VisualCommunity: a platform for archiving and studying communities

Suphanut Jamonnak; Deepshikha Bhati; Md Amiruzzaman; Ye Zhao; Xinyue Ye; Andrew Curtis

doi:10.1007/s42001-022-00170-y

VisualCommunity: a platform for archiving and studying communities

J Comput Soc Sci. 2022;5(2):1257-1279. doi: 10.1007/s42001-022-00170-y. Epub 2022 May 16.

Authors

Suphanut Jamonnak¹, Deepshikha Bhati¹, Md Amiruzzaman², Ye Zhao¹, Xinyue Ye³, Andrew Curtis⁴

Affiliations

¹ Department of Computer Science, Kent State University, Kent, OH USA.
² Department of Computer Science, West Chester University, West Chester, PA USA.
³ Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX USA.
⁴ Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH USA.

Abstract

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.

Keywords: AI processing; Community study; Geo-narrative; Spatial video; Visualization system.