VisualCommunity: a platform for archiving and studying communities

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

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1257-1279
Number of pages23
JournalJournal of Computational Social Science
Issue number2
StatePublished - Nov 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Transportation
  • Artificial Intelligence


  • AI processing
  • Community study
  • Geo-narrative
  • Spatial video
  • Visualization system


Dive into the research topics of 'VisualCommunity: a platform for archiving and studying communities'. Together they form a unique fingerprint.

Cite this