This paper presents an automated method for distinguishing high-quality threads from low-quality ones in online forums, addressing the challenges posed by trolling and varying user expertise. The authors introduce four artificial measures to assess thread quality based on post ratings and propose two predictive tasks that do not rely on these ratings. Utilizing a machine learning framework, the method demonstrates significant improvements in predicting thread quality across all measures. The study also analyzes the contributions of different feature types to the overall performance, identifying key elements that help in discovering valuable threads.
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Lee, Jung-Tae, Min-Chul Yang, and Hae-Chang Rim. "Discovering high-quality threaded discussions in online forums." Journal of Computer Science and Technology 29.3 (2014): 519-531.
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