JinTao Huang, KangNyeon Yi and JiHye Han, SungKyunKwan University, South Korea
The aim of this paper is to examine people’s perceptions of home sharing industry through comparing Airbnb and Couchsurfing, using python to crawling twitter’s data. We conducted semantic network analysis by using UCINET, which is embedded with NETDRAW, for calculating betweenness centrality and visualizing semantic network based on multidimensional scaling(MDS). And we also used LIWC to analysis public sentimental perceptions. The present study’s results show that the characteristics discovered about Airbnb and Couchsurfing in cyberspace have possible future directions in view of word usage frequency, centrality and semantic networks. Moreover, the results show that in sentimental aspects, there are different public trends of emotions on Airbnb and Couchsurfing. Through those results, researchers provide information to understand which sectors should entrepreneurs put more efforts and money.
Sharing Economy, Home-sharing, Airbnb, Couchsurfing, Semantic Network Analysis