THE PERCEPTION OF TWITTER CREDIBILITY AND YOUNG ADULTS’ LOYALTY IN SHAH ALAM
DOI:
https://doi.org/10.55197/qjssh.v7i5.1431Abstract
Social media has become an important channel for political information and discussion among young adults in Malaysia. This study examines perceptions of Twitter credibility and their relationship with loyalty among young adults in Shah Alam, Selangor. Drawing on the Source Credibility Model, the study considers perceived expertise, trustworthiness, reputation and promotional incentives as dimensions associated with Twitter credibility, alongside perceived loyalty and information sharing. A quantitative, cross-sectional questionnaire was distributed online to young adults aged 18–25 in Shah Alam. The study reports a sample of 382 respondents drawn from a population estimate of 74,366 young adults. Responses were collected using a five-point Likert-scale instrument organised around seven constructs. The analysis examined respondents’ demographic characteristics, descriptive measures and relationships between the constructs. The reported correlations between credibility and its proposed antecedents were positive: perceived expertise (0.56), trustworthiness (0.65), reputation (0.60) and promotional incentives (0.61). Twitter credibility was also positively associated with perceived loyalty (0.59) and verified information sharing (0.61). These findings suggest that trustworthiness and the reputation of information sources are relevant to how young adults assess political content on Twitter, while perceived credibility is related to continued engagement and information-sharing practices. The study contributes to discussions of social-media credibility and political information use in a Malaysian urban setting. It also highlights the importance of helping young users evaluate source reliability, distinguish account verification from factual accuracy and approach political news critically. Given the cross-sectional self-report design and the geographic and age restrictions, the findings should be interpreted as associations rather than causal effects, and their generalisability beyond the sampled respondents remains limited.
References
[1] Abbasi, A.Z., Tsiotsou, R.H., Hussain, K., Rather, R.A., Ting, D.H. (2023): Investigating the impact of social media images’ value, consumer engagement, and involvement on eWOM of a tourism destination: A transmittal mediation approach. – Journal of Retailing and Consumer Services 71: 12p.
[2] Ante, L. (2023): How Elon Musk's Twitter activity moves cryptocurrency markets. – Technological Forecasting and Social Change 186: 12p.
[3] Barnoy, A., Reich, Z. (2020): Trusting others: A Pareto distribution of source and message credibility among news reporters. – Communication Research 49(2): 196-220.
[4] Chopra, A., Avhad, V., Jaju, S. (2020): Influencer marketing: An exploratory study to identify antecedents of consumer behavior of millennial. – Business Perspectives and Research 9(1): 77-91.
[5] Cinelli, M., De Francisci Morales, G., Galeazzi, A., Quattrociocchi, W., Starnini, M. (2021): The echo chamber effect on social media. – Proceedings of the National Academy of Sciences 118(9): 8p.
[6] Collier, S.J., Lakoff, A. (2021): The government of emergency: Vital systems, expertise, and the politics of security. – Princeton University Press 320p.
[7] Ecker, U.K., Antonio, L.M. (2021): Can you believe it? An investigation into the impact of retraction source credibility on the continued influence effect. – Memory and Cognition 49(4): 631-644.
[8] Flamino, J., Galeazzi, A., Feldman, S., Macy, M.W., Cross, B., Zhou, Z., Serafino, M., Bovet, A., Makse, H.A., Szymanski, B.K. (2023): Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections. – Nature Human Behaviour 7: 904-916.
[9] Garg, P., Pahuja, S. (2020): Social media. – Advances in Marketing, Customer Relationship Management, and E-Services 21p.
[10] Goldani, M.H., Momtazi, S., Safabakhsh, R. (2021): Detecting fake news with capsule neural networks. – Applied Soft Computing 101: 12p.
[11] Henderson, K.S., Shteynberg, R.V. (2019): Plea decision-making: The influence of attorney expertise, trustworthiness, and recommendation. – Psychology, Crime and Law 26(6): 527-551.
[12] Horoub, I. (2023): Understanding media empowerment: Citizen journalism in Palestine. – Humanities and Social Sciences Communications 10(1): 10p.
[13] Johnston, N. (2020): Living in the world of fake news: High school students’ evaluation of information from social media sites. – Journal of the Australian Library and Information Association 69(4): 430-450.
[14] Jonathan, V. (2022): Twitter is now owned by Elon Musk – here's a brief history from the app's founding in 2006 to the present. – CNBC 3p.
[15] Kemp, S. (2023): Digital 2023: Malaysia. – DataReportal, Global Digital Insights 30p.
[16] Lee, C. (2020): The lowered voting age in Malaysia: Who will benefit? – ISEAS Yusof Ishak Institute 8p.
[17] Leong, P. (2020): Malaysian politics in the new media age: Implications on the political communication process. – Springer, Singapore 220p.
[18] Liaquat, U., Jost, J.T., Balcetis, E. (2023): System justification motivation as a source of backlash against equality-promoting policies – and what to do about it. – Social Issues and Policy Review 17(1): 131-154.
[19] Lyons, B.A., Montgomery, J.M., Guess, A.M., Nyhan, B., Reifler, J. (2021): Overconfidence in news judgments is associated with false news susceptibility. – Proceedings of the National Academy of Sciences 118(23): 8p.
[20] Matthes, J., Heiss, R., van Scharrel, H. (2023): The distraction effect: Political and entertainment-oriented content on social media, political participation, interest, and knowledge. – Computers in Human Behavior 142: 12p.
[21] Muda, M., Hamzah, M.I. (2021): Should I suggest this YouTube clip? The impact of UGC source credibility on eWOM and purchase intention. – Journal of Research in Interactive Marketing 15(3): 441-459.
[22] Naslund, J.A., Bondre, A., Torous, J., Aschbrenner, K.A. (2020): Social media and mental health: Benefits, risks, and opportunities for research and practice. – Journal of Technology in Behavioral Science 5(3): 245-257.
[23] Neo, R.L. (2021): Linking perceived political network homogeneity with political social media use via perceived social media news credibility. – Journal of Information Technology and Politics 18(3): 355-369.
[24] Piazza, J.A. (2021): Fake news: The effects of social media disinformation on domestic terrorism. – Dynamics of Asymmetric Conflict 15(1): 55-77.
[25] Savolainen, R. (2022): Assessing the credibility of information sources in times of uncertainty: Online debate about Finland’s NATO membership. – Journal of Documentation 79(7): 30-50.
[26] Serman, Z.E., Sims, J. (2022): Source credibility theory: SME hospitality sector blog posting during the COVID-19 pandemic. – Information Systems Frontiers 12p.
[27] Shahi, G.K., Majchrzak, T.A. (2022): AMUSED: An annotation framework of multimodal social media data. – Communications in Computer and Information Science 13p.
[28] Simpson, R. (2018): Changes in young adulthood. – Young Adult Development Project, Massachusetts Institute of Technology 5p.
[29] Szymkowiak, A., Melović, B., Dabić, M., Jeganathan, K., Kundi, G.S. (2021): Information technology and Gen Z: The role of teachers, the internet, and technology in the education of young people. – Technology in Society 65: 12p.
[30] Tandoc Jr., E.C., Thomas, R.J., Bishop, L. (2021): What is (fake) news? Analyzing news values (and more) in fake stories. – Media and Communication 9(1): 110-119.
[31] Tjiptono, F., Khan, G., Yeong, E.S., Kunchamboo, V. (2020): Generation Z in Malaysia: The four 'E' generation. – The New Generation Z in Asia: Dynamics, Differences, Digitalisation 15p.
[32] Vogel, I., Meghana, M. (2020): Detecting fake news spreaders on Twitter from a multilingual perspective. – 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA) 8p.
[33] Vrontis, D., Makrides, A., Christofi, M., Thrassou, A. (2021): Social media influencer marketing: A systematic review, integrative framework and future research agenda. – International Journal of Consumer Studies 45(4): 617-644.
[34] Yang, D., Alessandrini, S., Antonanzas, J., Antonanzas-Torres, F., Badescu, V., Beyer, H.G., Blaga, R., Boland, J., Bright, J.M., Coimbra, C.F.M., David, M., Frimane, Â., Gueymard, C.A., Hong, T., Kay, M.J., Killinger, S., Kleissl, J., Lauret, P., Lorenz, E., Zhang, J. (2020): Verification of deterministic solar forecasts. – Solar Energy 210: 20-37.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 NURFARAH DIYANA SHAIDI
This work is licensed under a Creative Commons Attribution 4.0 International License.
