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• W2574248532 abstract "Sentiment analysis is one of the great accomplishments of the last decade in the field of Language Technologies. In this paper, we explore mining collective sentiment from forum posts in a Massive Open Online Course (MOOC) in order to monitor students’ trending opinions towards the course and major course tools, such as lecture and peer-assessment. We observe a correlation between sentiment ratio measured based on daily forum posts and number of students who drop out each day. On a user-level, we evaluate the impact of sentiment on attrition over time. A qualitative analysis clarifies the subtle differences in how these language behaviors are used in practice across three MOOCs. Implications for research and practice are discussed." @default.
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• W2574248532 date "2014-01-01" @default.
• W2574248532 modified "2023-09-25" @default.
• W2574248532 title "Sentiment Analysis in MOOC Discussion Forums: What does it tell us?" @default.
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• W2574248532 hasPublicationYear "2014" @default.
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