BeWell: A sentiment aggregator for proactive community management

Andreas Lindner, Margeret Hall, Claudia Niemeyer, Simon Caton

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Granular, localized information can be unobtrusively gathered to assess public sentiment as a superior measure of policy impact. This information is already abundant and available via Online Social Media. The missing link is a rigorous, anonymized and open source artefact that gives feedback to stakeholders and constituents. To address this, BeWell, an unobtrusive, low latency multi-resolution measurement for the observation, analysis and modelling of community dynamics, is proposed. To assess communal well-being, 42 Facebook pages of a large public university in Germany are analyzed with a dictionary-based text analytics program, LIWC. We establish the baseline of emotive discourse across the sample, and detect significant campus-wide events in this proof of concept implementation, then discuss future iterations including a community dashboard and a participatory management plan. Copyright is held by the author/owner(s).

Original languageEnglish (US)
Title of host publicationCHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems
Subtitle of host publicationCrossings
PublisherAssociation for Computing Machinery
Pages1055-1060
Number of pages6
ISBN (Electronic)9781450331463
DOIs
Publication statusPublished - Apr 18 2015
Event33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 - Seoul, Korea, Republic of
Duration: Apr 18 2015Apr 23 2015

Publication series

NameConference on Human Factors in Computing Systems - Proceedings
Volume18

Other

Other33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015
CountryKorea, Republic of
CitySeoul
Period4/18/154/23/15

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Keywords

  • Human-computer Interaction
  • Sentiment analysis
  • Social computing
  • Text analytics
  • Well-being

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Cite this

Lindner, A., Hall, M., Niemeyer, C., & Caton, S. (2015). BeWell: A sentiment aggregator for proactive community management. In CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings (pp. 1055-1060). (Conference on Human Factors in Computing Systems - Proceedings; Vol. 18). Association for Computing Machinery. https://doi.org/10.1145/2702613.2732787