Author Influence Spreading Prediction Based on Co-Citation Interest Similarity

In the previous research, the assessment of author's influence is mainly based on the historical information of literature, such as the number of author's publications and times cited, and the reference relationship. However, the author influence is not only reflected in the amount of static data, but also in the behavior that the author's point of view is noticed and communicated. Meanwhile, the influence spreads through the relational path of cooperation and citation between authors, on which the authors should have similar academic interests. Therefore, this paper proposed an influence spreading model with the author's co-citation interest similarity and the path of citation and cooperation. On the basis of this, a novel algorithm of influence spreading prediction is designed, and carried on the experiment verification using the public literature information resources. The results of AUC indicator show the effectiveness on the proposed method

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