Universiteit Leiden ICT in Business
نویسنده
چکیده
Citation analysis is the quantitative study of science and technology based on publicationreference relationships. Currently, all references are assumed to make equal contribution to the citing publication, but as we all know this is not the case. To qualify this difference, the term “reference importance” is used to represent the amount of contribution that the reference makes to the citing publication. According to the previous studies, some citation features can be used to estimate the importance of references. In this thesis, the citation features that have been discussed in detail include: citation frequency, citing location, treatment, and selfcitation. Based on these features, a model that can measure the important of references was designed. This model takes the full text of scientific publications as input, and predicts the reference importance after examining citation frequency, citing location, treatment, and selfcitation of each reference. The model has been validated by the author-rated importance of references which was collected through individualized web-based surveys. With the reference importance, the performance and accuracy of citation analysis can be improved. For example, it can be used to better analyze the structure and development of scientific fields, and to develop new citation impact indicators that more accurately evaluate scientific performance. In this thesis, we use the reference importance to reduce the size of citation networks. We expect that the reduced citation networks will contain less noise than the original one.
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