Journal of Information Science
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Analysis of direct citation, co-citation and bibliographic coupling in scientific topic identification In our study, we examine the impact of citation network structures on the ability to discern valuable research topics in Computer Science literature. We use the bibliographic information available in the DBLP database to extract candidate phrases from scientific paper abstracts. Following that, we construct citation networks based on direct citation, co-citation and bibliographic coupling relationships between the papers. The candidate research topics, in the form of keyphrases and n-grammes, are subsequently ranked and filtered by a graph-text ranking algorithm. This selection of the highest ranked potential topics is further evaluated by domain experts and through the Wikipedia knowledge base. The results obtained from these citation networks are complementary, returning valid but non-overlapping output phrases between some pairs of networks. In particular, bibliographic coupling appears to capture more unique information than either direct citation or co-citation. These findings point towards the possible added value in combining bibliographic coupling analysis with other structures. At the same time, combining direct citation and co-citation is put into question. We expect our findings to be utilised in method design for research topic identification.
Journal of Information Science - Tập 48 Số 3 - Trang 349-373 - 2022
Can organizational knowledge capabilities affect knowledge sharing behavior? Recent concerns about the issue of knowledge management (KM) within an organization have accentuated the need for more efficient and effective knowledge sharing - that is, knowledge sharing plays an increasingly significant role in determining the outcomes of KM. Most scholars explore this issue from the economic perspective, while only a few research studies have focussed on organizational capabilities. Drawing from the theories of resource-based view and KM, this study aims to investigate the relationship between organizational knowledge capabilities (OKC) and knowledge sharing (KS). Using regression analysis with data from questionnaires collected in different industries with a valid response rate of 62.4%, the results show that OKC have a positive association with KS. Technical, structural, and human knowledge capabilities are significant for organizational knowledge sharing. Moreover, the effects of implementing KM on OKC and KS are also significant.
Journal of Information Science - Tập 33 Số 1 - Trang 95-109 - 2007
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