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Us Vs. Them – Understanding the Impact of Homophily in Political Discussions on Twitter

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Human-Computer Interaction – INTERACT 2021 (INTERACT 2021)

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Abstract

Analysing homophily, i.e. people’s tendency to associate with others with similar social attributes, can help us unravel and better understand user behaviour in social media. In our work, we analyse the impact of homophily in discussions regarding the Citizenship Amendment Act (CAA) on Twitter. The Indian Government enacted CAA to provide relaxation in the citizenship process to religious minorities in three neighbouring countries. While it was lauded by many, it also fuelled backlash amongst some Indian citizens, resulting in the emergence of two distinctive political dispositions regarding this matter. We collected 78,004 Tweets, including 11,794 original Tweets during a period of two weeks shortly after the ruling, and examined ways of potentially reducing homophily and therefore minimise the presence of echo chambers. In particular, we investigated users’ political dispositions and expressed sentiment, and how these two social attributes influence homophilic social ties and interactions. Further, we discuss how our findings can be used in social networks to allow people with diverse viewpoints and emotional attitudes to interact with each other in a positive and constructive manner.

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Notes

  1. 1.

    https://www.statista.com/statistics/242606/number-of-active-twitter-users-in-selected-countries.

  2. 2.

    https://radimrehurek.com/gensim/.

References

  1. Aiello, L.M., Barrat, A., Schifanella, R., Cattuto, C., Markines, B., Menczer, F.: Friendship prediction and homophily in social media. ACM Trans. Web (2012). https://doi.org/10.1145/2180861.2180866

    Article  Google Scholar 

  2. Ausserhofer, J., Maireder, A.: National politics on Twitter. Inf. Commun. Soc. 16(3), 291–314 (2013). https://doi.org/10.1080/1369118X.2012.756050

  3. Baek, Y.M., Wojcieszak, M., Delli Carpini, M.X.: Online versus face-to-face deliberation: who? Why? What? With what effects? New Media Soc. (2012). https://doi.org/10.1177/1461444811413191

    Article  Google Scholar 

  4. Barbera, P.: Birds of the same feather tweet together. Bayesian ideal point estimation using Twitter data. SSRN Electron. J. (2013). https://doi.org/10.2139/ssrn.2108098

    Article  Google Scholar 

  5. Barberá, P.: How Social media reduces mass political polarization. Evidence from Germany, Spain, and the U.S. LXXIII Congress of the Midwest Political Science Association (2014)

    Google Scholar 

  6. Bekafigo, M.A., McBride, A.: Who tweets about politics? Soc. Sci. Comput. Rev. 31(5), 625–643 (2013). https://doi.org/10.1177/0894439313490405

  7. Bisgin, H., Agarwal, N., Xu, X.: A study of homophily on social media. World Wide Web (2012). https://doi.org/10.1007/s11280-011-0143-3

    Article  Google Scholar 

  8. Bishop, B., Cushing, R.G.: The Big Sort: Why the Clustering of Like-Minded America is Tearing Us Apart. Mariner Books (2009)

    Google Scholar 

  9. Blei, D.M.: Probabilistic topic models. Commun. ACM (2012). https://doi.org/10.1145/2133806.2133826

    Article  Google Scholar 

  10. Blevins, J.L., Lee, J.J., McCabe, E.E., Edgerton, E.: Tweeting for social justice in #Ferguson: affective discourse in Twitter hashtags. New Media Soc. (2019). https://doi.org/10.1177/1461444819827030

    Article  Google Scholar 

  11. Bonilla, Y., Rosa, J.: #Ferguson: digital protest, hashtag ethnography, and the racial politics of social media in the United States. Am. Ethnol. (2015). https://doi.org/10.1111/amet.12112

    Article  Google Scholar 

  12. Boxell, L., Gentzkow, M., Shapiro, J.: Is the internet causing political polarization? Evidence from demographics. Nat. Bureau Econ. Res. (2017). https://doi.org/10.3386/w23258

    Article  Google Scholar 

  13. Bruns, A., Burgess, J.: The use of twitter hashtags in the formation of ad hoc publics. In: European Consortium for Political Research Conference, Reykjavík, 25–27 August 2011 (2011)

    Google Scholar 

  14. Bruns, A., Moon, B., Paul, A., Münch, F.: Towards a typology of hashtag publics: a large-scale comparative study of user engagement across trending topics. Commun. Res. Pract. (2016). https://doi.org/10.1080/22041451.2016.1155328

    Article  Google Scholar 

  15. Caetano, J.A., Lima, H.S., Santos, M.F., Marques-Neto, H.T.: Using sentiment analysis to define twitter political users’ classes and their homophily during the 2016 American presidential election. J. Internet Serv. Appl. (2018). https://doi.org/10.1186/s13174-018-0089-0

    Article  Google Scholar 

  16. Chen, J., Liu, Y., Zou, M.: User emotion for modeling retweeting behaviors. Neural Netw. (2017). https://doi.org/10.1016/j.neunet.2017.08.006

    Article  Google Scholar 

  17. CNN: Citizenship Amendment Bill explained: India’s controversial bill that excludes Muslims. https://edition.cnn.com/2019/12/11/asia/india-citizenship-amendment-bill-intl-hnk/index.html

  18. Coleman, J.: Relational analysis: the study of social organizations with survey methods. Human Organization (1958). https://doi.org/10.17730/humo.17.4.q5604m676260q8n7

  19. Colleoni, E., Rozza, A., Arvidsson, A.: Echo chamber or public sphere? predicting political orientation and measuring political homophily in Twitter using big data. J. Commun. (2014). https://doi.org/10.1111/jcom.12084

    Article  Google Scholar 

  20. Conover, M., Ratkiewicz, J., Francisco, M.: Political polarization on Twitter. ICWSM (2011). https://doi.org/10.1021/ja202932e

    Article  Google Scholar 

  21. Currarini, S., Jackson, M.O., Pin, P.: An economic model of friendship: homophily, minorities, and segregation. Econometrica 77(4), 1003–1045 (2009). https://doi.org/10.3982/ECTA7528

    Article  MathSciNet  MATH  Google Scholar 

  22. De Choudhury, M., Sundaram, H., John, A., Seligmann, D.D., Kelliher, A.: “Birds of a Feather”: does user homophily impact information diffusion in social media? (2010). http://arxiv.org/abs/1006.1702

  23. De Salve, A., Guidi, B., Ricci, L., Mori, P.: Discovering homophily in online social networks. Mob. Netw. Appl. 23(6), 1715–1726 (12 (2018). https://doi.org/10.1007/s11036-018-1067-2

  24. Endres, D.M., Schindelin, J.E.: A new metric for probability distributions (2003). https://doi.org/10.1109/TIT.2003.813506

  25. Enli, G.S., Skogerbø, E.: Personalized campaigns in party-centred politics. Inf. Commun. Soc. 16(5), 757–774 (6 (2013). https://doi.org/10.1080/1369118X.2013.782330

  26. Fiore, A.T., Donath, J.S.: Homophily in online dating: when do you like someone like yourself? In: Conference on Human Factors in Computing Systems - Proceedings (2005). https://doi.org/10.1145/1056808.1056919

  27. Fraisier, O., Cabanac, G., Pitarch, Y., Besançon, R., Boughanem, M.: Uncovering like-minded political communities on Twitter. In: ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval (2017). https://doi.org/10.1145/3121050.3121091

  28. Gerbaudo, P.: Social media and populism: an elective affinity? Media Cult. Soc. 40(5), 745–753 (2018). https://doi.org/10.1177/0163443718772192

    Article  Google Scholar 

  29. Gerber, E.R., Henry, A.D., Lubell, M.: Political homophily and collaboration in regional planning networks. Am. J. Polit. Sci. (2013). https://doi.org/10.1111/ajps.12011

    Article  Google Scholar 

  30. Gimpel, J.G., Hui, I.S.: Seeking politically compatible neighbors? The role of neighborhood partisan composition in residential sorting. Polit. Geogr. (2015). https://doi.org/10.1016/j.polgeo.2014.11.003

    Article  Google Scholar 

  31. Gonçalves, B., Perra, N., Vespignani, A.: Modeling users’ activity on Twitter networks: validation of Dunbar’s number. PLoS ONE (2011). https://doi.org/10.1371/journal.pone.0022656

    Article  Google Scholar 

  32. Goncalves, J., Kostakos, V., Venkatanathan, J.: Narrowcasting in social media: effects and perceptions. In: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013 (2013). https://doi.org/10.1145/2492517.2492570

  33. Goncalves, J., Liu, Y., Xiao, B., Chaudhry, S., Hosio, S., Kostakos, V.: Increasing the reach of government social media: A case study in modeling government-citizen interaction on Facebook. Policy Internet (2015). https://doi.org/10.1002/poi3.81

    Article  Google Scholar 

  34. Graells-Garrido, E., Lalmas, M., Quercia, D.: Data portraits: connecting people of opposing views (2013). https://arxiv.org/abs/1311.4658

  35. Gruzd, A., Wellman, B., Takhteyev, Y.: Imagining Twitter as an imagined community. Am. Behav. Sci. (2011). https://doi.org/10.1177/0002764211409378

    Article  Google Scholar 

  36. Guerra, P.C., Souza, R.C., Assunção, R.M., Meira, W.: Antagonism also flows through retweets: the impact of out-of-context quotes in opinion polarization analysis. In: Proceedings of the 11th International Conference on Web and Social Media, ICWSM 2017 (2017)

    Google Scholar 

  37. Hettiachchi, D., Goncalves, J.: Towards effective crowd-powered online content moderation. In: Proceedings of the 31st Australian Conference on Human-Computer-Interaction, pp. 342–346. ACM (2019). https://doi.org/10.1145/3369457.3369491

  38. Himelboim, I., Cameron, K., Sweetser, K.D., Danelo, M., West, K.: Valence-based homophily on Twitter: network analysis of emotions and political talk in the 2012 presidential election. New Media Soc. (2016). https://doi.org/10.1177/1461444814555096

    Article  Google Scholar 

  39. Himelboim, I., Mccreery, S., Smith, M.: Birds of a feather tweet together: integrating network and content analyses to examine cross-ideology exposure on Twitter. J. Comput. Mediat. Commun. (2013). https://doi.org/10.1111/jcc4.12001

    Article  Google Scholar 

  40. Himelboim, I., Smith, M., Shneiderman, B.: Tweeting apart: applying network analysis to detect selective exposure clusters in Twitter. Commun. Methods Meas. (2013). https://doi.org/10.1080/19312458.2013.813922

    Article  Google Scholar 

  41. Hindustan Times: #IndiaDoesNotSupportCAA takes Twitter by storm. https://www.hindustantimes.com/india-news/indiadoesnotsupportcaa-takes-twitter-by-storm/story-SwRmAoj4tEh2DY9OUK0mBJ.html

  42. Huber, G.A., Malhotra, N.: Political homophily in social relationships: evidence from online dating behavior. J. Polit. (2017). https://doi.org/10.1086/687533

    Article  Google Scholar 

  43. Huckfeldt, R.R., Sprague, J.: Citizens, politics and social. Communication (1995). https://doi.org/10.1017/cbo9780511664113

    Article  Google Scholar 

  44. Hui, I.: Who is your preferred neighbor? Partisan residential preferences and neighborhood satisfaction. Am. Politics Res. (2013). https://doi.org/10.1177/1532673X13482573

    Article  Google Scholar 

  45. Hutto, C.J., Gilbert, E.: VADER: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014 (2014)

    Google Scholar 

  46. Ince, J., Rojas, F., Davis, C.A.: The social media response to Black Lives Matter: how Twitter users interact with Black Lives Matter through hashtag use. Ethn. Racial Stud. (2017). https://doi.org/10.1080/01419870.2017.1334931

    Article  Google Scholar 

  47. India Today: Everything you wanted to know about the CAA and NRC. https://www.indiatoday.in/india-today-insight/story/everything-you-wanted-to-know-about-the-caa-and-nrc-1630771-2019-12-23

  48. Iyengar, S., Hahn, K.S.: Red media, blue media: evidence of ideological selectivity in media use. J. Commun. (2009). https://doi.org/10.1111/j.1460-2466.2008.01402.x

    Article  Google Scholar 

  49. Iyengar, S., Sood, G., Lelkes, Y.: Affect, not ideology: a social identity perspective on polarization (2012). https://doi.org/10.1093/poq/nfs038

  50. Iyengar, S., Westwood, S.J.: Fear and loathing across party lines: new evidence on group polarization. Am. J. Polit. Sci. (2015). https://doi.org/10.1111/ajps.12152

    Article  Google Scholar 

  51. Jackson, S.J., Foucault Welles, B.: Hijacking #myNYPD: social media dissent and networked Counterpublics. J. Commun. (2015). https://doi.org/10.1111/jcom.12185

    Article  Google Scholar 

  52. Kang, J.H., Lerman, K.: Using lists to measure homophily on twitter. In: AAAI Workshop - Technical Report (2012)

    Google Scholar 

  53. Lewicka, M.: Confirmation bias. In: Kofta, M., Weary, G., Sedek, G. (eds.) Personal Control in Action, pp. 233–258. Springer, Boston (1998). https://doi.org/10.1007/978-1-4757-2901-6_9

  54. Liu, Y., Venkatanathan, J., Goncalves, J., Karapanos, E., Kostakos, V.: Modeling what friendship patterns on Facebook reveal about personality and social capital. ACM Trans. Comput. Hum. Interact. 21(3),(2014). https://doi.org/10.1145/2617572

  55. Lovejoy, K., Waters, R.D., Saxton, G.D.: Engaging stakeholders through Twitter: how nonprofit organizations are getting more out of 140 characters or less. Public Relat. Rev. (2012). https://doi.org/10.1016/j.pubrev.2012.01.005

    Article  Google Scholar 

  56. Madden, M., Smith, A.: Reputation management and social media (2010)

    Google Scholar 

  57. Manikonda, L., Beigi, G., Liu, H., Kambhampati, S.: Twitter for sparking a movement, reddit for sharing the moment: #Metoo through the lens of social media (2018)

    Google Scholar 

  58. Mason, L.: Uncivil Agreement: How Politics Became Our Identity. University of Chicago Press (2018)

    Google Scholar 

  59. McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a feather: homophily in social networks. Ann. Rev. Sociol. (2001). https://doi.org/10.1146/annurev.soc.27.1.415

    Article  Google Scholar 

  60. Mehrotra, R., Sanner, S., Buntine, W., Xie, L.: Improving LDA topic models for microblogs via tweet pooling and automatic labeling. In: Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval (2013). https://doi.org/10.1145/2484028.2484166

  61. Mummolo, J., Nall, C.: Why partisans do not sort: the constraints on political segregation. J. Polit. (2017). https://doi.org/10.1086/687569

    Article  Google Scholar 

  62. Nagulendra, S., Vassileva, J.: Understanding and controlling the filter bubble through interactive visualization: a user study. In: HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media (2014). https://doi.org/10.1145/2631775.2631811

  63. NPR: India Passes Controversial Citizenship Bill That Would Exclude Muslims. https://www.npr.org/2019/12/11/787220640/india-passes-controversial-citizenship-bill-that-would-exclude-muslims

  64. Nyhan, B., Reifler, J.: When corrections fail: the persistence of political misperceptions. Polit. Behav. (2010). https://doi.org/10.1007/s11109-010-9112-2

    Article  Google Scholar 

  65. Pariser, E.: Filter Bubble (2012). https://doi.org/10.3139/9783446431164

  66. Park, C.S.: Does Twitter motivate involvement in politics? Tweeting, opinion leadership, and political engagement. Comput. Hum. Behav. (2013). https://doi.org/10.1016/j.chb.2013.01.044

    Article  Google Scholar 

  67. Pew Research Center: The Partisan Divide on Political Values Grows Even Wider. Technical report (2017)

    Google Scholar 

  68. Rader, E., Gray, R.: Understanding user beliefs about algorithmic curation in the Facebook news feed. In: Conference on Human Factors in Computing Systems - Proceedings (2015). https://doi.org/10.1145/2702123.2702174

  69. Ranganath, S., Hu, X., Tang, J., Liu, H.: Understanding and identifying advocates for political campaigns on social media. In: WSDM 2016 - Proceedings of the 9th ACM International Conference on Web Search and Data Mining (2016). https://doi.org/10.1145/2835776.2835807

  70. Small, T.A.: What the hashtag? Inf. Commun. Soc. 14(6), 872–895 (2011). https://doi.org/10.1080/1369118X.2011.554572

  71. Stieglitz, S., Dang-Xuan, L.: Emotions and information diffusion in social media - sentiment of microblogs and sharing behavior. J. Manag. Inf. Syst. (2013). https://doi.org/10.2753/MIS0742-1222290408

    Article  Google Scholar 

  72. Sunstein, C.R.: Republic.com 2.0 (2009). https://doi.org/10.5860/choice.45-5264

  73. Tajfel, H., Turner, J.: An Integrative Theory of Inter-group Conflict. In: The social psychology of intergroup relations. Oxford University Press (1979)

    Google Scholar 

  74. The Financial Express: ‘India Supports CAA’ : PM Modi launches Twitter campaign to support Citizenship Act. https://www.financialexpress.com/india-news/india-supports-caa-pm-modi-launches-twitter-campaign-to-support-citizenship-act/1807380/

  75. Tsugawa, S., Ohsaki, H.: On the relation between message sentiment and its virality on social media. Soc. Netw. Anal. Min. (2017). https://doi.org/10.1007/s13278-017-0439-0

    Article  Google Scholar 

  76. Venkatanathan, J., Karapanos, E., Kostakos, V., Gonçalves, J.: Network, personality and social capital. In: ACM Web Science Conference, WebSci 2012, pp. 326–329. ACM (2012). https://doi.org/10.1145/2380718.2380760

  77. Venkatanathan, J., Karapanos, E., Kostakos, V., Gonçalves, J.: A network science approach to modelling and predicting empathy. In: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013, pp. 1395–1400. ACM (2013). https://doi.org/10.1145/2492517.2500295

  78. Wang, F., Orton, K., Wagenseller, P., Xu, K.: Towards understanding community interests with topic modeling. IEEE Access (2018). https://doi.org/10.1109/ACCESS.2018.2815904

    Article  Google Scholar 

  79. Williams, H.T., McMurray, J.R., Kurz, T., Hugo Lambert, F.: Network analysis reveals open forums and echo chambers in social media discussions of climate change. Glob. Environ. Chang. (2015). https://doi.org/10.1016/j.gloenvcha.2015.03.006

    Article  Google Scholar 

  80. Xiong, Y., Cho, M., Boatwright, B.: Hashtag activism and message frames among social movement organizations: semantic network analysis and thematic analysis of Twitter during the #MeToo movement. Public Relat. Rev. (2019). https://doi.org/10.1016/j.pubrev.2018.10.014

    Article  Google Scholar 

  81. Xu, S., Zhou, A.: Hashtag homophily in twitter network: examining a controversial cause-related marketing campaign. Comput. Hum. Behav. (2020). https://doi.org/10.1016/j.chb.2019.08.006

    Article  Google Scholar 

  82. Xu, W.W., Sang, Y., Blasiola, S., Park, H.W.: Predicting opinion leaders in Twitter activism networks: the case of the Wisconsin recall election. Am. Behav. Sci. (2014). https://doi.org/10.1177/0002764214527091

    Article  Google Scholar 

  83. Yang, G.: Narrative agency in hashtag activism: the case of #blacklivesmatter (2016). https://doi.org/10.17645/mac.v4i4.692

  84. Yu, B., Kaufmann, S., Diermeier, D.: Exploring the characteristics of opinion expressions for political opinion classification. In: Proceedings of the 2008 International Conference on Digital Government Research (2008)

    Google Scholar 

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Authors and Affiliations

  1. School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia

    Danula Hettiachchi, Tanay Arora & Jorge Goncalves

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  1. Danula Hettiachchi
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  2. Tanay Arora
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Correspondence to Danula Hettiachchi .

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Editors and Affiliations

  1. Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy

    Carmelo Ardito

  2. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Rosa Lanzilotti

  3. Computer Science Department, University of Pisa, Pisa, Italy

    Alessio Malizia

  4. Department of Computer Science, University of York, York, UK

    Helen Petrie

  5. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Antonio Piccinno

  6. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Giuseppe Desolda

  7. Microsoft Research, Redmond, WA, USA

    Kori Inkpen

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Hettiachchi, D., Arora, T., Goncalves, J. (2021). Us Vs. Them – Understanding the Impact of Homophily in Political Discussions on Twitter. In: Ardito, C., et al. Human-Computer Interaction – INTERACT 2021. INTERACT 2021. Lecture Notes in Computer Science(), vol 12935. Springer, Cham. https://doi.org/10.1007/978-3-030-85610-6_27

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