Location

Hilton Waikoloa Village, Hawaii

Event Website

http://www.hicss.hawaii.edu

Start Date

1-4-2017

End Date

1-7-2017

Description

In 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.

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Jan 4th, 12:00 AM Jan 7th, 12:00 AM

Towards a Sentiment Analyzing Discussion-board

Hilton Waikoloa Village, Hawaii

In 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.

http://aisel.aisnet.org/hicss-50/cl/teaching_and_learning_technologies/14