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Social Media Influence on Firms' Market Performance: Through the Lens of Experts' Opinion and Wisdom of the Crowd

Sun, Jing (2017) Social Media Influence on Firms' Market Performance: Through the Lens of Experts' Opinion and Wisdom of the Crowd. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Drawing on social influence theory, I examine the dynamics of social media impact in influencing firm market performance in the context of financial analyst recommendations. I show that consistency between multiple social influences as a process of frame alignment guides investor behavior. Through an event study, using social media data collected on Twitter consisting of S&P 500 firms from 2010 to 2015, I find that consistency between social media sentiment and analyst recommendations is significantly associated with firm market performance. In addition, a positivity bias of social media valance and social media sentiment polarity moderate consistency’s influence on firm market performance. I conclude by discussing the need for integrating consistency and positivity bias effects of social media into the evaluation of social media influence. This study demonstrates that combining analyst expert opinions and the wisdom of the crowd provides a more nuanced view of social media influence on firm market performance.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Sun, Jingjingsun124@gmail.comjis470000-0002-1627-1943
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairPrescott,
Committee MemberMadhavan,
Committee MemberCohen,
Committee MemberStephen,
Committee MemberCaner,
Date: 28 September 2017
Date Type: Publication
Defense Date: 6 April 2017
Approval Date: 28 September 2017
Submission Date: 24 August 2017
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 90
Institution: University of Pittsburgh
Schools and Programs: Joseph M. Katz Graduate School of Business > Business Administration
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: social media, analyst recommendation, firm performance, social influence
Date Deposited: 28 Sep 2017 15:35
Last Modified: 28 Sep 2022 05:15


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