The popularity of Question–Answer websites such as StackOverflow, Ask and Yahoo! Answers is gradually increasing. Considering this increased popularity, the quality of the questions and answers is necessary to be taken into account. The reason for this necessity is that there could be many answers to any question, and some of these answers have a low level in terms of quality. The credibility and expertise of the questioner and the respondents in the field of the question is one of the solutions to get around this problem. In other words, individuals with a high level of expertise ask more difficult and high-quality questions in their field of expertise, and individuals with a high level of expertise can answer these questions appropriately. The present paper aims at finding the expertise level of the individuals based on available statistical data about questions and answers. For this purpose, two methods were tested. In the first method, which is performed through scoring in this study, the emphasis is on the scores of the questions and answers. The basic assumption of the scoring method is that the scores of the questions and the answers are related to each other, because individuals with a higher level of expertise raise questions with higher scores and, on the other hand, respondents also provide answers with higher scores. Therefore, it is possible to determine the level of expertise of individuals by examining the scores of the questions and answers. In the second method, which is named comment-mining here, the expertise of an individual is determined through scoring positive and negative words in the comments and ultimately obtaining a final score for the questions and answers of a user. The actual data on the StackOverflow website were used to perform these methods. The results of the scoring method show that there is no significant relationship between the scores of the questions and answers, so this method cannot be used to determine the level of expertise of users. But the results from the comment-mining method suggest that the method determines the expertise level of user to an acceptable level.

Question-Answer网站的受欢迎程度，例如StackOverflow，Ask和Yahoo! 答案正在逐渐增加。考虑到这种日益普及的问题，必须考虑问题和答案的质量。这种必要性的原因是，对于任何问题都可能有很多答案，并且其中某些答案的质量较低。发问者和被调查者在问题领域的信誉和专业知识是解决此问题的解决方案之一。换句话说，具有较高专业知识水平的个人在其专业知识领域中会提出更多困难和高质量的问题，而具有较高专业知识水平的个人可以适当地回答这些问题。本文旨在基于有关问题和答案的可用统计数据来找到个人的专业知识水平。为此，测试了两种方法。在本研究中通过评分进行的第一种方法中，重点是问题和答案的分数。评分方法的基本假设是，问题和答案的分数彼此相关，因为具有较高专业知识水平的人提出的分数更高，而受访者也提供分数较高的答案。因此，可以通过检查问题和答案的分数来确定个人的专业水平。在第二种方法（此处称为评论挖掘）中，通过对评论中的肯定和否定单词评分并最终获得用户的问题和答案的最终评分来确定个人的专业知识。StackOverflow网站上的实际数据用于执行这些方法。计分方法的结果表明，问题和答案的分数之间没有显着关系，因此该方法不能用于确定用户的专业水平。但是注释挖掘方法的结果表明，该方法将用户的专业知识水平确定为可接受的水平。计分方法的结果表明，问题和答案的分数之间没有显着关系，因此该方法不能用于确定用户的专业水平。但是注释挖掘方法的结果表明，该方法将用户的专业知识水平确定为可接受的水平。计分方法的结果表明，问题和答案的分数之间没有显着关系，因此该方法不能用于确定用户的专业水平。但是注释挖掘方法的结果表明，该方法将用户的专业知识水平确定为可接受的水平。