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  • × theme_ss:"Citation indexing"
  1. Kostoff, R.N.; Rio, J.A. del; Humenik, J.A.; Garcia, E.O.; Ramirez, A.M.: Citation mining : integrating text mining and bibliometrics for research user profiling (2001) 0.00
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    Abstract
    Identifying the users and impact of research is important for research performers, managers, evaluators, and sponsors. It is important to know whether the audience reached is the audience desired. It is useful to understand the technical characteristics of the other research/development/applications impacted by the originating research, and to understand other characteristics (names, organizations, countries) of the users impacted by the research. Because of the many indirect pathways through which fundamental research can impact applications, identifying the user audience and the research impacts can be very complex and time consuming. The purpose of this article is to describe a novel approach for identifying the pathways through which research can impact other research, technology development, and applications, and to identify the technical and infrastructure characteristics of the user population. A novel literature-based approach was developed to identify the user community and its characteristics. The research performed is characterized by one or more articles accessed by the Science Citation Index (SCI) database, beccause the SCI's citation-based structure enables the capability to perform citation studies easily. The user community is characterized by the articles in the SCI that cite the original research articles, and that cite the succeeding generations of these articles as well. Text mining is performed on the citing articles to identify the technical areas impacted by the research, the relationships among these technical areas, and relationships among the technical areas and the infrastructure (authors, journals, organizations). A key component of text mining, concept clustering, was used to provide both a taxonomy of the citing articles' technical themes and further technical insights based on theme relationships arising from the grouping process. Bibliometrics is performed on the citing articles to profile the user characteristics. Citation Mining, this integration of citation bibliometrics and text mining, is applied to the 307 first generation citing articles of a fundamental physics article on the dynamics of vibrating sand-piles. Most of the 307 citing articles were basic research whose main themes were aligned with those of the cited article. However, about 20% of the citing articles were research or development in other disciplines, or development within the same discipline. The text mining alone identified the intradiscipline applications and extradiscipline impacts and applications; this was confirmed by detailed reading of the 307 abstracts. The combination of citation bibliometrics and text mining provides a synergy unavailable with each approach taken independently. Furthermore, text mining is a REQUIREMENT for a feasible comprehensive research impact determination. The integrated multigeneration citation analysis required for broad research impact determination of highly cited articles will produce thousands or tens or hundreds of thousands of citing article Abstracts.
  2. Bornmann, L.; Daniel, H.-D.: Selecting manuscripts for a high-impact journal through peer review : a citation analysis of communications that were accepted by Angewandte Chemie International Edition, or rejected but published elsewhere (2008) 0.00
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    Abstract
    All journals that use peer review have to deal with the following question: Does the peer review system fulfill its declared objective to select the best scientific work? We investigated the journal peer-review process at Angewandte Chemie International Edition (AC-IE), one of the prime chemistry journals worldwide, and conducted a citation analysis for Communications that were accepted by the journal (n = 878) or rejected but published elsewhere (n = 959). The results of negative binomial-regression models show that holding all other model variables constant, being accepted by AC-IE increases the expected number of citations by up to 50%. A comparison of average citation counts (with 95% confidence intervals) of accepted and rejected (but published elsewhere) Communications with international scientific reference standards was undertaken. As reference standards, (a) mean citation counts for the journal set provided by Thomson Reuters corresponding to the field chemistry and (b) specific reference standards that refer to the subject areas of Chemical Abstracts were used. When compared to reference standards, the mean impact on chemical research is for the most part far above average not only for accepted Communications but also for rejected (but published elsewhere) Communications. However, average and below-average scientific impact is to be expected significantly less frequently for accepted Communications than for rejected Communications. All in all, the results of this study confirm that peer review at AC-IE is able to select the best scientific work with the highest impact on chemical research.
    Content
    Vgl. auch: Erratum Re: Selecting manuscripts for a high-impact journal through peer review: A citation analysis of communications that were accepted by Agewandte Chemie International Edition, or rejected but published elsewhere. In: Journal of the American Society for Information Science and Technology 59(2008) no.12, S.2037-2038.
  3. Huang, S.; Qian, J.; Huang, Y.; Lu, W.; Bu, Y.; Yang, J.; Cheng, Q.: Disclosing the relationship between citation structure and future impact of a publication (2022) 0.00
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    Abstract
    Each section header of an article has its distinct communicative function. Citations from distinct sections may be different regarding citing motivation. In this paper, we grouped section headers with similar functions as a structural function and defined the distribution of citations from structural functions for a paper as its citation structure. We aim to explore the relationship between citation structure and the future impact of a publication and disclose the relative importance among citations from different structural functions. Specifically, we proposed two citation counting methods and a citation life cycle identification method, by which the regression data were built. Subsequently, we employed a ridge regression model to predict the future impact of the paper and analyzed the relative weights of regressors. Based on documents collected from the Association for Computational Linguistics Anthology website, our empirical experiments disclosed that functional structure features improve the prediction accuracy of citation count prediction and that there exist differences among citations from different structural functions. Specifically, at the early stage of citation lifetime, citations from Introduction and Method are particularly important for perceiving future impact of papers, and citations from Result and Conclusion are also vital. However, early accumulation of citations from the Background seems less important.

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