Evaluating Answer Qualities on Q&A Community Sites (StackOverFlow)

Abstract

Social Networking sites have gained much popularity in the recent years due to the widespread use of internet and availability of huge amounts of information. One kind of social network is Question Answering Community sites like StackOverflow, Quora and many more. These sites facilitate the user to ask their query on such sites using natural language and get the answers to their queries in natural language. There are many challenges to face when achieving above goals. One of the goals is to find the valid answers out of available answers and present it to the user, so as to save the user from going through multiple answers for a particular question and selecting the valid or appropriate answer. In this paper, we propose a system that finds the best answer from all the available answers based on answer content and the relationship between question and answer. We trained the system using three different classifiers and noted the accuracy results of each; the classifier which gave maximum accuracy was selected.

Keywords: Question Answer Community, Feature Extraction, Model Training