Title
Stakeholder Analyses of Firm-Related Web Forums: Applications in Stock Return Prediction
Abstract
In this study, we present stakeholder analyses of firm-related web forums. Prior analyses of firm-related forums have considered all participants in the aggregate, failing to recognize the potential for diversity within the populations. However, distinctive groups of forum participants may represent various interests and stakes in a firm worthy of consideration. To perform the stakeholder analyses, the Stakeholder Analyzer system for firm-related web forums is developed following the design science paradigm of information systems research. The design of the system and its approach to stakeholder analysis is guided by two kernel theories, the stakeholder theory of the firm and the systemic functional linguistic theory. A stakeholder analysis identifies distinctive groups of forum participants with shared characteristics expressed in discussion and evaluates their specific opinions and interests in the firm. Stakeholder analyses are performed in six major firm-related forums hosted on Yahoo Finance over a 3-month period. The relationships between measures extracted from the forums and subsequent daily firm stock returns are examined using multiple linear regression models, revealing statistically significant indicators of firm stock returns in the discussions of the stakeholder groups of each firm with stakeholder-model-adjusted R2 values reaching 0.83. Daily stock return prediction is also performed for 31 trading days, and stakeholder models correctly predicted the direction of return on 67% of trading days and generated an impressive 17% return in simulated trading of the six firm stocks. These evaluations demonstrate that the stakeholder analyses provided more refined assessments of the firm-related forums, yielding measures at the stakeholder group level that better explain and predict daily firm stock returns than aggregate forum-level information.
Year
DOI
Venue
2015
10.1145/2675693
ACM Trans. Management Inf. Syst.
Keywords
Field
DocType
Social media analytics,web forums,stakeholder analysis,sentiment analysis,stock prediction
Social media analytics,Information systems research,Stakeholder,Stakeholder analysis,Sentiment analysis,Stakeholder theory,Design science,Stock (geology),Marketing,Business
Journal
Volume
Issue
ISSN
6
1
2158-656X
Citations 
PageRank 
References 
8
0.45
46
Authors
3
Name
Order
Citations
PageRank
David Zimbra12019.93
Hsinchun Chen29569813.33
Robert F. Lusch380.45