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  1. Shibata, N.; Kajikawa, Y.; Takeda, Y.; Matsushima, K.: Comparative study on methods of detecting research fronts using different types of citation (2009) 0.03
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    Date
    22. 3.2009 17:52:50
    Language
    e
  2. Chen, L.; Fang, H.: ¬An automatic method for ex-tracting innovative ideas based on the Scopus® database (2019) 0.03
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    Abstract
    The novelty of knowledge claims in a research paper can be considered an evaluation criterion for papers to supplement citations. To provide a foundation for research evaluation from the perspective of innovativeness, we propose an automatic approach for extracting innovative ideas from the abstracts of technology and engineering papers. The approach extracts N-grams as candidates based on part-of-speech tagging and determines whether they are novel by checking the Scopus® database to determine whether they had ever been presented previously. Moreover, we discussed the distributions of innovative ideas in different abstract structures. To improve the performance by excluding noisy N-grams, a list of stopwords and a list of research description characteristics were developed. We selected abstracts of articles published from 2011 to 2017 with the topic of semantic analysis as the experimental texts. Excluding noisy N-grams, considering the distribution of innovative ideas in abstracts, and suitably combining N-grams can effectively improve the performance of automatic innovative idea extraction. Unlike co-word and co-citation analysis, innovative-idea extraction aims to identify the differences in a paper from all previously published papers.
    Language
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  3. Jacobs, N.; Woodfield, J.; Morris, A.: Using local citation data to relate the use of journal articles by academic researchers to the coverage of full-text document access systems (2000) 0.03
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  4. An, J.; Kim, N.; Kan, M.-Y.; Kumar Chandrasekaran, M.; Song, M.: Exploring characteristics of highly cited authors according to citation location and content (2017) 0.03
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    Language
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  5. Mulkay, M.J.: Sociology of the scientific research community (1977) 0.03
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    Language
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    Source
    Science, technology and society: a cross-disciplinary perspective. Ed: I. Spiegel-Rosing u. D. de Solla Price
  6. Schwens, U.: Feasibility of exploiting bibliometric data in European national bibliographic databases (1999) 0.03
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  7. Milard, B.: ¬The social circles behind scientific references : relationships between citing and cited authors in chemistry publications (2014) 0.03
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    Abstract
    This paper provides a better understanding of the implications of researchers' social networks in bibliographic references. Using a set of chemistry papers and conducting interviews with their authors (n = 32), I characterize the type of relation the author has with the authors of the references contained in his/her paper (n = 3,623). I show that citation relationships do not always involve underlying personal exchanges and that unknown references are an essential component, revealing segmentations in scientific groups. The relationships implied by references are of various strengths and origins. Several inclusive social circles are then identified: co-authors, close acquaintances, colleagues, invisible colleges, peers, contactables, and strangers. I conclude that publication is a device that contributes to a relatively stable distribution among the various social circles that structure scientific sociability.
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  8. Raan, A.F.J. van: Scaling rules in the science system : influence of field-specific citation characteristics on the impact of research groups (2008) 0.03
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    Date
    22. 3.2009 19:03:12
    Footnote
    Vgl. auch: Costas, R., M. Bordons u. T.N. van Leeuwen u.a.: Scaling rules in the science system: Influence of field-specific citation characteristics on the impact of individual researchers. In: Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.740-753.
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  9. Kaminer, N.; Braunstein, Y.M.: Bibliometric analysis of the impact of Internet use on scholarly productivity (1998) 0.03
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  10. Coulter, N.; Monarch, I.; Konda, S.: Software engineering as seen through its research literature : a study in co-word analysis (1998) 0.03
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  11. Qin, J.: Semantic patterns in bibliographically coupled documents (2002) 0.03
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    Abstract
    Different research fields have different definitions for semantic patterns. For knowledge discovery and representation, semantic patterns represent the distribution of occurrences of words in documents and/or citations. In the broadest sense, the term semantic patterns may also refer to the distribution of occurrences of subjects or topics as reflected in documents. The semantic pattern in a set of documents or a group of topics therefore implies quantitative indicators that describe the subject characteristics of the documents being examined. These characteristics are often described by frequencies of keyword occurrences, number of co-occurred keywords, occurrences of coword, and number of cocitations. There are many ways to analyze and derive semantic patterns in documents and citations. A typical example is text mining in full-text documents, a research topic that studies how to extract useful associations and patterns through clustering, categorizing, and summarizing words in texts. One unique way in library and information science is to discover semantic patterns through bibliographically coupled citations. The history of bibliographical coupling goes back in the early 1960s when Kassler investigated associations among technical reports and technical information flow patterns. A number of definitions may facilitate our understanding of bibliographic coupling: (1) bibliographic coupling determines meaningful relations between papers by a study of each paper's bibliography; (2) a unit of coupling is the functional bond between papers when they share a single reference item; (3) coupling strength shows the order of combinations of units of coupling into a graded scale between groups of papers; and (4) a coupling criterion is the way by which the coupling units are combined between two or more papers. Kessler's classic paper an bibliographic coupling between scientific papers proposes the following two graded criteria: Criterion A: A number of papers constitute a related group GA if each member of the group has at least one coupling unit to a given test paper P0. The coupling strength between P0 and any member of GA is measured by the number of coupling units n between them. G(subA)(supn) is that portion of GA that is linked to P0 through n coupling units; Criterion B: A number of papers constitute a related group GB if each member of the group has at least one coupling unit to every other member of the group.
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  12. García, J.A.; Rodríguez-Sánchez, R.; Fdez-Valdivia, J.; Robinson-García, N.; Torres-Salinas, D.: Mapping academic institutions according to their journal publication profile : Spanish universities as a case study (2012) 0.03
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  13. Ikae, C.; Savoy, J.: Gender identification on Twitter (2022) 0.03
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    Abstract
    To determine the author of a text's gender, various feature types have been suggested (e.g., function words, n-gram of letters, etc.) leading to a huge number of stylistic markers. To determine the target category, different machine learning models have been suggested (e.g., logistic regression, decision tree, k nearest-neighbors, support vector machine, naïve Bayes, neural networks, and random forest). In this study, our first objective is to know whether or not the same model always proposes the best effectiveness when considering similar corpora under the same conditions. Thus, based on 7 CLEF-PAN collections, this study analyzes the effectiveness of 10 different classifiers. Our second aim is to propose a 2-stage feature selection to reduce the feature size to a few hundred terms without any significant change in the performance level compared to approaches using all the attributes (increase of around 5% after applying the proposed feature selection). Based on our experiments, neural network or random forest tend, on average, to produce the highest effectiveness. Moreover, empirical evidence indicates that reducing the feature set size to around 300 without penalizing the effectiveness is possible. Finally, based on such reduced feature sizes, an analysis reveals some of the specific terms that clearly discriminate between the 2 genders.
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  14. Fairthorne, R.A.: Bradford's law and perspective (1980) 0.02
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    Source
    Theory and application of information research. Proc. of the 2nd Int. Research Forum on Information Science, 3.-6.8.1977, Copenhagen. Ed.: O. Harbo u. L. Kajberg
  15. Schoepflin, U.; Glänzel, W.: Mehrwert von bibliographischen Datenbanken (1994) 0.02
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  16. Leydesdorff, L.: Dynamic and evolutionary updates of classificatory schemes in scientific journal structures (2002) 0.02
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    Abstract
    Can the inclusion of new journals in the Science Citation Index be used for the indication of structural change in the database, and how can this change be compared with reorganizations of reiations among previously included journals? Change in the number of journals (n) is distinguished from change in the number of journal categories (m). Although the number of journals can be considered as a given at each moment in time, the number of journal categories is based an a reconstruction that is time-stamped ex post. The reflexive reconstruction is in need of an update when new information becomes available in a next year. Implications of this shift towards an evolutionary perspective are specified.
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  17. Payne, N.; Thelwall, M.: Mathematical models for academic webs : linear relationship or non-linear power law? (2005) 0.02
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  18. Shi, D.; Rousseau, R.; Yang, L.; Li, J.: ¬A journal's impact factor is influenced by changes in publication delays of citing journals (2017) 0.02
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    Abstract
    In this article we describe another problem with journal impact factors by showing that one journal's impact factor is dependent on other journals' publication delays. The proposed theoretical model predicts a monotonically decreasing function of the impact factor as a function of publication delay, on condition that the citation curve of the journal is monotone increasing during the publication window used in the calculation of the journal impact factor; otherwise, this function has a reversed U shape. Our findings based on simulations are verified by examining three journals in the information sciences: the Journal of Informetrics, Scientometrics, and the Journal of the Association for Information Science and Technology.
    Language
    e
  19. Bornmann, L.; Schier, H.; Marx, W.; Daniel, H.-D.: Is interactive open access publishing able to identify high-impact submissions? : a study on the predictive validity of Atmospheric Chemistry and Physics by using percentile rank classes (2011) 0.02
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    Abstract
    In a comprehensive research project, we investigated the predictive validity of selection decisions and reviewers' ratings at the open access journal Atmospheric Chemistry and Physics (ACP). ACP is a high-impact journal publishing papers on the Earth's atmosphere and the underlying chemical and physical processes. Scientific journals have to deal with the following question concerning the predictive validity: Are in fact the "best" scientific works selected from the manuscripts submitted? In this study we examined whether selecting the "best" manuscripts means selecting papers that after publication show top citation performance as compared to other papers in this research area. First, we appraised the citation impact of later published manuscripts based on the percentile citedness rank classes of the population distribution (scaling in a specific subfield). Second, we analyzed the association between the decisions (n = 677 accepted or rejected, but published elsewhere manuscripts) or ratings (reviewers' ratings for n = 315 manuscripts), respectively, and the citation impact classes of the manuscripts. The results confirm the predictive validity of the ACP peer review system.
    Language
    e
  20. Onodera, N.; Iwasawa, M.; Midorikawa, N.; Yoshikane, F.; Amano, K.; Ootani, Y.; Kodama, T.; Kiyama, Y.; Tsunoda, H.; Yamazaki, S.: ¬A method for eliminating articles by homonymous authors from the large number of articles retrieved by author search (2011) 0.02
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    e

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