VisualCommunity is a platform designed to support community or neighborhood scale research. The platform integrates mobile, AI, visualization techniques, along with tools to help domain researchers, practitioners, and students collecting and working with spatialized video and geo-narratives. These data, which provide granular spatialized imagery and associated context gained through expert commentary have previously provided value in understanding various community-scale challenges. This paper further enhances this work AI-based image processing and speech transcription tools available in VisualCommunity, allowing for the easy exploration of the acquired semantic and visual information about the area under investigation. In this paper we describe the specific advances through use case examples including COVID-19 related scenarios.
Journal of Computational Social Science
Jamonnak, S., Bhati, D., Amiruzzaman, M., Zhao, Y., Ye, X., & Curtis, A. (2022). VisualCommunity: a platform for archiving and studying communities. Journal of Computational Social Science, 1-23. http://dx.doi.org/10.1007/s42001-022-00170-y