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SIGBPS AOI: Text Mining and Business Applications Track Chairs:
Jason Li (Drexel University)
Track Description: Textual data has been constantly accumulated in the business process and become an important information source for business decision making. Some examples include business process descriptions, management announcements, meeting and communication records, and company website text. There are even much more text generated outside but relevant to companies, such as financial news, company research reports, online product reviews, tweets and discussion board messages. How to discover and extract valuable insights from these texts to improve business performance becomes an increasingly important research issue. Text mining methods, exemplified by natural language processing and machine learning techniques, have been introduced to business researchers to empower their text analysis. This track aims to provide a platform to discuss both methodological advancements and new business applications of text mining.
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