TRAP@NCI

BeWell: A Sentiment Aggregator for Proactive Community Management

Lindner, Andreas, Hall, Margeret, Niemeyer, Claudia and Caton, Simon (2015) BeWell: A Sentiment Aggregator for Proactive Community Management. In: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems. ACM, New York, pp. 1055-1060. ISBN 9781450331463

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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.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Staff Research and Publications
Related URLs:
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 12 Dec 2016 15:53
Last Modified: 12 Dec 2016 15:53
URI: http://trap.ncirl.ie/id/eprint/2514

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