Quantitative Analysis of Hotspots and Trends in User-generated Content

Yong XU, Ya-li WU, Qian WANG, Xin-rui ZHANG, Fan-hua LI

Abstract


User generated content (UGC) is a kind of Internet product mode leaded by user under Web 2.0, which is more active in recent years. In the paper, the text mining and visual analysis tool CiteSpace was used to analyze literatures with key words of "user generated content" published in Web of Science database from 2008 to 2019. The themes of literatures, institutes of authors, key words, and co-citation were analyzed to get focuses and trends of UGC. In the paper, the research hotspots of UGC were included to provide suggestion for further work: basic information, motivation, application and analysis of UGC, and legal issues.

Keywords


User Generated Content, CiteSpace, Visualization analysis, Sentiment analyzing


DOI
10.12783/dtcse/msam2020/34257

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