Web forums offer open and interactive social communication platforms for numerous participants to share information and offer perspectives on a variety of business and social issues with audiences around the world. In addition to facilitating widespread communication, these web forums contain massive amounts of data and represent rich sources of information that can be utilized to advance the understanding of participants and society. In particular, web forums pertaining to firms and their customers, employees, and investors, represent valuable resources for the acquisition of business intelligence. However, web forums represent a complex analytic landscape requiring the development of automated, intelligent, and scalable analytic approaches. The dissertation follows the design science paradigm in management information systems research, and aims to develop and refine approaches to the analysis of web forums, and to apply these analytic approaches to firm-related web forums to derive information that may explain and predict firm stock behavior. The designs of the devised approaches to web forum analysis are informed by the stakeholder theory of the firm, and systemic functional linguistic theory. We introduce and advance a stakeholder approach to the analysis of firm-related web forums, and improve existing approaches to sentiment analysis in web forums. In Chapter 2 we develop and deploy a stakeholder framework to analyze a popular firm-related finance web forum and apply the extracted measures to explain firm stock return, volatility, and trading volume. In Chapter 3 we advance the stakeholder framework and perform dynamic analyses of web forums over time, and compare several feature representations of stakeholders and approaches to sentiment analysis. We deploy the stakeholder framework to analyze several firm-related web forums, and apply the derived measures to predict firm stock return and perform simulated trading of firm stock over a one year period to determine the economic value of the extracted information. Finally, in Chapter 4 we develop approaches to improve the scalability of sentiment analysis across multiple web forums in a collection. Overall the dissertation contributes to the literature on the analysis of web forums, and demonstrates the value of firm-related web forums as sources of business intelligence.
|Contributors||Nunamaker, Jay F. Jr., Lusch, Robert, Lin, Mingfeng, Nunamaker, Jay F. Jr., Chen, Hsinchun|
|Publisher||The University of Arizona.|
|Source Sets||University of Arizona|
|Type||text, Electronic Dissertation|
|Rights||Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.|
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