Research on Enterprise Public Opinions Based on Large-scale Text Data Sentiment Mining

Lianren Wu, jinjie Li, Qi Jiayin

Knowledge Management Forum ›› 2016, Vol. 1 ›› Issue (6) : 457-463.

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PDF(695 KB)
Knowledge Management Forum ›› 2016, Vol. 1 ›› Issue (6) : 457-463. DOI: 10.13266/j.issn.2095-5472.2016.053

Research on Enterprise Public Opinions Based on Large-scale Text Data Sentiment Mining

  • Lianren Wu, jinjie Li, Qi Jiayin
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Abstract

[Purpose/significance] In the era of big data, text mining and sentiment analysis technologies have been widely used in the analysis of online reviews (ORs). Through the large-scale text data mining, the key factors influencing the public opinion of enterprises are studied. [Method/process] We collected more than twenty-five million hotel online reviews from 103878 hotels, identifying key content elements that affected the customer service experience. [Result/conclusion] Through the exploratory factor analysis and the multiple regression analysis, the authors explore the relationships between the hotel customer experience and satisfaction. It is hoped that this study sets an example for the development of business analytics in enterprises marketing and management.

Key words

online review / text mining / sentiment analysis / enterprise public opinion / business analysis

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Lianren Wu, jinjie Li, Qi Jiayin. Research on Enterprise Public Opinions Based on Large-scale Text Data Sentiment Mining[J]. Knowledge Management Forum. 2016, 1(6): 457-463 https://doi.org/10.13266/j.issn.2095-5472.2016.053
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