flows. Second, it demonstrates that both the path of the information flow and the changes in the structure of the network, as measured by the growth of network gatekeepers within the Occupy movement, are related to parameters of the model. Third, the analysis suggests that the Occupy gatekeepers recursively extend their reach by repeatedly promoting information that users shared deep into Twitter's social network of followers. Fourth, the model provides the initial steps towards a theory explaining the process by which social network dynamics and information flows interact. This model's capacity to identify information flows deep in networks and to predict trends that potentially alter those networks will prove useful to individuals, to organizations, and to governments

Semaan et al. Social Infrastructures: Towards a theory of Resilience Maintaining and Creating Social Infrastructures: Towards a Theory of Resilience

ABSTRACT Societies rely on the social infrastructure for proper societal function. When crises emerge, the importance of the social infrastructure magnifies as people often rely on others, both known and unknown, for support. For citizens experiencing a war environment, however, societal trust can be affected and we show how technologies are used to maintain and create social infrastructures for resilience. Through interviews with 45 Iraqi civilians who had lived through the 2 nd Gulf War, we found that people were able to evoke the social infrastructure through technological resources to maintain practices for work, to obtain goods and services, and to receive contextual support. We then theorize properties of social infrastructure that could be developed into affordances for new technologies to promote resilience during crises