Opinion mining in management research: the state of the art and the way forward
Abstract
In the past decade, the explosive growth of social media has led to the
emergence of a wide variety of information sources that can significantly impact
individual level decision making processes. This has resulted in an increasing
availability of unstructured textual data and automated evaluation of opinions,
attitudes, and emotions has been accepted as an indispensable analytical tool in
diverse domains. Consequently, there is a strong need to understand the underlying
technical aspects of this emerging new field of analysis. In the current paper we
address this need by reviewing the state of the art in sentiment analysis, summarize
some of the important recent applications of sentiment analysis and offer future
directions for further research. This paper differs from earlier reviews in a number
of ways: first, it offers preliminary technical exposition of various techniques fol-
lowing a simple classification scheme so as to help potential future users to develop
overall understanding of this rapidly developing field; second, it discusses in greater
detail some of the more recently proposed techniques to solve a set of problems in
specific management domains; third, it also presents some examples to elucidate
how combining sentiment analysis techniques with conventional econometric
approaches can help us solve business specific problems. The main goal of this
paper is to generate more interest about this interesting new domain among man-
agement researchers.
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