Identifying opinion leader nodes in online social networks with a new closeness evaluation algorithm
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In online social networks, there are some influential opinion leader nodes who can be used to accelerate the spread of positive information and suppress the diffusion of rumors. If these opinion leaders can be identified timely and correctly, there will be contributing to guide the popular opinions. The closeness is introduced for mapping the relationship between the nodes according to the different interaction types in online social network. In order to measure the impact of the information transmission between non-adjacent nodes in online social networks, a closeness evaluating algorithm of the adjacent nodes and the non-adjacent nodes is given based on the relational features between users. By using the algorithm, the closeness between the adjacent nodes and the non-adjacent nodes can obtained depending on the interaction time of nodes and the delay of their hops. Furthermore, a more accurate and efficient betweenness centrality scheme based on the optimized algorithm with the degree of closeness and the corresponding updating strategy. The opinion leader nodes should be identified more accurately and efficiently under the improved algorithm because the considering of closeness between nodes in the network. Finally, the maximum spreading experiment is done for comparing the proposed method with other existing identifying opinion leader selecting schemes based on the Independent Cascade Model. The result of experiment shows the effectiveness and practicality of the evaluating algorithm.
KeywordsSocial networks Closeness Independent cascade Opinion leader nodes
We would like to thank the anonymous reviewers for their careful reading and useful comments. This work was supported by the National Natural Science Foundation of China (U1405255, 61202390), the China 111 Project (B16037), the Foundation of Science and Technology on Information Assurance Laboratory (KJ-14-109) and the Fundamental Research Funds for the Central Universities (JB161505).
Compliance with ethical standards
Conflict of interest
Li Yang, Yafeng Qiao, Zhihong Liu, Jianfeng Ma and Xinghua Li declare that there are no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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