A mobile visualization platform for exploring social media data
Article Sidebar
Main Article Content
Abstract
With the increasing application of using mobile device and social media, large amount of continuous information about human behaviors is available. Data visualization provides an insightful presentation for the large-scale social media datasets. The focus of this paper is on the development of a mobile-device based visualization and analysis platform for social media data for the purpose of retrieving and visualizing visitors’ information for a specific region. This developed platform allows users to view the “big picture†of the visitors’ locations information. The result shows that the developed platform 1) performs a satisfied data collection and data visualization on a mobile device, 2) assists users to understand the varieties of human behaviors while visiting a place, and 3) offers a feasible role in imaging immediate information from social media and leading to further policy-making in related sectors and areas. Future research opportunities and challenges for social media data visualization are discussed.
Keywords: Social media, data visualization, mobile device
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
Anslow, C., Noble, J., Marshall, S., & Tempero, E. (2009) Web Software Visualization Via Google’s Visualization API.
Doshi, J., GoradiaA, I., & Mistry, D. (2014). A Review of Google Data Visualization Tools. International Journal of Current Engineering and Technology, 4(5).
Few, S. (2013). Data visualization for human perception. The Encyclopedia of Human-Computer Interaction, 2nd Ed.
Foursquare (2015a). Venues Service, Received October 18, 2015 from: https://developer.foursquare.com/overview/venues.html
Foursquare (2015b), Foursquare API, Retrieved October 18, 2015 form: https://developer.foursquare.com/
Hochman, N., & Schwartz, R. (2012, May). Visualizing instagram: Tracing cultural visual rhythms. In Proceedings of the Workshop on Social Media Visualization (SocMedVis) in conjunction with the Sixth International AAAI Conference on Weblogs and Social Media (ICWSM–12) (pp. 6-9).
Hu, Y., Manikonda, L., & Kambhampati, S. (2014). What we instagram: A first analysis of instagram photo content and user types. Proceedings of ICWSM. AAAI.
IDC. (2015). Smartphone OS Market Share, 2015 Q2. Retrieved 2015 from: http://www.idc.com/prodserv/smartphone-os-market-share.jsp, International Data Corporation
Instagram, 2015, Instagram statistics, Retrieved from: http://instagram.com/press/
Michalos, M., Tselenti, P. and Nalmpantis, S. L. 2012. Visualization Techniques for Large Datasets. Journal of Engineering Science and Technology Review, 5(1), 72-76.
Miguéns, J., Baggio, R., & Costa, C. (2008). Social media and tourism destinations: TripAdvisor case study. Advances in Tourism Research, 26-28.
Nebhi, K. (2012). Ontology-based information extraction from Twitter.
Qi, Y., Shi, G., Yu, X., & Li, Y. (2015, June). Visualization in media big data analysis. In Computer and Information Science (ICIS), 2015 IEEE/ACIS 14th International Conference on (pp. 571-574). IEEE.
Yin, J., Lampert, A., Cameron, M., Robinson, B., & Power, R. (2012). Using social media to enhance emergency situation awareness. IEEE Intelligent Systems, (6), 52-59.
Zhao, W. X., Jiang, J., He, J., Song, Y., Achananuparp, P., Lim, E. P., & Li, X. (2011, June). Topical keyphrase extraction from twitter. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1 (pp. 379-388). Association for Computational Linguistics.