Towards a Sentiment Analyzing Discussion-board

dc.contributor.authorThoms, Brian
dc.contributor.authorEryilmaz, Evren
dc.contributor.authorMercado, Glo
dc.contributor.authorRamirez, Benjamin
dc.contributor.authorRodriguez, Jose
dc.date.accessioned2016-12-29T00:10:00Z
dc.date.available2016-12-29T00:10:00Z
dc.date.issued2017-01-04
dc.description.abstractIn this paper we present the design and construction of a sentiment analyzing discussion board, which was used to support learning and interaction within an existing online social networking (OSN) system. More specifically, this research introduces an innovative extension to learning management software (LMS) that combines real-time sentiment analysis with the goal of fostering student engagement and course community. In this study we perform data mining to extract sentiment on over 6,000 historical discussion board posts. This initial data was analyzed for sentiment and interaction patterns and used for guiding the redesign of an existing asynchronous online discussion board (AOD). The redesign incorporates a sentiment analyzer, which allows users to analyze the sentiment of their individual contributions prior to submission. Preliminary results found that the proposed system produced more favorable outcomes when compared to existing AOD software.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.021
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41171
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectasynchronous online discussion
dc.subjectdata mining
dc.subjectdesign science research
dc.subjectonline social networking
dc.subjectsentiment analysis
dc.titleTowards a Sentiment Analyzing Discussion-board
dc.typeConference Paper
dc.type.dcmiText

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