Research On Contribution Evaluation Of Experts In Knowledge Sharing Community From The Perspective Of Customer Engagement

In recent years,lots of knowledge sharing communities emerged,such as Zhihu,De Dao,Netease Cloud Classroom,Guokr,etc.However,due to the poor knowledge ecological environment and low user activity,some of them lost numerous users and failed in community operations.As a type of virtual community,the most important to the survival and development of knowledge-sharing communities is to expand user groups and increase the user flow.Therefore,how to attract potential user groups to join in the community and maintain the loyalty and satisfaction of the existing user groups,thereby enhancing their stickiness,has become the basis for the survival and development of the knowledge sharing community.The realization of customer engagement of knowledge sharing community users is an effective way to enhance community user stickiness and expand community user flow.Users with high level of engagement can not only continue to consume knowledge of the community,but also help the community to attract more potential audiences and expand the user flow through the reputation communication,product recommendations,writing reviews and blog posts.Therefore,when evaluating the contribution of users in the knowledge sharing community,it is necessary to focus on whether it has created user engagement value for the community.This paper will evaluate the contribution of expert users in the community from the perspective of achieving user engagement in the knowledge sharing community,not only focusing on the content contributions created by experts,but also considering the user engagement created by expert users.This article selected Baidu Zhidao Daily as the research scenario to evaluate the contribution of experts in Zhidao Daily.First,based on literature research and expert interviews,we used customer engagement theory to build a knowledge sharing community expert contribution evaluation system,and verify the rationality of the evaluation system through mathematical statistics,and then establish the final evaluation model.Then we used python language to write a crawler program to obtain the contribution behavior data of 716 experts in Zhidao Daily.On basis of the data crawled,the entropy weight method was used to calculate the weights of the indicators in the evaluation system,and the entropy weights of the indicators of the evaluation system were established.At last,the comprehensive evaluation value of expert users was calculated by the TOPSIS evaluation method to generate the evaluation results of expert contribution..After the analysis of evaluation results,we could see that it is feasible to evaluate the user contribution of the knowledge sharing community from the perspective of customer engagement.Compared with content contributions,user engagement contributions created by experts have a greater impact on experts' comprehensive evaluation values.Meanwhile,the knowledge areas in the community are unevenly distributed.A few knowledge areas concentrate most of the expert productivity,and experts with multi-domain knowledge bring greater value to the community's content production and user engagement.At the same time,the contribution of experts in the knowledge sharing community revealed the "Matthew Effect".A few experts not only contributed more content,but also created a high level of user engagement,indicating their core contribution status in the community.Compared with individual expert users,the expert group organized as a team not only shares more knowledge,but also improves the engagement of users.Experts with more personal homepages also show greater advantages in community contributions.In addition,compared with the original user popularity evaluation mechanism in the community,the evaluation system constructed in this paper comprehensively considers the contributions of experts from multiple aspects,thus the evaluation results are more scientific and accurate.In response to results of this article,the study also proposes several strategies from the perspective of customer engagement to help the community improve the contribution level of expert users.From the perspective of improving user's personal engagement,establishing an expert knowledge production team,creating high-quality word-of-mouth of the expert,improving the expert's entry threshold,and optimizing the community's knowledge ecological environment can effectively improve the quantity and quality of the community's knowledge content,which improves the satisfaction and pleasure of users in the community.Through optimizing the expert evaluation system and establishing the interaction network between experts and users,the emotional bond between user and community could be strengthened,thereby promoting the interaction between users in the community.