The Identification Method Research And Software Development Of Key Nodes And Key Links In Microblog Networking

The students gradually form a variety of groups through mutual contacts and communications with each other, after entering the University. Scientific classification of college students lays the foundation for different kinds of college students’ ideological and political education. According to the students’ characteristics, regional differences and familial economic conditions, college students are divided into different types of groups in the traditional condition. However, with the development of the Internet, social networking in the college students has showed an unprecedented development momentum. Thus the contacts between students also become closely, which emerges with the new features of the social group of college students. Notably, in this situation, traditional group classification methods have been unable to meet the requirement of the student management work in the age of the Internet. Researching the characteristics of the students under the background of Internet with the new classification techniques, contributes to the scientific education and management of college students and enhances the effectiveness of Ideological and political work. Therefore, in the Internet plus age, it is the hotspot issue of common concern and exploration in the aspect of university organization and management. Complex network theory and social network analysis are inseparable. What’s more, community structure directly reflects the nature of the relationship between social network connections. Learning about the network structures of society can help to master the network topology structure and facilitate the management and utilization of the network.We firstly analyze the social network influence on college students, and present a new classification method for college student groups based on social network under the age of the Internet. Then, obtaining the real dataset of students’QQ relationship and WeChat relationship through the questionnaire on hand. With the improved community partition algorithm, we carry on the group’s type division to these connection relationships and get the corresponding student community structure. It is gratifying that we find a series of students with special relationship. So we analysis the characteristic of community for students and validate further. Our results provide useful guidance and help for the management and education of college students. All of our work are based on the counselor work. To a more deep illustration, our contributions are as follows:(1) The human reality relationships can map in the social network, and vice versa. Through the interactions of college students in the social network, we can dig out the nature of students’connections. And further, getting some implicit connections and characteristics that may not easily find in the management work.(2) We get the students’private social network information on a voluntary basis through the questionnaire on hand. After the above process, we build the social network database of students and evaluate data in the database. Then, pick out the useful data and apply the data to the theoretical analysis.(3) With the improved algorithm based on similarity of edge, we carry on the division to the student groups. And many implicit relationships can be found by using graph analysis in this process. We get special student groups’ behavior and representation characteristics based on the analysis of college students’ association status. Meanwhile, with the existing theory, we explore some new methods for student management, which is convenient for the managers control the students’ information more efficiently and accurately.In this paper, we connect the actual management work with the complex network theory, and innovatively put forward a new method for community classification. As a result, through group characteristics analysis and performance evaluation on experiments performed on the real-world dataset demonstrate our scheme indeed accord with our proposed design goals. Not only can it enhance the scientific management of students and the ideological and political education, but also makes a good job in the education work for the managers of colleges.