Research On The Structure And Influence Of University Knowledge Network Based On Weibo Interconnection

In recent years,with the rapid development of Weibo and other new forms of media,universities and other higher education institutions in China have also actively participated in opening Weibo accounts and carrying out new media building work.Weibo has now basically replaced traditional websites,forums and so on.It has become a new platform for universities to release information,take part in social interactions and carry out work,and has played a crucial role in the information exchange activities in universities.University Weibo is the key development area of universities under the new media era,whose Weibo influence often reflects the comprehensive level of these universities.However,Weibo,this virtual social network form,differs from traditional ones in its influence evaluation indicators.In this case,it is a necessity to study the network structure and influence evaluation indicators of universities' Weibo information exchange activities.This paper takes the 132 Weibo users of "Double First-Class"(namely world-class universities and first-class disciplines)universities as the research objects,uses Python to write Web crawler to collect data,builds a relation matrix,and uses Ucinet and other social network analysis software.By doing so,the network structure is analyzed through three levels,the whole,sub-groups,and individuals so as to explore the structural characteristics of the Weibo interconnection network in universities.Based on the above,the features of the fans and posting numbers are combined and analyzed to establish the influence transfer matrix and a weighted influence evaluation model is built up through the improvement of the LeaderRank algorithm.Then iteratively calculate the influence of each university's Weibo,and then get the specific rankings of university Weibo influence.After analysis,the result obtained shows that the Weibo interconnection network in universities generally has a tight connection.This kind of network structure provides a good environment for the rapid flow of knowledge in university Weibo networks.There is strong cohesion among universities' Weibo but also node with obvious leaders'opinions,but it is still necessary for universities to continue to strengthen ties among their Weibo,and actively participate in Weibo activities to further increase the level of mutual knowledge sharing.In addition,through the improvement of the LeaderRank algorithm,the specific scores and rankings of the universities' Weibo influence are acquired.The distribution of the scores shows the power law distribution characteristics,which is more in line with the distribution characteristics of Weibo users' influence.This paper researches the Weibo interconnection network in universities and offers suggestions for the user behaviors and interactions among universities and other institutions in the social media platform under the new media era,provides the necessary theoretical basis for optimizing the Weibo network structure,enhancing the Weibo influence of universities and promoting knowledge sharing among universities.It is expected to further promote the development of information technology in universities and improve China's comprehensive strength in the field of higher education.