What's Vs. How's in Online Hotel Reviews: Comparing Information Value of Content and Writing Style with Machine Learning

被引：8

作者：

Shin, Seunghun ^{[1
]}

Du, Qianzhou ^{[1
]}

Xiang, Zheng ^{[1
]}

机构：

[1] Pamplin Coll Business, Howard Feiertag Dept Hospitality & Tourism Manage, Blacksburg, VA 24061 USA

来源：

INFORMATION AND COMMUNICATION TECHNOLOGIES IN TOURISM 2019 | 2019年

关键词：

Writing style; Textual content; Online hotel reviews; Machine learning; Natural language processing (NLP); CONSUMER REVIEWS; HELPFULNESS; WORDS;

D O I：

10.1007/978-3-030-05940-8_25

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Writing style is an important rhetorical feature of textual information. However, its value has not yet been well understood within the context of social media. This research compares two major aspects of textual content, i.e., content and style, to determine the information value of online hotel reviews. Using TripAdvisor hotel reviews, several machine learning techniques based on natural language processing (NLP) are applied to predict review helpfulness. The results indicate that textual features are core features of online reviews; that style is a more influential aspect than content; and, that combining both features produces the best results. This study contributes to the understanding of user-generated content in the textual format within the hospitality and tourism contexts. Limitations and directions for future research are also discussed.

引用

页码：321 / 332

页数：12

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