research-article

Deciphering word-of-mouth in social media: Text-based metrics of consumer reviews

Authors:

Yubo ChenAuthors Info & Claims

ACM Transactions on Management Information Systems (TMIS), Volume 3, Issue 1

Article No.: 5, Pages 1 - 23

https://doi.org/10.1145/2151163.2151168

Published: 10 April 2012 Publication History

Abstract

Enabled by Web 2.0 technologies, social media provide an unparalleled platform for consumers to share their product experiences and opinions through word-of-mouth (WOM) or consumer reviews. It has become increasingly important to understand how WOM content and metrics influence consumer purchases and product sales. By integrating marketing theories with text mining techniques, we propose a set of novel measures that focus on sentiment divergence in consumer product reviews. To test the validity of these metrics, we conduct an empirical study based on data from Amazon.com and BN.com (Barnes & Noble). The results demonstrate significant effects of our proposed measures on product sales. This effect is not fully captured by nontextual review measures such as numerical ratings. Furthermore, in capturing the sales effect of review content, our divergence metrics are shown to be superior to and more appropriate than some commonly used textual measures the literature. The findings provide important insights into the business impact of social media and user-generated content, an emerging problem in business intelligence research. From a managerial perspective, our results suggest that firms should pay special attention to textual content information when managing social media and, more importantly, focus on the right measures.

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Liu QSon H(2024)Methods for aggregating investor sentiment from social mediaHumanities and Social Sciences Communications10.1057/s41599-024-03434-211:1Online publication date: 17-Jul-2024
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Index Terms

Deciphering word-of-mouth in social media: Text-based metrics of consumer reviews
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 3, Issue 1

April 2012

119 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/2151163

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Copyright © 2012 ACM.

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Publication History

Published: 10 April 2012

Accepted: 01 January 2012

Received: 01 January 2012

Published in TMIS Volume 3, Issue 1

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Westland J(2024)Review Valence Impact on Jello Shot SalesAdvances in Digital Marketing and eCommerce10.1007/978-3-031-62135-2_23(225-235)Online publication date: 20-Jun-2024
https://doi.org/10.1007/978-3-031-62135-2_23
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