Abstract
Urban Activity Explorer is a new prototype for a planning support system that uses visual analytics to understand mobile social media data. Mobile social media data are growing at an astounding rate and have been studied from a variety of perspectives. Our system consists of linked visualizations that include temporal , spatial and topical data, and is well suited for exploring multiple scenarios. It allows a wide latitude for exploration, verification and knowledge generation as a central feature of the system. For this work, we used a database of approximately 1,000,000 geolocated tweets over a two-month period in Los Angeles. Urban Activity Explorer’s usage of visual analytic principles is uniquely suited to address the issues of inflexibility in data systems that led to planning support systems. We demonstrate that mobile social media can be a valuable and complementary source of information about the city.
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References
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003, January). Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.
Chang, R., Ghoniem, M., Kosara, R., Ribarsky, W., Yang, J., Suma, E., et al. (2007). Wirevis: Visualization of categorical, time-varying data from financial transactions. In IEEE Symposium on Visual Analytics Science and Technology, 2007, VAST 2007 (pp. 155–162). IEEE.
Chen, M., Ebert, D., Hagen, H., Laramee, R. S., Van Liere, R., Ma, K.-L., et al. (2009). Data, information, and knowledge in visualization. IEEE Computer Graphics and Applications, 29(1), 12–19.
Cho, I., Dou, W., Wang, D. X., Sauda, E., & Ribarsky, W. (2016). VAiRoma: A visual analytics system for making sense of places, times, and events in roman history. IEEE Transactions on Visualization and Computer Graphics, 22(1), 210–219.
Diakopoulos, N., Naaman, M., & Kivran-Swaine, F. (2010). Diamonds in the rough: Social media visual analytics for journalistic inquiry. In IEEE Symposium on Visual Analytics Science and Technology (VAST), 2010 (pp. 115–122). IEEE.
Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271.
Dou, W., Wang, X., Skau, D., Ribarsky, W., & Zhou, M. X. (2012). Leadline: Interactive visual analysis of text data through event identification and exploration. In IEEE Conference on Visual Analytics Science and Technology (VAST), 2012 (pp. 93–102). IEEE.
Goodchild, M. F. (2007). Citizens as sensors: The world of volunteered geography. GeoJournal, 69(4), 211–221.
Harris, B., & Batty, M. (1993). Locational models, geographic information and planning support systems. Journal of Planning Education and Research, 12(3), 184–198.
Karduni, A., Kermanshah, A., & Derrible, S. (2016). A protocol to convert spatial polyline data to network formats and applications to world urban road networks. Scientific Data, 3(160046). doi:10.1038/sdata.2016.46
Karduni, A., Cho, I., Wessel, G., Ribarsky, W., Sauda, E., Dou, W. (2017). Urban space explorer: A visual analytics system for understanding urban social media activities. IEEE Computer Graphics and Applications—Special Issue Geographic Data Science.
Keim, D., Andrienko, G., Fekete, J.-D., Görg, C., Kohlhammer, J., & Melançon, G. (2008). Visual analytics: Definition, process, and challenges. In A. Kerren, J. Stasko, J.-D. Fekete, & C. North (Eds.), Information Visualization Human-Centered Issues and Perspectives (pp. 154–175). Lecture Notes in Computer Science 4950. Berlin: Springer.
Kitchin, R. (2013). Big data and human geography: Opportunities, challenges and risks. Dialogues in Human Geography, 3(3), 262–267.
Klosterman, R. E. (1997). Planning support systems: A new perspective on computer-aided planning. Journal of Planning Education and Research, 17(1), 45–54.
Klosterman, R. E., & Pettit, C. J. (2005). An update on planning support systems. Environment and Planning B: Planning and Design, 32(4), 477–484.
MacEachren, A. M., Jaiswal, A., Robinson, A. C., Pezanowski, S., Savelyev, A., Mitra, P. et al. (2011). Senseplace2: Geotwitter analytics support for situational awareness. In IEEE Conference on Visual Analytics Science and Technology (VAST), 2011 (pp. 181–190). IEEE.
Ratti, C., Frenchman, D., Pulselli, R. M., & Williams, S. (2006). Mobile landscapes: Using location data from cell phones for urban analysis. Environment and Planning B: Planning and Design, 33(5), 727–748.
Ruths, D., & Pfeffer, J. (2014). Social media for large studies of behavior. Science, 346(6213), 1063–1064.
Sakaki, T., Okazaki, M., & Matsuo, Y. (2010). Earthquake shakes Twitter users: Real-time event detection by social sensors. In Proceedings of the 19th International Conference on World Wide Web, 2010 (pp. 851–860). ACM.
Stieglitz, S., & Dang-Xuan, L. (2013). Social media and political communication: A social media analytics framework. Social Network Analysis and Mining, 3(4), 1277–1291.
Sun, Y., Fan, H., Li, M., & Zipf, A. (2016). Identifying the city center using human travel flows generated from location-based social networking data. Environment and Planning B: Planning and Design, 43(3), 480–498.
Thomas, J. J., & Cook, K. A. (2006). A visual analytics agenda. IEEE Computer Graphics and Applications, 26(1), 10–13.
Twitter Usage Statistics—Internet Live Stats. (2017). http://www.internetlivestats.com/twitter-statistics/
Wessel, G. (2012). From place to nonplace: A case study of social media and contemporary food trucks. Journal of Urban Design, 17(4), 511–531.
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Karduni, A., Cho, I., Wessel, G., Dou, W., Ribarsky, W., Sauda, E. (2017). Urban Activity Explorer: Visual Analytics and Planning Support Systems. In: Geertman, S., Allan, A., Pettit, C., Stillwell, J. (eds) Planning Support Science for Smarter Urban Futures. CUPUM 2017. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-57819-4_4
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