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How social media effects shape sentiments along the twitter journey?A Bayesian network approach

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  • Airani, Rajeev
  • Karande, Kiran

Abstract

Consistent with market orientation, marketing activities based on sentiment analysis involve gathering market intelligence, disseminating it firmwide, and responding to customer needs. While it has been applied in various marketing settings, antecedents of consumer sentiments that are rooted in social media platform effects need further examination. Using consumers’ social media journey as conceptual support, the current research investigates how consumer sentiments on social media are shaped by hashtag position, the bandwagon effect, and user anonymity and authority. The conceptual framework presented proposes that individual user characteristics of anonymity and authority influence platform effects including hashtag position and positive and negative bandwagon effects which impact expressed sentiments. The hypotheses are tested by analyzing over half a million tweets for 127 movies using the machine learning methodology of Bayesian Network analysis. Managerial implications for regulating platform effects to achieve the intended sentiment outcome, and limitations and avenues for future research are offered.

Suggested Citation

  • Airani, Rajeev & Karande, Kiran, 2022. "How social media effects shape sentiments along the twitter journey?A Bayesian network approach," Journal of Business Research, Elsevier, vol. 142(C), pages 988-997.
    • Handle: RePEc:eee:jbrese:v:142:y:2022:i:c:p:988-997
    DOI: 10.1016/j.jbusres.2021.12.071
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    1. Kristina Lerman, 2016. "Information Is Not a Virus, and Other Consequences of Human Cognitive Limits," Future Internet, MDPI, vol. 8(2), pages 1-11, May.
    2. Xiao Liu & Param Vir Singh & Kannan Srinivasan, 2016. "A Structured Analysis of Unstructured Big Data by Leveraging Cloud Computing," Marketing Science, INFORMS, vol. 35(3), pages 363-388, May.
    3. Wendy W. Moe & David A. Schweidel, 2012. "Online Product Opinions: Incidence, Evaluation, and Evolution," Marketing Science, INFORMS, vol. 31(3), pages 372-386, May.
    4. H. Leibenstein, 1950. "Bandwagon, Snob, and Veblen Effects in the Theory of Consumers' Demand," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 64(2), pages 183-207.
    5. Dongling Huang & Lan Luo, 2016. "Consumer Preference Elicitation of Complex Products Using Fuzzy Support Vector Machine Active Learning," Marketing Science, INFORMS, vol. 35(3), pages 445-464, May.
    6. Leonard Lee & J. Jeffrey Inman & Jennifer J. Argo & Tim Böttger & Utpal Dholakia & Timothy Gilbride & Koert van Ittersum & Barbara Kahn & Ajay Kalra & Donald R. Lehmann & Leigh M. McAlister & Venkates, 2018. "From Browsing to Buying and Beyond: The Needs-Adaptive Shopper Journey Model," Journal of the Association for Consumer Research, University of Chicago Press, vol. 3(3), pages 277-293.
    7. Harrigan, Paul & Evers, Uwana & Miles, Morgan & Daly, Timothy, 2017. "Customer engagement with tourism social media brands," Tourism Management, Elsevier, vol. 59(C), pages 597-609.
    8. Emilio Ferrara & Zeyao Yang, 2015. "Measuring Emotional Contagion in Social Media," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    9. Rebecca Hamilton & Linda L. Price, 2019. "Consumer journeys: developing consumer-based strategy," Journal of the Academy of Marketing Science, Springer, vol. 47(2), pages 187-191, March.
    10. Lin, Hsin-Chen & Bruning, Patrick F. & Swarna, Hepsi, 2018. "Using online opinion leaders to promote the hedonic and utilitarian value of products and services," Business Horizons, Elsevier, vol. 61(3), pages 431-442.
    11. V. Srinivasan Rao & Sirkka L. Jarvenpaa, 1991. "Computer Support of Groups: Theory-Based Models for GDSS Research," Management Science, INFORMS, vol. 37(10), pages 1347-1362, October.
    12. Kastanakis, Minas N. & Balabanis, George, 2012. "Between the mass and the class: Antecedents of the “bandwagon” luxury consumption behavior," Journal of Business Research, Elsevier, vol. 65(10), pages 1399-1407.
    13. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
    Full references (including those not matched with items on IDEAS)

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