Finding Intermediary Topics Between People of Opposing Views: A Case Study

In micro-blogging platforms, people can connect with others and have conversations on a wide variety of topics. However, because of homophily and selective exposure, users tend to connect with like-minded people and only read agreeable information. Motivated by this scenario, in this paper we study the diversity of intermediary topics, which are latent topics estimated from user generated content. These topics can be used as features in recommender systems aimed at introducing people of diverse political viewpoints. We conducted a case study on Twitter, considering the debate about a sensitive issue in Chile, where we quantified homophilic behavior in terms of political discussion and then we evaluated the diversity of intermediary topics in terms of political stances of users.

[1]  R. M. Alvarez.  Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data , 2014 .

[2]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[3]  Michael J. Muller,et al.  Make new friends, but keep the old: recommending people on social networking sites , 2009, CHI.

[4]  Ricardo Baeza-Yates,et al.  Modern Information Retrieval - the concepts and technology behind search, Second edition , 2011 .

[5]  Qi He,et al.  TwitterRank: finding topic-sensitive influential twitterers , 2010, WSDM '10.

[6]  Derek L. Hansen,et al.  Computing political preference among twitter followers , 2011, CHI.

[7]  M. Zelen,et al.  Rethinking centrality: Methods and examples☆ , 1989 .

[8]  L. Jost.  Entropy and diversity , 2006 .

[9]  Wendy Liu,et al.  Homophily and Latent Attribute Inference: Inferring Latent Attributes of Twitter Users from Neighbors , 2012, ICWSM.

[10]  Daniele Quercia,et al.  The Social World of Twitter: Topics, Geography, and Emotions , 2012, ICWSM.

[11]  Mounia Lalmas,et al.  Balancing diversity to counter-measure geographical centralization in microblogging platforms , 2014, HT.

[12]  Daniele Quercia,et al.  People of opposing views can share common interests , 2014, WWW.

[13]  Eli Pariser,et al.  The Filter Bubble: What the Internet Is Hiding from You , 2011 .

[14]  Antoine Boutet,et al.  What’s in Twitter, I know what parties are popular and who you are supporting now! , 2013, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[15]  John Hannon,et al.  Recommending twitter users to follow using content and collaborative filtering approaches , 2010, RecSys '10.

[16]  D. Boyd,et al.  Dynamic Debates: An Analysis of Group Polarization Over Time on Twitter , 2010 .

[17]  Daniele Quercia,et al.  Why individuals seek diverse opinions (or why they don't) , 2013, WebSci.

[18]  Jacob Ratkiewicz,et al.  Political Polarization on Twitter , 2011, ICWSM.

[19]  Susan T. Dumais,et al.  Characterizing Microblogs with Topic Models , 2010, ICWSM.

[20]  María Jesús Ibáñez Canelo.  "El Control De Los Cuerpos De Las Mujeres Es Algo Medular En La Política Patriarcal Capitalista" Entrevista a Soledad Rojas, Feminista Chilena , 2014 .

[21]  Peter A. Gloor,et al.  Tracking the 2011 Student-led Collective Movement in Chile through Social Media Use , 2012, ArXiv.

[22]  L. Festinger,et al.  A Theory of Cognitive Dissonance , 2017 .

[23]  Jacob Ratkiewicz,et al.  Predicting the Political Alignment of Twitter Users , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[24]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[25]  Ulrik Brandes,et al.  Centrality Measures Based on Current Flow , 2005, STACS.

[26]  Ana-Maria Popescu,et al.  Democrats, republicans and starbucks afficionados: user classification in twitter , 2011, KDD.

[27]  S. Asch.  Forming impressions of personality. , 1946, Journal of Abnormal Psychology.

[28]  Bonnie L Shepard,et al.  Abortion Policies and Practices in Chile: Ambiguities and Dilemmas , 2007, Reproductive health matters.