Title | ||
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Actionable Social Media Competitive Analytics For Understanding Customer Experiences. |
Abstract | ||
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A large amount of user-generated content is now freely available on social media sites. To increase their competitive advantage, companies need to monitor and analyze not only the customer-generated content on their own social media sites, but also the content on their competitors' social media sites. In this article, we describe a framework to integrate several techniques including quantitative analysis, text mining, and sentiment analysis for analyzing and comparing social media content from business competitors. Specifically, we conducted an in-depth case study which applies our developed framework to the analysis and comparison of social media content on the Facebook sites of the three largest drugstore chains in the United States: Walgreens, CVS, and Rite Aid. We found similarities and differences in the social media use among the three drugstore chains. We discuss the implications of our findings and provide recommendations to help companies develop their social media competitive analysis strategies. |
Year | DOI | Venue |
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2016 | 10.1080/08874417.2016.1117377 | JOURNAL OF COMPUTER INFORMATION SYSTEMS |
Keywords | Field | DocType |
Social media,text mining,sentiment analysis,business intelligence,competitive intelligence,competitive analytics | Competitive intelligence,Social media,Social media optimization,Computer science,Sentiment analysis,Competitive advantage,Knowledge management,Business intelligence,Analytics,Marketing,Competitor analysis | Journal |
Volume | Issue | ISSN |
56.0 | 2.0 | 0887-4417 |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Wu He | 1 | 433 | 38.40 |
Xin Tian | 2 | 61 | 8.71 |
Yong Chen | 3 | 750 | 118.44 |
Dazhi Chong | 4 | 3 | 2.51 |