BeWell: A Sentiment Aggregator for Proactive Community Management

Andreas Lindner, Margeret Hall, Claudia Niemeyer, Simon Caton

Publication: Chapter in book/Conference proceedingContribution to conference proceedings


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.
Original languageEnglish
Title of host publicationCHI EA '15
Editors Bo Begole, Jinwoo Kim, Kori Inkpen, Woontack Woo
Place of PublicationSeoul Republic of Korea
PublisherACM Press
Pages1055 - 1060
ISBN (Print)9781450331463
Publication statusPublished - 2015

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102

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