Browse > Article
http://dx.doi.org/10.7840/kics.2017.42.2.505

Investigation of Twitter Users' Activity Radius and Home Region in the City: The Case of Las Vegas  

Cho, Jaehee (Kwangwoon University College of Business)
Seo, Il-Jung (Kwangwoon University College of Business)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.42, no.2, 2017 , pp. 505-513 More about this Journal
Abstract
In this study, we collected 200,578,703 geo-tweets and removed the twitter bots. Using the concept of activity radius, Twitter users are classified. Users are also divided first into domestic and overseas, and again domestic ones are divided into locals and non-locals. Statistical characteristics of activity strength and active area of Twitter users are described according to activity radius and home region, and the geographical distribution is presented visually. Through a case study of Las Vegas, we have identified the difference in activity strength and active area by the user's home residence. We expect to derive theories about human mobility by analyzing various cities with the method proposed in this study.
Keywords
human mobility; big data; geotagged tweets; home region; activity radius; central location;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 C. Robusto, "The cosine-haversine formula," The Am. Math. Monthly, vol. 64, no. 1, pp. 38-40, 1957.   DOI
2 LVCVA, Las Vegas Visitor Profile Study (2015), Retrieved Jan. 6, 2017, from http://www.lvcva.com.
3 S. Park, Y. I. Kim, and S. R. Lee, "Hierarchical visualization of cloud-based social network service using fuzzy," J. KICS, vol. 38B, no. 7, pp. 501-511. Jul. 2013.   DOI
4 J. Moon, I. Jang, Y. C. Choe, J. G. Kim, and G. Bock, "Case study of big data-based agri-food recommendation system according to types of customers," J. KICS, vol. 40, no. 5, pp. 903-913, May 2015.   DOI
5 M. Lenormand, B. Goncalves, A. Tugores, and J. J. Ramasco, "Human diffusion and city influence," J. The Royal Soc. Interface, vol. 12, no. 109, id. 20150473, pp. 1-9, Jul. 2015.
6 J. T. Oh, "Personal environment service and technology based on smart phone," J. KICS, vol. 38C, no. 5, pp. 454-463, May 2013.   DOI
7 J. H. Cho, "Tutorial: Geo-tweet analysis to understand mobility patterns of people," in Proc. Korea Soc. IT Serv. Conf., pp. 419-428, Seoul, Korea, May 2016.
8 B. Hawelka, I. Sitko, E. Beinat, S. Sobolevsky, P. Kazakopoulos, and C. Ratti, "Geo-located twitter as proxy for global mobility patterns," Cartography and Geographic Inf. Sci., vol. 41, no. 3, pp. 260-271, Feb. 2014.   DOI
9 J. Yin, Y. Gao, Z. Du, and S. Wang, "Exploring multi-scale spatiotemporal twitter user mobility patterns with a visual-analytics approach," ISPRS Int. J. Geo-Inf., vol. 5, no. 10, id. 187, pp. 1-19, Oct. 2016.   DOI
10 J. H. Cho and I. Seo, "Comparing the spatial mobility of residents and tourists by using teotagged tweets," J. Inf. Technol. Serv., vol. 15, no. 3, pp. 211-221, Sep. 2016.
11 J. Mahmud, J. Nichols, and C. Drews, "Home location identification of twitter users," ACM Trans. Intell. Syst. Technol., vol. 5, no. 3, id. 47, pp. 1-21, Jul. 2014.
12 Z. Cheng, J. Caverlee, and K. Lee, "You are where you tweet: A content-based approach to geo-locating Twitter use," in Proc. 19th ACM Int. Conf. Inf. and Knowledge Management, pp. 759-768, Toronto, Canada, Oct. 2010.
13 B. Hecht, L. Hong, B. Suh, and E. H. Chi, "Tweets from Justin Bieber's heart: The dynamics of the 'location' field in user profiles," in Proc. SIGCHI Conf. Human Factors in Comput. Syst., pp. 237-246, Vancouver, Canada, May 2011.
14 N. Hossain, T. Hu, R. Feizi, A. M. White, J. Luo, and H. Kautz, Inferring fine-grained details on user activities and home location from social media: detecting drinking-whiletweeting patterns in communities (2016), Retrived Jan. 6, 2017, from http://arxiv.org/ abs/1603.03181.
15 J. Kulshrestha, F. Kooti, A. Nikravesh, and K. P. Gummadi, "Geographic dissection of the Twitter network," in Proc. 6th Int. AAAI Conf. on Weblogs and Social Media, pp. 202-209, Dublin, Ireland, Jun. 2012.
16 A. Belyi, I. Bojic, S. Sobolevsky, I. Sitko, B. Hawelka, L. Rudikova, A. Kurbatski, and C. Ratti, Global multi-layer network of human mobility (2016), Retrived Jan. 6, 2017, from http://arxiv.org/abs/1601.05532.