Political and Racial Polarization and the Intersection with Social Work

Immediately following the 2016 presidential election, fifty-one people were given an online survey based on several political topics: race, party identification, voting choice, and opinions on the state of political and racial polarization in the United States. Given the role of the media to shape public opinion, an option was given for the survey respondents to give their opinion on controversial articles that were selected. Before conducting the survey, I believed that the respondents would agree that the United States is polarized, but agree with the message that the controversial articles were giving off. The clear majority of respondents agreed that the United States is becoming more politically and racially divided. I then used their responses for a discussion-based presentation and connected the issue of polarization to social work; social workers must validate the concerns of their clients following the election, but must also teach resiliency.Ope

Public discourse and news consumption on online social media: A quantitative, cross-platform analysis of the Italian Referendum

The rising attention to the spreading of fake news and unsubstantiated rumors on online social media and the pivotal role played by confirmation bias led researchers to investigate different aspects of the phenomenon. Experimental evidence showed that confirmatory information gets accepted even if containing deliberately false claims while dissenting information is mainly ignored or might even increase group polarization. It seems reasonable that, to address misinformation problem properly, we have to understand the main determinants behind content consumption and the emergence of narratives on online social media. In this paper we address such a challenge by focusing on the discussion around the Italian Constitutional Referendum by conducting a quantitative, cross-platform analysis on both Facebook public pages and Twitter accounts. We observe the spontaneous emergence of well-separated communities on both platforms. Such a segregation is completely spontaneous, since no categorization of contents was performed a priori. By exploring the dynamics behind the discussion, we find that users tend to restrict their attention to a specific set of Facebook pages/Twitter accounts. Finally, taking advantage of automatic topic extraction and sentiment analysis techniques, we are able to identify the most controversial topics inside and across both platforms. We measure the distance between how a certain topic is presented in the posts/tweets and the related emotional response of users. Our results provide interesting insights for the understanding of the evolution of the core narratives behind different echo chambers and for the early detection of massive viral phenomena around false claims

The Effect of Collective Attention on Controversial Debates on Social Media

We study the evolution of long-lived controversial debates as manifested on Twitter from 2011 to 2016. Specifically, we explore how the structure of interactions and content of discussion varies with the level of collective attention, as evidenced by the number of users discussing a topic. Spikes in the volume of users typically correspond to external events that increase the public attention on the topic -- as, for instance, discussions about `gun control' often erupt after a mass shooting. This work is the first to study the dynamic evolution of polarized online debates at such scale. By employing a wide array of network and content analysis measures, we find consistent evidence that increased collective attention is associated with increased network polarization and network concentration within each side of the debate; and overall more uniform lexicon usage across all users.Comment: accepted at ACM WebScience 201

Sectarianism and state funded schooling in Scotland. A critical response to the final report of the Advisory Group on Tackling Sectarianism in Scotland

The Scottish Government has recently invested considerable energy and resource into tackling sectarianism in Scotland. They have commissioned reviews of existing research, commissioned new research and funded community based projects. They also appointed an independent Advisory Group in 2012 to investigate the scope of sectarianism and provide some recommendations on how to address sectarianism. This article is focused on the Final Report of the Advisory Group on Tackling Sectarianism in Scotland - April 2015 (Scottish Government, 2015a) and the key statements in this Final Report that refer to state funded school education. The article argues that there is much to commend in the Final Report and provides a critical examination of the discussion of the relationship between school education and sectarianism and the contribution of school education to anti-sectarian activities and education

A Motif-based Approach for Identifying Controversy

Among the topics discussed in Social Media, some lead to controversy. A number of recent studies have focused on the problem of identifying controversy in social media mostly based on the analysis of textual content or rely on global network structure. Such approaches have strong limitations due to the difficulty of understanding natural language, and of investigating the global network structure. In this work we show that it is possible to detect controversy in social media by exploiting network motifs, i.e., local patterns of user interaction. The proposed approach allows for a language-independent and fine- grained and efficient-to-compute analysis of user discussions and their evolution over time. The supervised model exploiting motif patterns can achieve 85% accuracy, with an improvement of 7% compared to baseline structural, propagation-based and temporal network features

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17

All Together Now: Collaboration and Innovation for Youth Engagement

Each new generation must become active, informed, responsible, and effective citizens. As a teacher we surveyed for this report said, civic education "is essential if we are to continue as a free democratic society. Not to educate the next generation will ensure the destruction of our American way of life as we know it."Data show that many young Americans are reasonably well informed and active. For instance, 45% of citizens between the ages of 18 and 29 voted in the 2012 election. In a national survey conducted for this Commission, 76% of people under the age of 25 who voted could correctly answer at least one (out of two) factual questions about where the presidential candidates stood on a campaign issue and state their own opinion on that issue.On the other hand, more than half of young people did not vote. And on some topics, most young people were misinformed. A majority (51.2%) of under 25-year olds believed that the federal government spends more on foreign aid than on Social Security, when in fact Social Security costs about 20 times more. (Older adults have also been found to be misinformed on similar topics.) Our research, like many other studies, finds that young people from disadvantaged backgrounds are far less likely to be informed and to vote.These shortcomings cannot be attributed to the schools alone, since families, friends, political campaigns, election officials, the mass media, social media, and community-based organizations are among the other important influences on young people. In fact, our research shows that while schools matter, civic education must be a shared responsibility.The outcomes are acceptable only when all the relevant institutions invite, support, and educate young people to engage in politics and civic life. Improving the quality and quantity of youth participation will require new collaborations; for example, state election officials and schools should work together to make voting procedures understandable and to educate students about voting rules