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POLITICAL DISCUSSIONS ON SOCIAL MEDIA IN PAKISTAN AND OBSTINATE PARTISANSHIP

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11 Pages : 121-131

http://dx.doi.org/10.31703/gpr.2021(VI-I).11      10.31703/gpr.2021(VI-I).11      Published : Mar 2021

Political Discussions on Social Media in Pakistan and Obstinate Partisanship

Abstract

    With the rise of social media over the last two decades, people have become more polarized and rigid in their views. Social interactions on social media networks are affecting political behaviors and making people obstinate partisans. The term obstinate partisanship was coined by Ardevol-Abreu and Gil de Zuniga (2020) and referred to the blind, unconditional loyalty to a certain political party. The purpose of this study is to examine the prevalence of obstinate partisanship in Pakistani media users who are active consumers of political news and regularly engage in political discussions. This study seeks to investigate how significantly various factors impact obstinate partisanship. The factors studied are media use habits, affiliation with a political party, sociodemographic characteristics including age, gender, education, income, area of residence, and political discussion attributes. The survey data collected from the four major cities of Pakistan and their neighboring rural areas were used. The data revealed that the individuals who engage in political talk online and disagreements during discussions over political issues are more likely to remain unconditionally supportive of party policy and action regardless of their adequacy, the effectiveness of the policy and party performance and this disposition seems to increase with age.

    Offline Political Discussions, Social Media Use, Online Political Discussions, Echo Chambers, and Obstinate Partisanship

    (1) Ifra Iftikhar
    Associate Professor, Lahore Garrison University, Lahore, Punjab, Pakistan.
    (2) Irem Sultana
    Assistant Professor, Government College University, Faisalabad, Punjab, Pakistan.
    (3) Malik Adnan
    Assistant Professor, Department of Media Studies, The Islamia University of Bahawalpur, Punjab, Pakistan.
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References

  • Ardevol-Abreu, A., & Gil de Zúñiga, H. (2020).
  • Bae, S. Y., Kwak, N., & Campbell, S. W. (2013). Who will cross the border? The transition of political discussion into the newly emerged venues. Computers in Human Behavior, 29(5), 2081-2089. doi:10.1016/j.chb.2013.04.006.
  • Bartle, J., & Bellucci, P. (2014). Introduction. In J. B. (Eds.), Political parties and partisanship: Social identity and individual attitudes (pp. 1- 25). New York: NY: Routledge/ECPR
  • Baumann, F., Lorenz-Spreen, P., Sokolov, I. M., & Starnini, M. (2020). Modeling echo chambers and polarization dynamics in social networks. Physical Review Letters, http://arxiv.org/abs/1906.12325.
  • Boutyline, A., & Willer, R. (2016). The Social Structure of Political Echo Chambers:Variation in Ideological Homophily in Online Networks. Political Psychology, xx(xx). doi: 10.1111/pops.12337.
  • Butler, D., & Stokes, D. E. (1974). Electoral change in Britain. London: UK: Macmillan.
  • Cebrian, M., Rahwan, I., & Pentland, A. (2016). Beyond viral. Commun. ACM, 59(4):36-39.
  • Centola, D. (2013). The spread of behavior in an online social network experiment. Science, 329(5996), 1194.
  • Centola, D., & Macy, M. (2007). Complex contagions and the weakness of long ties. American Journal of Sociology, 113(3), 702-34.
  • Chen, T., Shi, J., Yang, J., Cong, G., & Li, G. (2020). Modeling Public Opinion Polarization in Group Behavior by Integrating SIRS-Based Information Diffusion Proces. Complexity, vol. 2020, Article ID 4791527, https://doi.org/10.1155/2020/4791527.
  • Dilliplane, S. (2011). All the news you want to hear: The impact of partisan news exposure on political participation. Public Opinion Quarterly, 75(2), 287-316. doi:10.1093/poq/nfr006.
  • Du, S., & Gregory, S. (2017). The echo chamber effect in Twitter: does community polarization increase? In G. S. In: Cherifi H., Complex Networks & Their Applications V. COMPLEX NETWORKS 2016. Studies in Computational Intelligence, (693). Springer, Cham. https://doi.org/10.1007/978-3-319-50901- 3_30.
  • Dubois, E., & Blank, G. (2018). The echo chamber is overstated: the moderating effect of political interest and diverse media. Information, Communication & Society, 21:5, 729-745, DOI: 10.1080/1369118X.2018.1428656.
  • Gastil, J., Black, L., & Moscovitz, K. (2008). Ideology, attitude change, and deliberation in small face-to face groups. Political Communication, 25(1), 23-46. doi:10.1080/10584600701807836.
  • Gil de Zúñiga, H. (2017). Attributes of interpersonal political discussion as antecedents of cognitive elaboration. Revista Española de Investigaciones Sociológicas,157(1) 65-84. doi:10.5477/cis/reis.157.65.
  • Gonzalez-Bailon, S., Borge-Holthoefer, J., Rivero, A., & Moreno, Y. (2011). The dynamics of protest recruitment through an online network. Scientific Reports, 1, 1-7.
  • Guess, A., Nyhan, B., Lyons, B., & Reifler, J. (2018). Avoiding the Echo Chambers about Echo Chamber:Why selective exposure to like-minded political news is less prevalent than you think. Miami: Knight Foundation
  • Hargittai, E., Gallo, J., & Kane., M. (2008). Cross- ideological discussions among conservative and liberal bloggers. Public Choice, 134(1- 2):67-86.
  • Huckfeldt, R., Mendez, J. M., & Osborn, T. (2004). Disagreement, ambivalence, and engagement: The political consequences of heterogeneous networks. Political Psychology, 25(1), 65-95. https://doi.org/10.1111/j.1467- 9221.2004.00357.x.
  • Jamieson, K., & Cappella, J. (2008). Echo Chamber: Rush Limbaugh and the Conservative Media establishment. London: Oxford UP.
  • Kanji, M., & Archer, K. (2002). The Theories of Voting and Their Applicability in Canada. In J. Everitt, & B. O'Neill, Citizen Politics: Research and Theory in Canadian Political Behaviour (pp. 160-183). Don Mills, Ontario: Oxford University Press.
  • Lemert, J. B. (1984). News context and the elimination of mobilizing information: An experiment. Journalism Quarterly, 61, 243- 249. doi:10.1177/107769908406100201.
  • Mutz, D. (2002a). Cross-cutting social networks: Testing democratic theory in practice. American Political Science Review, 96(1), 111- 126. DOI: https://doi.org/10.1017/S000305540200426 4.
  • Perrella, A. (2010). Overview of Voter Behaviour Theories. In E. H. MacIvor, Election (pp. 221- 249). Toronto: Emond Montgomery Publications.
  • Price, V. C. (2002). Does disagreement contribute to more deliberative opinion? . Political Communication, 19(1), 95-112. https://doi.org/10.1080/105846002317246 506.
  • Romero, D., Meeder, B., & Kleinberg, J. (2011). Differences in the mechanics of information diffusion across topics: Idioms,political hashtags, and complex contagion on Twitter. Proceedings of the 20th International Conference on World Wide Web, (pp. 695- 704).
  • Sîrbu, A., Loreto, V., Servedio, V. D., & Tria, F. (2013). Opinion dynamics with disagreement and modulated information. Journal of Statistical Physics, vol. 151, no. 1-2, pp. 218- 237.
  • Smith, D. R., & Mackie, D. M. (2007). Social psychology. Hove: UK: Psychology Press.
  • Sunstein, C. (2002). The Law of Group Polarization. Journal of Political Philosophy, 10, 175-195.
  • Tsang, A., & Larson, K. (2016). The Echo Chamber: Strategic Voting and Homophily in Social Networks. In K. T. J. Thangarajah (Ed.), Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016) (pp. 368- 375). Singapore: International Foundation for Autonomous Agents and Multiagent Systems www.ifaamas.org
  • Vraga, E. K., Anderson, A. A., Kotcher, J. E., & Maibach, E. W. (2015). Issue-specific engagement: How Facebook contributes to opinion leadership and efficacy on energy and climate issues. . Journal of Information Technology & Politics, 12(2): 200-218. doi:10.1080/19331681.2015.1034910.
  • Yardi, S. b. (2010). Dynamic debates: An analysis of group polarization over time on twitter. Bulletin of Science, Technology and Society, 20:1-8.
  • Yoo, S. W., & Zúñiga, H. G. (2019). The role of heterogeneous political discussion and partisanship on the effects of incidental news exposure online. Journal of Information Technology & Politics, 16, 20-35. https://doi.org/10.1080/19331681.2018.15 61346.
  • Zaller, J. R. (1992). The nature and origins of mass opinion. Cambridge, UK: Cambridge University Press.
  • Zhang, Y., Wang, Y., Chen, T., & Shi, J. (2020). Agent-based modeling approach for group polarization behavior considering conformity and network relationship strength[J]. Concurrency And Computation-Practice & Experience, 32(14), Article ID e5707.

Cite this article

APA

    APA : Iftikhar, I., Sultana, I., & Adnan, M. (2021). Political Discussions on Social Media in Pakistan and Obstinate Partisanship. Global Political Review, VI(I), 121-131. https://doi.org/10.31703/gpr.2021(VI-I).11

CHICAGO

    CHICAGO : Iftikhar, Ifra, Irem Sultana, and Malik Adnan. 2021. "Political Discussions on Social Media in Pakistan and Obstinate Partisanship." Global Political Review, VI (I): 121-131 doi: 10.31703/gpr.2021(VI-I).11

HARVARD

    HARVARD : IFTIKHAR, I., SULTANA, I. & ADNAN, M. 2021. Political Discussions on Social Media in Pakistan and Obstinate Partisanship. Global Political Review, VI, 121-131.

MHRA

    MHRA : Iftikhar, Ifra, Irem Sultana, and Malik Adnan. 2021. "Political Discussions on Social Media in Pakistan and Obstinate Partisanship." Global Political Review, VI: 121-131

MLA

    MLA : Iftikhar, Ifra, Irem Sultana, and Malik Adnan. "Political Discussions on Social Media in Pakistan and Obstinate Partisanship." Global Political Review, VI.I (2021): 121-131 Print.

OXFORD

    OXFORD : Iftikhar, Ifra, Sultana, Irem, and Adnan, Malik (2021), "Political Discussions on Social Media in Pakistan and Obstinate Partisanship", Global Political Review, VI (I), 121-131

TURABIAN

    TURABIAN : Iftikhar, Ifra, Irem Sultana, and Malik Adnan. "Political Discussions on Social Media in Pakistan and Obstinate Partisanship." Global Political Review VI, no. I (2021): 121-131. https://doi.org/10.31703/gpr.2021(VI-I).11