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  • 1.
    Ahlgren, Per
    et al.
    School of Education and Communication in Engineering Sciences (ECE), KTH Royal Institute of Technology, Sweden.
    Colliander, Cristian
    Umeå University, Faculty of Social Sciences, Department of Sociology. Umeå University, Umeå University Library.
    Sjögårde, Peter
    School of Education and Communication in Engineering Sciences (ECE), KTH Royal Institute of Technology, Sweden; Department of ALM, Uppsala University, Uppsala, Sweden.
    Exploring the Relation Between Referencing Practices and Citation Impact: A Large-Scale Study Based on Web of Science Data2018In: Journal of the Association for Information Science and Technology, ISSN 2330-1635, E-ISSN 2330-1643, Vol. 69, no 5, p. 728-743Article in journal (Refereed)
    Abstract [en]

    In this large-scale contribution, we deal with the relationship between properties of cited references of Web of Science articles and the field normalized citation rate of these articles. Using nearly 1 million articles, and three classification systems with different levels of granularity, we study the effects of number of cited references, share of references covered by Web of Science, mean age of references and mean citation rate of references on field normalized citation rate. To expose the relationship between the predictor variables and the response variable, we use quantile regression. We found that a higher number of references, a higher share of references to publications within Web of Science and references to more recent publications correlate with citation impact. A correlation was observed even when normalization was done with a finely grained classification system. The predictor variables affected citation impact to a larger extent at higher quantile levels. Regarding the relative importance of the predictor variables, citation impact of the cited references was in general the least important variable. Number of cited references carried most of the importance for both low and medium quantile levels, but this importance was lessened at the highest considered level.

  • 2.
    Bohlin, Ludvig
    et al.
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Viamontes Esquivel, Alcides
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Lancichinetti, Andrea
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Rosvall, Martin
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Robustness of journal rankings by network flows with different amounts of memory2016In: Journal of the Association for Information Science and Technology, ISSN 2330-1635, E-ISSN 2330-1643, Vol. 67, no 10, p. 2527-2535Article in journal (Refereed)
    Abstract [en]

    As the number of scientific journals has multiplied, journal rankings have become increasingly important for scientific decisions. From submissions and subscriptions to grants and hirings, researchers, policy makers, and funding agencies make important decisions influenced by journal rankings such as the ISI journal impact factor. Typically, the rankings are derived from the citation network between a selection of journals and unavoidably depend on this selection. However, little is known about how robust rankings are to the selection of included journals. We compare the robustness of three journal rankings based on network flows induced on citation networks. They model pathways of researchers navigating the scholarly literature, stepping between journals and remembering their previous steps to different degrees: zero-step memory as impact factor, one-step memory as Eigenfactor, and two-step memory, corresponding to zero-, first-, and second-order Markov models of citation flow between journals. We conclude that higher-order Markov models perform better and are more robust to the selection of journals. Whereas our analysis indicates that higher-order models perform better, the performance gain for higher-order Markov models comes at the cost of requiring more citation data over a longer time period.

  • 3.
    Colliander, Cristian
    Umeå University, Faculty of Social Sciences, Department of Sociology.
    A novel approach to citation normalization: a similarity-based method for creating reference sets2015In: Journal of the Association for Information Science and Technology, ISSN 2330-1635, E-ISSN 2330-1643, Vol. 66, no 3, p. 489-500Article in journal (Refereed)
    Abstract [en]

    A similarity-oriented approach for deriving reference values used in citation normalization is explored and contrasted with the dominant approach of utilizing database-defined journal sets as a basis for deriving such values. In the similarity-oriented approach, an assessed article's raw citation count is compared with a reference value that is derived from a reference set, which is constructed in such a way that articles in this set are estimated to address a subject matter similar to that of the assessed article. This estimation is based on second-order similarity and utilizes a combination of 2 feature sets: bibliographic references and technical terminology. The contribution of an article in a given reference set to the reference value is dependent on its degree of similarity to the assessed article. It is shown that reference values calculated by the similarity-oriented approach are considerably better at predicting the assessed articles' citation count compared to the reference values given by the journal-set approach, thus significantly reducing the variability in the observed citation distribution that stems from the variability in the articles' addressed subject matter.

  • 4.
    Riviera, Emanuela
    Umeå University, Faculty of Social Sciences, Department of Sociology.
    Testing the Strength of the Normative Approach in Citation Theory Through Relational Bibliometrics: The Case of Italian Sociology2015In: Journal of the Association for Information Science and Technology, ISSN 2330-1635, E-ISSN 2330-1643, Vol. 66, no 6, p. 1178-1188Article in journal (Refereed)
    Abstract [en]

    In scientometrics, citer behavior is traditionally investigated using one of two main approaches. According to the normative point of view, the behavior of scientists is regulated by norms that make the detection of citation patterns useful for the interpretation of bibliometric measures. According to the constructivist perspective, citer behavior is influenced by other factors linked to the social and/or psychological sphere that do not allow any statistical inferences that are useful for the purposes of interpretation. An intermediate position supports normative theories in describing citer behavior with respect to high citation frequencies and constructivist theories with respect to low citation counts. In this paper, this idea was tested in a case study of the Italian sociology community. Italian sociology is characterized by an unusual organization into three political or ideological camps, and belonging to one camp can be considered a potentially strong constructivist reason to cite. An all-author co-citation analysis was performed to map the structure of the Italian sociology community and look for evidence of three camps. We did not expect to find evidence of this configuration in the co-citation map. The map, in fact, included authors who obtained high citation counts that are supposedly produced by a normative-oriented behavior. The results confirmed this hypothesis and showed that the clusters seemed to be divided according to topic and not by camp. Relevant scientific works were cited by the members of the entire community regardless of their membership in any particular camp.

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