Social Network Analysis And Research For The Evaluation Of Scientific Researchers

At present,the form of assessment for scientific researchers is single and result-oriented.That is,taking the check-in status of employee attendance,the number of papers published,or the degree of participation in projects as indicators for assessing scientific researchers.However,the results of single data analysis could not fully reflect the ability and situation of a scientific researcher in his work.Scientific researchers produce a lot of data in their daily work:the data from work mailboxes,and the data which from activities of employees such as erranding and attending meetings.These huge and rich data resources contain many information that has not yet been mined and utilized.Understanding that information is beyond human ability,but mining and analyzing these data could enrich employee assessment standards.Nowadays,the application of social network technology always focuses on the internet social network.Analyze user-focused network and user-forwarding network of Sina Weibo to predict user forwarding behavior;study user behavior on Facebook to discover social actors and roles in hot events;research on the STEM education community on Twitter to analyze user characteristics and mine key users.For the working network which isolated from the Internet,because of physical isolation,low user activity,and small user activity,seldom uses social network technology.But the researchers who use this working network have produced a lot of data through their work emails,attending meetings,erranding and other activities.These data have great application value for performance appraisal and personnel management.Due to the complexity of the information contained in these data and the large amount of redundant data,their value has not been fully utilized.By organizing and reconstructing these data,we can get the data set which is easy to store and use.And then,we could build the social network of scientific researchers in working,and analyze it by using social network analysis technology.In this paper,firstly,preprocesses data resources by means of data cleaning and extraction.So that data existing in different systems could be effectively correlated,such as mail data generated during work,data generated by attending meetings,and data generated by erranding.Subsequently,three data sets are obtained:mail data set,meeting data set and erranding data set.Secondly,combine these multi-source data sets,based on social network technology and force-guided layout algorithm,we could build the social network of relationships in the work of researchers.Finally,with the help of using social network analysis methods,based on node importance estimation method of network nodes,we can mine important nodes in this social network of relationships in the work.We could identify social people in the work community,technology bulls,and key people who play a role in the work.These analysis results could be used to examine the cooperation patterns between different departments and teams,and optimize departments,teams and work arrangements.Comprehensive analysis and research of experimental results,we could effectively analyze the motivation and periodicity of the researchers in their work.Compared with the traditional performance appraisal method,the results of this paper could be used as a supplement and aid to traditional performance assessment methods.