Ranking potential reply-providers in community question answering system

Abstract

Community Question Answering (CQA) websites have greatly facilitated users' lives, with an increasing number of people seeking help and exchanging ideas on the Internet. This newly-emerged community features two characteristics: social relations and an ask-reply mechanism. As users' behaviours and social statuses play a more important role in CQA services than traditional answer retrieving websites, researchers' concerns have shifted from the need to passively find existing answers to actively seeking potential reply providers that may give answers in the near future. We analyse datasets derived from an online CQA system named “Quora”, and observed that compared with traditional question answering services, users tend to contribute replies rather than questions for help in the CQA system. Inspired by the findings, we seek ways to evaluate the users' ability to offer prompt and reliable help, taking into account activity, authority and social reputation characteristics. We propose a hybrid method that is based on a Question-User network and social network using optimised PageRank algorithm. Experimental results show the efficiency of the proposed method for ranking potential answer-providers.