Understanding Community Rivalry on Social Media: A Case Study of Two Footballing Giants

Detection of hate speech in online user generated content has become of increasing importance in recent times. Hate speech can not only be against a particular user but also against a group. Rivalry between two communities with opposing ideologies has been observed to instigate a lot of hate content on social media during controversial events. Moreover, this online hate content has been observed to have power to shape exogenous elements like communal riots [4, 6]. In this paper, we aim to analyze community rivalry in the football domain (Real Madrid FC vs FC Barcelona) based on the hate content exchanged between their supporters and understand how events affect the relationship between these clubs. We further analyze the behavior of key instigators of hate speech in this domain and show how they differ from general users. We also perform a linguistic analysis of the hate content exchanged between rival communities. Overall, our work provides a data-driven analysis of the nuances of online hate speech in the football domain that not only allows a deepened understanding of its social implications, but also its detection.

[1]  Conor Hayes,et al.  Cross-Community Influence in Discussion Fora , 2012, ICWSM.

[2]  Walter Daelemans,et al.  Detection and Fine-Grained Classification of Cyberbullying Events , 2015, RANLP.

[3]  Kush R. Varshney,et al.  The Effect of Extremist Violence on Hateful Speech Online , 2018, ICWSM.

[4]  Gianluca Stringhini,et al.  Hate is not Binary: Studying Abusive Behavior of #GamerGate on Twitter , 2017, HT.

[5]  Jake Harwood,et al.  Intergroup communication : multiple perspectives , 2005 .

[6]  Pete Burnap,et al.  Us and them: identifying cyber hate on Twitter across multiple protected characteristics , 2016, EPJ Data Science.

[7]  Mumit Khan,et al.  Detecting flames and insults in text , 2008 .

[8]  Michael Wiegand,et al.  Inducing a Lexicon of Abusive Words – a Feature-Based Approach , 2018, NAACL.

[9]  Joel R. Tetreault,et al.  Abusive Language Detection in Online User Content , 2016, WWW.

[10]  Henry Lieberman,et al.  Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying , 2012, TIIS.

[11]  Mai ElSherief,et al.  Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media , 2018, ICWSM.

[12]  Gianluca Stringhini,et al.  Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior , 2018, ICWSM.

[13]  Steven L. Scott,et al.  Inferring causal impact using Bayesian structural time-series models , 2015, 1506.00356.

[14]  Jure Leskovec,et al.  Community Interaction and Conflict on the Web , 2018, WWW.

[15]  Zeynep Tufekci,et al.  Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls , 2014, ICWSM.

[16]  Jean-Louis Barsoux,et al.  How to Become a Better Leader , 2012 .

[17]  Ingmar Weber,et al.  Automated Hate Speech Detection and the Problem of Offensive Language , 2017, ICWSM.

[18]  Xiaocheng Feng,et al.  Target-Dependent Sentiment Classification with Long Short Term Memory , 2015, ArXiv.

[19]  Eric P. Xing,et al.  Sparse Additive Generative Models of Text , 2011, ICML.

[20]  Muhammad Imran,et al.  Summarizing Situational Tweets in Crisis Scenario , 2016, HT.

[21]  Xiaocheng Feng,et al.  Effective LSTMs for Target-Dependent Sentiment Classification , 2015, COLING.

[22]  Giovanni Vigna,et al.  Peer to Peer Hate: Hate Speech Instigators and Their Targets , 2018, ICWSM.

[23]  Njagi Dennis Gitari,et al.  A Lexicon-based Approach for Hate Speech Detection , 2015, MUE 2015.

[24]  Yuzhou Wang,et al.  Locate the Hate: Detecting Tweets against Blacks , 2013, AAAI.

[25]  H. Tajfel,et al.  An integrative theory of intergroup conflict. , 1979 .

[26]  Fabrício Benevenuto,et al.  Analyzing the Targets of Hate in Online Social Media , 2016, ICWSM.

[27]  Ryan L. Boyd,et al.  The Development and Psychometric Properties of LIWC2015 , 2015 .

[28]  Dirk Hovy,et al.  Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter , 2016, NAACL.

[29]  S. Rothmann,et al.  THE BIG FIVE PERSONALITY DIMENSIONS AND JOB PERFORMANCE , 2003 .

[30]  Vasudeva Varma,et al.  Deep Learning for Hate Speech Detection in Tweets , 2017, WWW.

[31]  Adam Michael Edwards,et al.  Detecting tension in online communities with computational Twitter analysis , 2015 .

[32]  Huan Liu,et al.  Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose , 2013, ICWSM.

[33]  Gianluca Stringhini,et al.  Mean Birds: Detecting Aggression and Bullying on Twitter , 2017, WebSci.

[34]  M. Sherif.  Group Conflict and Co-operation: Their Social Psychology , 1967 .

[35]  Joel R. Tetreault,et al.  Do Characters Abuse More Than Words? , 2016, SIGDIAL Conference.