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Research Note —The Allure of Homophily in Social Media: Evidence from Investor Responses on Virtual Communities

Author

Listed:
  • Bin Gu

    (W. P. Carey School of Business, Arizona State University, Tempe, Arizona 85287)

  • Prabhudev Konana

    (McCombs School of Business, University of Texas at Austin, Austin, Texas 78712)

  • Rajagopal Raghunathan

    (McCombs School of Business, University of Texas at Austin, Austin, Texas 78712)

  • Hsuanwei Michelle Chen

    (School of Information, San Jose State University, San Jose, California 95192)

Abstract

Millions of people participate in online social media to exchange and share information. Presumably, such information exchange could improve decision making and provide instrumental benefits to the participants. However, to benefit from the information access provided by online social media, the participant will have to overcome the allure of homophily —which refers to the propensity to seek interactions with others of similar status (e.g., religion, education, income, occupation) or values (e.g., attitudes, beliefs, and aspirations). This research assesses the extent to which social media participants exhibit homophily (versus heterophily) in a unique context—virtual investment communities (VICs). We study the propensity of investors in seeking interactions with others with similar sentiments in VICs and identify theoretically important and meaningful conditions under which homophily is attenuated. To address this question, we used a discrete choice model to analyze 682,781 messages on Yahoo! Finance message boards for 29 Dow Jones stocks and assess how investors select a particular thread to respond. Our results revealed that, despite the benefits from heterophily, investors are not immune to the allure of homophily in interactions in VICs. The tendency to exhibit homophily is attenuated by an investor’s experience in VICs, the amount of information in the thread, but amplified by stock volatility. The paper discusses important implications for practice.

Suggested Citation

  • Bin Gu & Prabhudev Konana & Rajagopal Raghunathan & Hsuanwei Michelle Chen, 2014. "Research Note —The Allure of Homophily in Social Media: Evidence from Investor Responses on Virtual Communities," Information Systems Research, INFORMS, vol. 25(3), pages 604-617, September.
    • Handle: RePEc:inm:orisre:v:25:y:2014:i:3:p:604-617
    DOI: 10.1287/isre.2014.0531
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    References listed on IDEAS

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    Cited by:

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    2. Liangfei Qiu & Asoo Vakharia & Arunima Chhikara, 2019. "Multi-Dimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Working Papers 19-01, NET Institute.
    3. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Fung, Derrick W.H. & Lee, Wing Yan & Yeh, Jason J.H. & Yuen, Fei Lung, 2020. "Friend or foe: The divergent effects of FinTech on financial stability," Emerging Markets Review, Elsevier, vol. 45(C).
    5. Liangfei Qiu & Arunima Chhikara & Asoo Vakharia, 2021. "Multidimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Information Systems Research, INFORMS, vol. 32(3), pages 876-894, September.
    6. Wang, Wanxin & Mahmood, Ammara & Sismeiro, Catarina & Vulkan, Nir, 2019. "The evolution of equity crowdfunding: Insights from co-investments of angels and the crowd," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    7. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
    8. Mengke Qiao & Ke-Wei Huang, 2021. "Correcting Misclassification Bias in Regression Models with Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 32(2), pages 462-480, June.
    9. Maxime Delabarre, 2021. "FinTech in the Financial Market," SciencePo Working papers Main hal-03107769, HAL.
    10. Peng Xie, 2022. "The Interplay Between Investor Activity on Virtual Investment Community and the Trading Dynamics: Evidence From the Bitcoin Market," Information Systems Frontiers, Springer, vol. 24(4), pages 1287-1303, August.
    11. Tingting Song & Qian Tang & Jinghua Huang, 2019. "Triadic Closure, Homophily, and Reciprocation: An Empirical Investigation of Social Ties Between Content Providers," Information Systems Research, INFORMS, vol. 30(3), pages 912-926, September.
    12. Prasanta Bhattacharya & Tuan Q. Phan & Xue Bai & Edoardo M. Airoldi, 2019. "A Coevolution Model of Network Structure and User Behavior: The Case of Content Generation in Online Social Networks," Service Science, INFORMS, vol. 30(1), pages 117-132, March.
    13. Kawaljeet Kaur Kapoor & Kuttimani Tamilmani & Nripendra P. Rana & Pushp Patil & Yogesh K. Dwivedi & Sridhar Nerur, 2018. "Advances in Social Media Research: Past, Present and Future," Information Systems Frontiers, Springer, vol. 20(3), pages 531-558, June.
    14. Mochen Yang & Gediminas Adomavicius & Gordon Burtch & Yuqing Rena, 2018. "Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 29(1), pages 4-24, March.
    15. Sophie Cockcroft & Mark Russell, 2018. "Big Data Opportunities for Accounting and Finance Practice and Research," Australian Accounting Review, CPA Australia, vol. 28(3), pages 323-333, September.
    16. Maxime Delabarre, 2021. "FinTech in the Financial Market," Working Papers hal-03107769, HAL.

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