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.
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | CHI EA '15 |
| Herausgeber*innen | Bo Begole, Jinwoo Kim, Kori Inkpen, Woontack Woo |
| Erscheinungsort | Seoul Republic of Korea |
| Verlag | ACM Press |
| Seiten | 1055 - 1060 |
| ISBN (Print) | 9781450331463 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 2015 |
Österreichische Systematik der Wissenschaftszweige (ÖFOS)
- 102
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