Strategies For Improving The Quality Of Answers In Social Q&A Communities

With the continuous development and application of information and communication technology,the mode of human knowledge dissemination has changed dramatically.The traditional knowledge dissemination network and Internet technology are combined to form a social Q&A community with "Zhihu" and "Quora" as typical representatives.The core element of social Q&A community is the user,which creates value through the knowledge connection between the user and the user.The growth of user amout is both an opportunity and a challenge for the development of social Q&A community.A large number of users from all walks of life and different identity backgrounds swarmed into the social Q&A community,which led to a sharp decline in the preciseness,professionalism and seriousness of the community,and the quality of the Q&A community significantly reduced.In this context,this paper takes "Zhihu" as the specific research object,from the two perspectives of responders' behavior and answer content,to explore strategies that can effectively improve the answer quality of social Q&A community.This paper first determines the background and significance of the research,then read a large number of relevant literature to review the relevant research at home and abroad,on this basis,it determines the research objectives,ideas and methods,and briefly introduces the research content and research framework of this paper.The theoretical basis of this study is mainly from the existing theoretical research of social Q&A community supported by social media theory and user generated content theory,and based on the theoretical knowledge of human dynamics and data mining,so as to provide a basis for the establishment of research content and research methods.In the perspective of responders' behavior,this paper collects behavioral data related to"excellent responder" in "Zhihu" community through crawlers,and analyzes and simulates the collected behavioral data by using the theory of human dynamics and relevant statistical analysis methods.It is found that the behavior of "excellent responder" in answering questions is not a random event,but a power law distribution of the time interval of answering which satisfies the fat tail characteristic.The other users' "Likes" of the answers will have a greater incentive effect on the interest of "excellent responder" in answering questions and then it can reduce the time interval of answering;The human dynamics model of interest can well explain the behavior characteristics of"excellent responder" in answering questions.In the perspective of answer content,this paper collected 87670 answers of 55 questions under the topic of Computer Science in "Zhihu" community.Through the research and analysis of the answer content data and the reference of the relevant literature,10 potential characteristics that may affect the quality of the answer content are determined,and the core characteristics that affect the quality of the answer content are studied by using the two classification model in data mining.It is found that the more the number of tagging,the clearer the key content and structure,the higher the quality of the answer content;the more reasonable the text length distribution is 100-700;the more positive the emotional value of the answer content can be more recognized by other users.Based on the above research findings,this paper proposes the following strategies and suggestions from the perspective of the construction and operation of social Q&A community to improve the answer quality of the whole community.In terms of responders' behavior,in order to motivate more "excellent responder" to answer questions,appropriate push time should be selected;secondly,operation and optimization should be carried out around improving the number of "Likes" in answer content,such as "double click Likes" can be supported in interaction level.In the aspect of answer content,the editing of answer content should support user-defined template,length verification and repeatability detection of answer content,and judgment of emotional tendency of answer content.The theoretical contributions of this paper include:introducing the human dynamics model based on interest to conduct in-depth research on the behavior of "excellent responder" in the social Q&A community,identifying the internal characteristics and laws of their answering behavior,enriching the theory of user information behavior;aiming at the problem of poor answer quality in the social Q&A community,integrating the behavior and answer content perspective,it provides a theoretical basis for the follow-up discussion of the strategies to improve the anser quality of social Q&A community.The contributions of this paper in application practice include:standing on the position of social Q&A community operators,summarizing the characteristics and influencing factors of "excellent responder" answering behavior,and aiming at the main characteristics that affect the answer quality,putting forward operational strategies to improve the answer quality,and then implementing them into the product operation and function optimization scheme of community platform function.