Abstract
Quora is a fast growing social Q&A site where users create and answer questions, and identify the best answers by upvotes and downvotes with crowd wisdom. Unfortunately, little is known about properties of experts and non-experts and how to detect experts in general topics or a specific topic. To fill the gaps, in this manuscript we (1) analyze behaviors of experts and non-experts in five popular topics; (2) propose user activity features, quality of answer features, linguistic features and temporal features to identify distinguishing patterns between experts and non-experts; and (3) develop statistical models based on the features to automatically detect experts. Our experimental results show that our classifiers effectively identify experts in general topics and a specific topic, achieving up to 97 % accuracy and 0.987 AUC.
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Patil, S., Lee, K. Detecting experts on Quora: by their activity, quality of answers, linguistic characteristics and temporal behaviors. Soc. Netw. Anal. Min. 6, 5 (2016). https://doi.org/10.1007/s13278-015-0313-x
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DOI: https://doi.org/10.1007/s13278-015-0313-x