Participatory Social Sensor: A Framework to Social Media Data Acquisition and Analysis
Nowadays, understanding urban mobility, transit, people viewpoint, and social behaviors has been the focus of many research and investments. However, data access is restricted to private companies and governments. In addition, the costs to create a sensor infrastructure on a given area is prohibitive. Then, using Location-Based Social Media (LBSM) may provide a new way to better comprehend the social behaviors, by the use of a users viewpoint. In this work, we propose the use of LBSM as participatory sensing, designing the Participatory Social Sensor (PSS), a friendly framework to social media data acquisition and analysis. We develop the Twitter data acquisition and analysis process, aiming to achieve the user application goals through a file setup,where the user specifies the spatial area, temporal interval, tags, and other parameters. As a result, the PSS shows a set of visual analysis which provides a context overview, allowing an easy way to researchers make-decision. A case study, Detection and Enrichment Service for Road Events Based on Heterogeneous Data Merger for VANETs, based on PSS framework was published in the current conference.
Gaurav, M., Srivastava, A., Kumar, A., and Miller, S. (2013). Leveraging candidate popularity on twitter to predict election outcome. In Proceedings of the 7th workshop on social network mining and analysis, page 7. ACM.
Karami, A., Dahl, A. A., Turner-McGrievy, G., Kharrazi, H., and Shaw Jr, G. (2018). Characterizing diabe-tes, diet, exercise, and obesity comments on twitter. International Journal of Information Management, 38(1):1-6.
Santos, B. P., Rettore, P. H., Ramos, H. S., Vieira, L. F. M., and A.F. Loureiro, A. (2018). Enriching traffic information with a spatiotemporal model based on social media. In ISCC, Natal, Brazil.
Xu, S., Li, S., and Wen, R. (2018). Sensing and detecting traffic events using geosocial media data: A review. Computers, Environment and Urban Systems, (June).