Abstract
People around the world often rely on online community forums for answers to their queries. These forums have become hugely popular in the last decade, leading to a spurt in the number of users and questions. For a better user experience, quality monitoring is essential. However, manual moderation of millions of questions is infeasible. Prior works mostly rely on handcrafted features which is ineffective or use community feedback as part of learning which makes them unsuitable for monitoring during question creation. In this work, we use recent deep learning techniques to assess the quality of questions in online community forums at creation time. We evaluate our model on the StackOverflow dataset that contains 60000 questions across three qualities. Our model achieves an F1 score of 0.92 on this dataset.
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Rithish, H., Deepak, G., Santhanavijayan, A. (2021). Automated Assessment of Question Quality on Online Community Forums. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2021. Lecture Notes in Networks and Systems, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-030-73882-2_72
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DOI: https://doi.org/10.1007/978-3-030-73882-2_72
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