Design And Implementation Of Scholar Big Data Collection And Evaluation System

In the era of Web 2.0,the application of computer technology and communication technology in the field of scientific communication has undergone an informal scientific communication.New scientific communication methods based on user-created content,interaction and sharing ideas have made scientific research more abundant and varied,and the emerging academic social network has set up unfair.A new way of scientific communication.In the face of the explosive growth of academic literature,how to intuitively and effectively evaluate the impact of scholars and literature has become a problem to be solved in various research fields.Traditional evaluation methods use journal impact factors(JIF)and citation counts to measure the impact of scholars in the scientific community.But the traditional evaluation system of academic papers is more and more difficult to realize the comprehensive and objective evaluation of scientific research results because of its delay and one-sidedness.In recent years,scholars have devoted much attention to the establishment and research of academic indicators in evaluating research results and methods,but there are still many problems to be explored,such as visually displaying the dynamic changes of scholars' existing achievements,and comprehensively evaluating the influence of scholars.In view of the above problems and shortcomings,this paper proposes to design and implement a big data of scholar collection and evaluation system by crawling scholar's big data,establishing an evaluation system on the basis of existing research,applying data visualization technology,visually displaying big data of scholar collection and evaluation system.The design of scholar's big data collection and evaluation system realizes the distributed crawling function.Using the application program interface(API),Medenley,GitHub and Twitter as the scholar's data source to crawl the detailed scholar's data such as articles and authors,an efficient scholar's big data crawling way is proposed.Data crawling method realizes the comprehensive collection of massive scholar data.In order to display the academic achievement and influence of scholars and evaluate them scientifically and quantitatively,three ranking lists of scholars are given,and the large academic data of each scholar on the list are displayed visually.The quantitative evaluation visualization of massive scholar data is realized.Based on the three dimensions of journal influencing factors(JIF),scientific influence and social prestige,it is more convenient to distinguish articles with high scientific impact,JIF and social popularity by abstracting each article into a block in the coordinate system of annual and citation rate.