Recommendation of Associated Tourist Attractions Based on SNS Analysis
Kaaen Kwon 1, Ah Cho 1, Wan-Sup Cho 2, Kwan-Hee Yoo 3, and
Ga-Ae Ryu 4
1. Department of Business Data Convergence, Chungbuk National University, Cheongju, Korea
2. Department of Management Information System, Chungbuk National University, Cheongju, Korea
3. Department of Software Engineering, Chungbuk National University, Cheongju, Korea
4. Department of Digital Informatics and Convergence, Chungbuk National, University, Cheongju, Korea
2. Department of Management Information System, Chungbuk National University, Cheongju, Korea
3. Department of Software Engineering, Chungbuk National University, Cheongju, Korea
4. Department of Digital Informatics and Convergence, Chungbuk National, University, Cheongju, Korea
Abstract—With the development of mobile devices and the supply of internet, information exchange has actively been made through SNS like blogs. In particular, blogs are widely used as a space where people share their experience after their visit to tourist attractions. Although the analysis on blog articles is expected to draw meaningful information, relevant research has yet to be conducted actively. This study proposes a method of recommending associated tourist attractions based on tourist’s opinions using Association Analysis and Text Network Analysis (TNA), in order to help to develop tour products and policies
Index Terms—SNS, tourist attraction, text network analysis, association rules
Cite: Kaaen Kwon, Ah Cho, Wan-Sup Cho, Kwan-Hee Yoo, and Ga-Ae Ryu, "Recommendation of Associated Tourist Attractions Based on SNS Analysis," Journal of Advanced Management Science, Vol. 4, No. 5, pp. 393-396, September 2016. doi: 10.12720/joams.4.5.393-396
Index Terms—SNS, tourist attraction, text network analysis, association rules
Cite: Kaaen Kwon, Ah Cho, Wan-Sup Cho, Kwan-Hee Yoo, and Ga-Ae Ryu, "Recommendation of Associated Tourist Attractions Based on SNS Analysis," Journal of Advanced Management Science, Vol. 4, No. 5, pp. 393-396, September 2016. doi: 10.12720/joams.4.5.393-396