The Erosion of Voters’ Trust: How eWOM Shapes perceptions of Mainstream Political Parties in Pakistan?

##plugins.themes.academic_pro.article.main##

Talha Aslam
Saqib Riaz

Abstract

In this technological age, Electronic word of mouth (eWOM) plays crucial role in making public Voter perception. This study examines the effect of eWOM on voter perception of mainstream political parties in Pakistan. This study majorly focuses on the extent that at what level eWOM influneces voter’s attitudes and belief toward these political parties. This study uses arbitration theory to explore how eWOM turns as a casual clash tool, affecting voter trust and perceptions of mainstream political parties in Pakistan. Arbitration theory uses in this study to explore that how eWOM turns as a casual clash tool, effecting voter perceptions of mainstream political parties in Pakistan. Research methodology used in this research is quantitative, data collected from 800 respondents from University of the Punjab, University of Karachi, University of Baluchistan, University of Peshawar, and Quaid-e-Azam University. Data collected through questionnaire is analyzed to identify the patterns and correlations between eWOM exposure and voter perception, with major focus on how eWOM assists as intervening factor the mediation of contradictory political parties. The findings reveal that eWOM plays highly significant role in making perceptions of voter in decision making. This research study highlights that wider exposure to eWOM significantly impacts voter perception.  The research also discloses that eWOM considerably forms voters' perceptions, affecting their attitudes and voting behaviors. eWOM influences political parties' deliberate decisions, guiding them to accept platforms and policies that reflect public emotion.

##plugins.themes.academic_pro.article.details##

How to Cite
[1]
Aslam, T. and Riaz, S. 2024. The Erosion of Voters’ Trust: How eWOM Shapes perceptions of Mainstream Political Parties in Pakistan?. Journal of Policy Research. 10, 2 (Jun. 2024), 759–767. DOI:https://doi.org/10.61506/02.00295.

References

  1. Anstead, N., & O'Loughlin, B. (2015). Social media analysis and public opinion: The 2010 UK general election. Journal of computer-mediated communication, 20(2), 204-220. DOI: https://doi.org/10.1111/jcc4.12102
  2. Akram, H., Yingxiu, Y., Al-Adwan, A. S., & Alkhalifah, A. (2021). Technology Integration in Higher Education During COVID-19: An Assessment of Online Teaching Competencies Through Technological Pedagogical Content Knowledge Model. Frontiers in Psychology, 12, 736522-736522. https://doi.org/10.3389/fpsyg.2021.736522 DOI: https://doi.org/10.3389/fpsyg.2021.736522
  3. Akram, H., Abdelrady, A. H., Al-Adwan, A. S., & Ramzan, M. (2022). Teachers’ perceptions of technology integration in teaching-learning practices: A systematic review. Frontiers in psychology, 13, 920317. DOI: https://doi.org/10.3389/fpsyg.2022.920317
  4. Betz, H.-G. (1994). The losers of globalization or modernization thesis. Comparative Political Studies, 27(3), 263-288. https://doi.org/10.1177/0010414094027003001 DOI: https://doi.org/10.1177/0010414094027003001
  5. Bhadauria, A. S., Shukla, M., Kumar, P., & Dwivedi, N. (2024, February). Forecasting Election Sentiments: Deep Learning vs. Traditional Models. In 2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS) (pp. 1-6). IEEE. DOI: https://doi.org/10.1109/SCEECS61402.2024.10482071
  6. Boler, M., & Davis, E. (2020). Affective politics of digital media (Vol. 155, No. 10). New York: Routledge. DOI: https://doi.org/10.4324/9781003052272
  7. Bushong, B., & Gagnon-Bartsch, T. (2023). Reference dependence and attribution bias: evidence from real-effort experiments. American Economic Journal: Microeconomics, 15(2), 271-308. DOI: https://doi.org/10.1257/mic.20210031
  8. Cheng, J. P., Mendoza-Topaz, C., Howard, G., Chadwick, J., Shvets, E., Cowburn, A. S., ... & Nichols, B. J. (2015). Caveolae protect endothelial cells from membrane rupture during increased cardiac output. The Journal of cell biology, 211(1), 53-61. DOI: https://doi.org/10.1083/jcb.201504042
  9. De Cleen, B., & Stavrakakis, Y. (2017). Hierarchical system that confers authority from bottom to top. Political Studies, 65(3), 624-640. https://doi.org/10.1177/0032321716647116
  10. Dyrberg, T. B. (2003). Hierarchical system that confers authority from bottom to top. Security Dialogue, 34(2), 157-174. https://doi.org/10.1177/0967010603034002004 DOI: https://doi.org/10.1177/0967010603034002004
  11. Enli, G. S., & Skogerbø, E. (2013). Personalized campaigns in party-centred politics: Twitter and Facebook as arenas for political communication. Information, communication & society, 16(5), 757-774. DOI: https://doi.org/10.1080/1369118X.2013.782330
  12. Hassan, T. A., Hollander, S., Van Lent, L., & Tahoun, A. (2019). Firm-level political risk: Measurement and effects. The Quarterly Journal of Economics, 134(4), 2135-2202. DOI: https://doi.org/10.1093/qje/qjz021
  13. Howard, P. N., & Parks, M. R. (2012). Social media and political change: Capacity, constraint, and consequence. Journal of communication, 62(2), 359-362. DOI: https://doi.org/10.1111/j.1460-2466.2012.01626.x
  14. Iyer, P., Yazdanparast, A., & Strutton, D. (2017). Examining the effectiveness of WOM/eWOM communications across age-based cohorts: implications for political marketers. Journal of Consumer Marketing, 34(7), 646-663. DOI: https://doi.org/10.1108/JCM-11-2015-1605
  15. J., Aalberg, Van Aelst, P., Strömbäck, T., Esser, F., De Vreese, C., Matthes, J., ... & Stanyer, J. (2017). Political communication in a high-choice media environment: a challenge for democracy?. Annals of the International Communication Association, 41(1), 3-27. DOI: https://doi.org/10.1080/23808985.2017.1288551
  16. Jagers, J., & Walgrave, S. (2007). Populism as political communication style: An empirical study of political parties' discourse in Belgium. European journal of political research, 46(3), 319-345. DOI: https://doi.org/10.1111/j.1475-6765.2006.00690.x
  17. Kausar, S. W. A., Gul, A., & Hafeez, S. (2023). Exploring intra-party democracy and political finance in Pakistan: The case of effectiveness of mainstream political parties. Asian Journal of Comparative Politics, 8(2), 529-546. DOI: https://doi.org/10.1177/20578911221149422
  18. Kazi, T. (2021). Religious television and pious authority in Pakistan. Indiana University Press. DOI: https://doi.org/10.2307/j.ctv1c3pdxq
  19. Kim, J., & Lee, K. H. (2019). Influence of integration on interactivity in social media luxury brand communities. Journal of Business Research, 99(1), 422-429. DOI: https://doi.org/10.1016/j.jbusres.2017.10.001
  20. Kriesi, H., et al. (2008). The losers of globalization or modernization thesis. Comparative Political Studies, 41(4-5), 513-536. https://doi.org/10.1177/0010414007311065
  21. Larsson, A. O. (2016). Online, all the time? A quantitative assessment of the permanent campaign on Facebook. New media & society, 18(2), 274-292. DOI: https://doi.org/10.1177/1461444814538798
  22. Lee, K. Y., & Choi, H. (2019). Predictors of electronic word-of-mouth behavior on social networking sites in the United States and Korea: Cultural and social relationship variables. Computers in Human Behavior, 94 (2), 9-18. DOI: https://doi.org/10.1016/j.chb.2018.12.025
  23. Lee, M., & Youn, S. (2009). Electronic word of mouth (eWOM) How eWOM platforms influence consumer product judgement. International journal of advertising, 28(3), 473-499. DOI: https://doi.org/10.2501/S0265048709200709
  24. Le-Hoang, P. V. (2020). The effects of Electronic Word of Mouth (eWOM) on the adoption of consumer eWOM information. Independent Journal of Management & Production, 11(6), 1760-1777. DOI: https://doi.org/10.14807/ijmp.v11i6.1152
  25. Li, C., & Bernoff, J. (2019). Harnessing the power of eWOM: A strategic approach to promoting political brands in the digital age. Journal of Political Marketing, 18(3), 272-289.
  26. Li, L., Wang, H., Wang, Y., Chen, M., & Wei, T. (2022). Improving IoT data availability via feedback-and voting-based anomaly imputation. Future generation computer systems, 135 (2), 194-204. DOI: https://doi.org/10.1016/j.future.2022.04.027
  27. Liu, J. (2017). Does Being an Expert Make You More Negative? An Investigation of Subjective Expertise and Electronic Word-of-Mouth Communication (Doctoral dissertation, University of Miami).
  28. Malle, B. F., & Korman, J. (2013). Attribution theory. Oxford University Press. DOI: https://doi.org/10.1093/obo/9780199828340-0096
  29. Ma, D., Akram, H., & Chen, I. H. (2024). Artificial Intelligence in Higher Education: A Cross-Cultural Examination of Students’ Behavioral Intentions and Attitudes. The International Review of Research in Open and Distributed Learning, 25(3), 134-157. DOI: https://doi.org/10.19173/irrodl.v25i3.7703
  30. Marland, A., & DeCillia, B. (2020). Reputation and brand management by political parties: Party vetting of election candidates in Canada. Journal of Nonprofit & Public Sector Marketing, 32(4), 342-363. DOI: https://doi.org/10.1080/10495142.2020.1798857
  31. Milewicz, K., & Milewicz, K. (2014). Manifests. Political Psychology, 35(5), 647-665. https://doi.org/10.1111/pops.12139
  32. Mir, A., Mitts, T., & Staniland, P. (2023). Political coalitions and social media: evidence from Pakistan. Perspectives on Politics, 21(4), 1337-1356. DOI: https://doi.org/10.1017/S1537592722001931
  33. Mouffe, C. (2013). Agonistics: Thinking the world politically. Verso Books, P.236.
  34. Mudde, C., & Kaltwasser, C. R. (2015). Vox populi or vox masculini? Populism and gender in Northern Europe and South America. Patterns of Prejudice, 49(1-2), 16-36. DOI: https://doi.org/10.1080/0031322X.2015.1014197
  35. Mudde, C., & Kaltwasser, C. R. (2017). Society split into two groups: the masses and the governing class. European Journal of Political Research, 56(3), 419-436. https://doi.org/10.1111/1475-6765.12167 DOI: https://doi.org/10.1111/1475-6765.12167
  36. Murtaza, K., & Azhar, M. M. (2020). Agitational politics impacts on national Institutions: A case study of khan’s agitation 2014. Journal of Law & Social Studies (JLSS), 2(1), 22-25. DOI: https://doi.org/10.52279/jlss.02.01.2025
  37. Ostiguy, P. (2009). Hierarchical system that confers authority from bottom to top. Theory and Society, 38(3), 245-272. https://doi.org/10.1007/s11186-009-9104-5
  38. Panizza, U., & Presbitero, A. F. (2014). Public debt and economic growth: is there a causal effect?. Journal of Macroeconomics, 41 (1), 21-41. DOI: https://doi.org/10.1016/j.jmacro.2014.03.009
  39. Chen, Z., & Ramzan, M. (2024). Analyzing the role of Facebook-based e-portfolio on motivation and performance in English as a second language learning. International Journal of English Language and Literature Studies, 13(2), 123-138. DOI: https://doi.org/10.55493/5019.v13i2.5002
  40. Ramzan, M., Javaid, Z. K., & Fatima, M. (2023). Empowering ESL Students: Harnessing the Potential of Social Media to Enhance Academic Motivation in Higher Education. Global Digital & Print Media Review, VI, 224-237. DOI: https://doi.org/10.31703/gdpmr.2023(VI-II).15
  41. Ramzan, M., Bibi, R., & Khunsa, N. (2023). Unraveling the Link between Social Media Usage and Academic Achievement among ESL Learners: A Quantitative Analysis. Global. Educational Studies Review, VIII, 407-421. DOI: https://doi.org/10.31703/gesr.2023(VIII-II).37
  42. Rutter, R., Roper, S., & Lettice, F. (2016). Social media interaction, the university brand and recruitment performance. Journal of Business Research, 69(8), 3096-3104. DOI: https://doi.org/10.1016/j.jbusres.2016.01.025
  43. Scammell, M. (2015). Politics and image: the conceptual value of branding. Journal of political marketing, 14(1-2), 7-18.
  44. Scammell, M. (2015). Politics and image: the conceptual value of branding. Journal of political marketing, 14(1-2), 7-18. DOI: https://doi.org/10.1080/15377857.2014.990829
  45. Schneider, H., & Ferié, F. (2015). How to manage a party brand: empirical perspectives on electoral probability and internal conflict. Journal of Political Marketing, 14(1-2), 64-95.
  46. Schneider, H., & Ferié, F. (2015). How to manage a party brand: empirical perspectives on electoral probability and internal conflict. Journal of Political Marketing, 14(1-2), 64-95. DOI: https://doi.org/10.1080/15377857.2014.990832
  47. Shakil, K., & Yilmaz, I. (2021). Religion and populism in the Global South: Islamist civilisationism of Pakistan’s Imran Khan. Religions, 12(9), 77-92. DOI: https://doi.org/10.3390/rel12090777
  48. Smith, A. (2018). The Impact of Social Media on Political Brand Image: Evidence from the 2016 US Presidential Election. Journal of Information Technology & Politics, 15(2), 97-112.
  49. Tormey, S. (2018). Populism: democracy's Pharmakon?. Policy studies, 39(3), 260-273. DOI: https://doi.org/10.1080/01442872.2018.1475638
  50. Trope, Y. (1986). Identification and inferential processes in dispositional attribution. Psychological review, 93(3), 239-254. DOI: https://doi.org/10.1037//0033-295X.93.3.239
  51. Walter, A. S., & De Vries, C. E. (2009). When the Gloves Come Off: Inter-Party Variation in Negative Campaigning. Available at SSRN 1458326. DOI: https://doi.org/10.2139/ssrn.1458326
  52. Wang, Y., & Yu, C. (2017). Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning. International Journal of Information Management, 37(3), 179-189. DOI: https://doi.org/10.1016/j.ijinfomgt.2015.11.005
  53. Wang, Y., Liu, H., & Zhang, H. (2019). Understanding the Influence of User-Generated Content on Political Brand Image in Social Media. International Journal of Information Management, 49, 13-25.
  54. Wojczewski, T. (2019). Politics of insecurity and fear-mongering. International Political Science Review, 40(1), 95-110. https://doi.org/10.1177/0192512118794607
  55. Wolkenstein, K. (2015). Persistent and widespread occurrence of bioactive quinone pigments during post-Paleozoic crinoid diversification. Proceedings of the National Academy of Sciences, 112(9), 2794-2799. DOI: https://doi.org/10.1073/pnas.1417262112
  56. Zhang, J., & Daugherty, T. (2009). Third‐person effect and social networking: Implications for online marketing and word‐of‐mouth communication. American Journal of Business, 24(2), 53-64. DOI: https://doi.org/10.1108/19355181200900011