The Recognition Of The Niche Experts And The Stability Study Of Its' Group In The Social Network

The creation and development of web2.0 technology has promoted the rapid development of the social platforms,such as the interactive question and answer platform,blogs,BBS and so on.Various types of social platforms have drawn tons of attention from people.Along with the rapid growth of the number of social networking platform users,the value of social networking platforms were deeply digged.The popularization of smart phones and the breakthrough of mobile Internet technology has made the development of the social platform grow rapidly in mobile marketplaces.Nowadays,social platforms play an increasingly significant role in our daily life,for example on marketing,public opinion guidance,knowledge-sharing,carrying out open government affairs,emergency responses,etc.Social platforms have become the indispensable information source,more and more young people tend to get the latest information from social platforms.Users interact and communicate with each other on social platforms.Social platforms and the users constitute a complex network in which the users are the nodes and the communication with others are the edges.The network is called a social network.The activeness of users in social networks are different from each other which means the degree of nodes in the network are different from the viewpoint of complex network theory.A node's degree equals the number of edges associated with it.In addition to the degree,a node's betweenness is also a very important index in a social network which indicates the ratio of the number of shortest paths that passed the node and the number of all the shortest paths in the network.The higher the degree and the betweenness of a node is,the more important it is in the network.That means the node plays a critical role in the information spreading through the network.This article study the experts in social networks which are called "niche experts"."Niche experts" are very active in social networks.They interacted frequently with other users and gained the trust of a large number of users,they also play an important role in information transmission,knowledge sharing,public opinion guidance.Most of the existing expert identification studies are based on the academic resources or academic platforms which ignore the expert users in social networks.So this paper views the expert users in social networks as the research object aiming to complete the results of experts recognition as well as to improve the efficiency of knowledge sharing,information spreading,public opinion guidance in social network by making full use of the key nodes.The charactics of "niche experts" group are frequent interactions with other users and the high degree number and betweenness in social networks within the domain.In this paper,the author designed the method that recognits "niche experts" based on the weight in social networks which is got using complex network analysis softwares according to the degree and the betweenness.Having recognited the "niche experts"group we need to calculate the weights of "niche expertsts" again based on time weight to distinguish the earlier "niche experts" nodes and the new "niche experts" nodes.This article also explored the stability of "niche experts" when the time and the semantic environment changes using clustering analysis method and divided "niche experts" into finer groups.The experimental data of this paper is the users relationships data of MetaFilter-a famous blog community in America-from 2007 to 2016.The social networks were built using a complex network analysis software Pajek and the ranking of weights were got using VOSviewer.The "niche experts" were recognited with these steps.Through clustering analysis I found that the "niche expert" group was instable over time and the semantic environment changes.In terms of the results of this paper,about 10%of the "niche experts" users can maintain stability over time and about 11%of the "niche experts" users were able to keep the place of core users under more than two semantic environments.Experts recognition needs to pay attention to the core experts of "niche experts" for high-quality experts group considering the instability of "niche experts".