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2015

Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums

4 years 10 months ago
Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums
Massive open online courses (MOOCs) are redefining the education system and transcending boundaries posed by traditional courses. With the increase in popularity of online courses, there is a corresponding increase in the need to understand and interpret the communications of the course participants. Identifying topics or aspects of conversation and inferring sentiment in online course forum posts can enable instructor interventions to meet the needs of the students, rapidly address course-related issues, and increase student retention. Labeled aspect-sentiment data for MOOCs are expensive to obtain and may not be transferable between courses, suggesting the need for approaches that do not require labeled data. We develop a weakly supervised joint model for aspectsentiment in online courses, modeling the dependencies between various aspects and sentiment using a recently developed scalable class of statistical relational models called hinge-loss Markov random fields. We validate our...
Arti Ramesh, Shachi H. Kumar, James R. Foulds, Lis
Added 13 Apr 2016
Updated 13 Apr 2016
Type Journal
Year 2015
Where ACL
Authors Arti Ramesh, Shachi H. Kumar, James R. Foulds, Lise Getoor
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