25/07/2020

Humor detection in product question answering systems

Yftah Ziser, Elad Kravi, David Carmel

Keywords: product question answering, humor detection

Abstract Paper Similar Papers

Abstract: Community question-answering (CQA) has been established as a prominent web service enabling users to post questions and get answers from the community. Product Question Answering (PQA) is a special CQA framework where questions are asked (and are answered) in the context of a specific product. Naturally, humorous questions are integral part of such platforms, especially as some products attract humor due to their unreasonable price, their peculiar functionality, or in cases that users emphasize their critical point-of-view through humor. Detecting humorous questions in such systems is important for sellers, to better understand user engagement with their products. It is also important to signal users about flippancy of humorous questions, and that answers for such questions should be taken with a grain of salt.In this study we present a deep-learning framework for detecting humorous questions in PQA systems. Our framework utilizes two properties of the questions - Incongruity and Subjectivity, demonstrating their contribution for humor detection. We evaluate our framework over a real-world dataset, demonstrating an accuracy of 90.8

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