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Modeling the role of message content and influencers in social media rebroadcasting

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  • Zhang, Yuchi
  • Moe, Wendy W.
  • Schweidel, David A.

Abstract

We develop a model that examines the role of content, content-user fit, and influence on social media rebroadcasting behavior. While previous research has studied the role of content or the role of influence in the spread of social media content separately, none has simultaneously examined both in an effort to assess the relative effects of each. Our modeling approach also accounts for a message's “fit” with users, based on the content of the message and the content of messages typically shared by users.

Suggested Citation

  • Zhang, Yuchi & Moe, Wendy W. & Schweidel, David A., 2017. "Modeling the role of message content and influencers in social media rebroadcasting," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 100-119.
    • Handle: RePEc:eee:ijrema:v:34:y:2017:i:1:p:100-119
    DOI: 10.1016/j.ijresmar.2016.07.003
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    1. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    2. De Bruyn, Arnaud & Lilien, Gary L., 2008. "A multi-stage model of word-of-mouth influence through viral marketing," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 151-163.
    3. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    4. Scott K. Shriver & Harikesh S. Nair & Reto Hofstetter, 2013. "Social Ties and User-Generated Content: Evidence from an Online Social Network," Management Science, INFORMS, vol. 59(6), pages 1425-1443, June.
    5. Haenlein, Michael, 2013. "Social interactions in customer churn decisions: The impact of relationship directionality," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 236-248.
    6. East, Robert & Hammond, Kathy & Lomax, Wendy, 2008. "Measuring the impact of positive and negative word of mouth on brand purchase probability," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 215-224.
    7. Christophe Van den Bulte & Yogesh V. Joshi, 2007. "New Product Diffusion with Influentials and Imitators," Marketing Science, INFORMS, vol. 26(3), pages 400-421, 05-06.
    8. Teck-Hua Ho & Shan Li & So-Eun Park & Zuo-Jun Max Shen, 2012. "Customer Influence Value and Purchase Acceleration in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 236-256, March.
    9. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    10. Olivier Toubia & Andrew T. Stephen, 2013. "Intrinsic vs. Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?," Marketing Science, INFORMS, vol. 32(3), pages 368-392, May.
    11. Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
    12. David Bell & Sangyoung Song, 2007. "Neighborhood effects and trial on the internet: Evidence from online grocery retailing," Quantitative Marketing and Economics (QME), Springer, vol. 5(4), pages 361-400, December.
    13. Bhatia, Tulikaa & Wang, Lei, 2011. "Identifying physician peer-to-peer effects using patient movement data," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 51-61.
    14. 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.
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    19. Khan, Naseer Abbas & Khan, Ali Nawaz & Moin, Muhammad Farrukh, 2021. "Self-regulation and social media addiction: A multi-wave data analysis in China," Technology in Society, Elsevier, vol. 64(C).
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