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Conventional patent citation analyses have focused mainly on the presence of citation relationships, the number of patents cited by the subject patent, and the number of times the subject patent is cited by others (i.e., the numbers of backward and forward citations of the subject patent). However, most of them have not focused on patent classifications. Assuming that a patent based on a variety of technological bases tends to be an important patent that is cited more often, this study examines and clarifies the relationship between the diversity of classifications assigned to backward citations and the number of forward citations for Japanese patents. The results show notable differences in the number of classifications assigned to backward citations between the often cited and less frequently cited groups. It is considered that the diversity of backward citations can be utilized in the evaluation criteria for grouping that roughly identifies the often cited patents or eliminates a large part of less frequently cited patents.

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Many studies have analyzed “direct” partnerships in co-authorship networks. On the other hand, the global network structure, including “indirect” links between researchers, has not yet been sufficiently studied. This study analyzes researchers' activities from the viewpoints considering their roles in the global structures of co-authorship networks, and compares the co-authorship networks between the theoretical and application areas in computer science. The modified HITS algorithm is used to calculate the two types of importance of researchers in co-authorship networks, i.e., the importance as the leader and that as the follower.

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