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Colliander, CristianORCID iD iconorcid.org/0000-0002-7653-4004
Publications (10 of 11) Show all publications
Colliander, C. & Ahlgren, P. (2019). Comparison of publication-level approaches to ex-post citation normalization. Scientometrics, 120(1), 283-300
Open this publication in new window or tab >>Comparison of publication-level approaches to ex-post citation normalization
2019 (English)In: Scientometrics, ISSN 0138-9130, E-ISSN 1588-2861, Vol. 120, no 1, p. 283-300Article in journal (Refereed) Published
Abstract [en]

In this paper, we compare two sophisticated publication-level approaches to ex-post citation normalization: an item-oriented approach and an approach falling under the general algorithmically constructed classification system approach. Using articles published in core journals in Web of Science (SCIE, SSCI & A&HCI) during 2009 (n=955,639), we first examine, using the measure Proportion explained variation (PEV), to what extent the publication-level approaches can explain and correct for variation in the citation distribution that stems from subject matter heterogeneity. We then, for the subset of articles from life science and biomedicine (n=456,045), gauge the fairness of the normalization approaches with respect to their ability to identify highly cited articles when subject area is factored out. This is done by utilizing information from publication-level MeSH classifications to create high quality subject matter baselines and by using the measure Deviations from expectations (DE). The results show that the item-oriented approach had the best performance regarding PEV. For DE, only the most fine-grained clustering solution could compete with the item-oriented approach. However, the item-oriented approach performed better when cited references were heavily weighted in the similarity calculations.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Algorithmically constructed classification system approach, Citation impact, Field normalization, Item-oriented approach, Research evaluation
National Category
Information Studies
Identifiers
urn:nbn:se:umu:diva-159084 (URN)10.1007/s11192-019-03121-z (DOI)000471656400014 ()
Available from: 2019-05-17 Created: 2019-05-17 Last updated: 2019-07-12Bibliographically approved
Ahlgren, P., Colliander, C. & Sjögårde, P. (2018). Exploring the Relation Between Referencing Practices and Citation Impact: A Large-Scale Study Based on Web of Science Data. Journal of the Association for Information Science and Technology, 69(5), 728-743
Open this publication in new window or tab >>Exploring the Relation Between Referencing Practices and Citation Impact: A Large-Scale Study Based on Web of Science Data
2018 (English)In: 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) Published
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.

Keywords
bibliometrics; reference practices; citation analysis; citation normalization; quantile regression
National Category
Information Studies
Identifiers
urn:nbn:se:umu:diva-142719 (URN)10.1002/asi.23986 (DOI)
Available from: 2017-12-08 Created: 2017-12-08 Last updated: 2018-06-09Bibliographically approved
Jarlbrink, J., Snickars, P. & Colliander, C. (2016). Maskinläsning: om massdigitalisering, digitala metoder och svensk dagspress. Nordicom Information, 38(3), 27-40
Open this publication in new window or tab >>Maskinläsning: om massdigitalisering, digitala metoder och svensk dagspress
2016 (Swedish)In: Nordicom Information, ISSN 0349-5949, Vol. 38, no 3, p. 27-40Article in journal (Refereed) Published
Abstract [en]

This article highlights the media historical possibilities to analyse linguistic patterns in massive amounts of texts using digital methods. Our starting point is the fact that The National Library of Sweden has made over 12 million newspaper pages available in digital format. An important question is how to research them. The article presents a media history of the Swedish newspaper digitisation, as well as new ways of conducting historical newspaper research using digital methods. A case study is presented where the conceptualisation of a new media technology (the internet) in newspapers from the 1990s is tracked with a digital tool searching for word co-occurrences. The possibilities of digital methods are often incredible, but we should not underestimate the problematic aspects of using digital tools to explore digitised newspapers. The poor quality of the OCR (Optical Character Recognition) is described as one of the major challenges facing historical newspaper research in a digital environment

Place, publisher, year, edition, pages
Göteborg: Nordicom, 2016
Keywords
media history, digitized newspapers, OCR, digital humanities, text analysis
National Category
Media Studies Information Systems, Social aspects
Research subject
medie- och kommunikationsvetenskap
Identifiers
urn:nbn:se:umu:diva-129854 (URN)
Available from: 2017-01-09 Created: 2017-01-09 Last updated: 2018-06-09Bibliographically approved
Colliander, C. (2015). A novel approach to citation normalization: a similarity-based method for creating reference sets. Journal of the Association for Information Science and Technology, 66(3), 489-500
Open this publication in new window or tab >>A novel approach to citation normalization: a similarity-based method for creating reference sets
2015 (English)In: 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) Published
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.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2015
Keywords
bibliometrics, scientometrics, citation analysis, normalized citation impact, similarity measures
National Category
Information Studies
Research subject
biblioteks- och informationsvetenskap
Identifiers
urn:nbn:se:umu:diva-88877 (URN)10.1002/asi.23193 (DOI)000350100500005 ()
Available from: 2014-05-16 Created: 2014-05-16 Last updated: 2018-06-07Bibliographically approved
Lindahl, J., Stenling, A., Lindwall, M. & Colliander, C. (2015). Trends and knowledge base in sport and exercise psychology research: a bibliometric review study. International Review of Sport and Exercise Psychology, 8(1), 71-94
Open this publication in new window or tab >>Trends and knowledge base in sport and exercise psychology research: a bibliometric review study
2015 (English)In: International Review of Sport and Exercise Psychology, ISSN 1750-984X, E-ISSN 1750-9858, Vol. 8, no 1, p. 71-94Article in journal (Refereed) Published
Abstract [en]

Bibliometric methods were used to examine: (1) research themes in sport and exercise psychology articles published between 2008 and 2011; and (2) the intellectual base of the field of sport and exercise psychology, defined as influential literature being cited in these articles. The dataset consisted of 795 articles from five sport and exercise psychology journals and 345 articles obtained through citation-based extension (n = 1140 articles). A cluster analysis yielded 73 clusters showing themes in sport and exercise psychology research. Principal component analysis was used to identify and analyze relationships between 14 highly cited research areas constituting the intellectual base of sport and exercise psychology. Some main findings were: (1) the identification of many re-emerging themes, (2) research related to motivation seems to be extensive, (3) sport psychology and exercise psychology research share theoretical frameworks to some extent, however (4) differences compared to previous reviews indicate that sport psychology and exercise psychology may be regarded as two distinct research fields, rather than one united field, and (5) isolated research areas were identified indicating potential for research integration. Suggestions for future research are provided. The bibliometric approach presented a broad overview of trends and knowledge base in sport and exercise psychology research.

Place, publisher, year, edition, pages
Taylor & Francis, 2015
Keywords
bibliometrics, review, sport and exercise psychology, author co-citation analysis, cluster analysis
National Category
Applied Psychology Information Studies
Identifiers
urn:nbn:se:umu:diva-105959 (URN)10.1080/1750984X.2015.1019540 (DOI)000370526200004 ()
Available from: 2015-07-02 Created: 2015-07-02 Last updated: 2018-06-07Bibliographically approved
Colliander, C. (2014). Science mapping and research evaluation: a novel methodology for creating normalized citation indicators and estimating their stability. (Doctoral dissertation). Umeå: Umeå universitet
Open this publication in new window or tab >>Science mapping and research evaluation: a novel methodology for creating normalized citation indicators and estimating their stability
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The purpose of this thesis is to contribute to the methodology at the intersection of relational and evaluative bibliometrics. Experimental investigations are presented that address the question of how we can most successfully produce estimates of the subject similarity between documents. The results from these investigations are then explored in the context of citation-based research evaluations in an effort to enhance existing citation normalization methods that are used to enable comparisons of subject-disparate documents with respect to their relative impact or perceived utility. This thesis also suggests and explores an approach for revealing the uncertainty and stability (or lack thereof) coupled with different kinds of citation indicators.This suggestion is motivated by the specific nature of the bibliographic data and the data collection process utilized in citation-based evaluation studies.

The results of these investigations suggest that similarity-detection methods that take a global view of the problem of identifying similar documents are more successful in solving the problem than conventional methods that are more local in scope. These results are important for all applications that require subject similarity estimates between documents. Here these insights are specifically adopted in an effort to create a novel citation normalization approach that – compared to current best practice – is more in tune with the idea of controlling for subject matter when thematically different documents are assessed with respect to impact or perceived utility. The normalization approach is flexible with respect to the size of the normalization baseline and enables a fuzzy partition of the scientific literature. It is shown that this approach is more successful than currently applied normalization approaches in reducing the variability in the observed citation distribution that stems from the variability in the articles’ addressed subject matter. In addition, the suggested approach can enhance the interpretability of normalized citation counts. Finally, the proposed method for assessing the stability of citation indicators stresses that small alterations that could be artifacts from the data collection and preparation steps can have a significant influence on the picture that is painted by the citationindicator. Therefore, providing stability intervals around derived indicators prevents unfounded conclusions that otherwise could have unwanted policy implications.

Together, the new normalization approach and the method for assessing the stability of citation indicators have the potential to enable fairer bibliometric evaluative exercises and more cautious interpretations of citation indicators.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2014. p. 37
Series
Akademiska avhandlingar vid Sociologiska institutionen, Umeå universitet, ISSN 1104-2508 ; 76
Keywords
document-document similarity, science mapping, citation analysis, citation normalization, stability analysis, citation impact, research evaluation
National Category
Social Sciences Interdisciplinary Information Studies
Research subject
biblioteks- och informationsvetenskap
Identifiers
urn:nbn:se:umu:diva-94189 (URN)978-91-7601-134-8 (ISBN)
Public defence
2014-10-31, Hörsal 1031, Norra Beteendevetarhuset, Umeå universitet, Umeå, 13:15 (English)
Opponent
Supervisors
Available from: 2014-10-10 Created: 2014-10-06 Last updated: 2018-06-07Bibliographically approved
Colliander, C. & Ahlgren, P. (2012). Experimental comparison of first and second-order similarities in a scientometric context. Scientometrics, 90(2), 675-685
Open this publication in new window or tab >>Experimental comparison of first and second-order similarities in a scientometric context
2012 (English)In: Scientometrics, ISSN 0138-9130, E-ISSN 1588-2861, Vol. 90, no 2, p. 675-685Article in journal (Refereed) Published
Abstract [en]

The measurement of similarity between objects plays a role in several scientific areas. In this article, we deal with document–document similarity in a scientometric context. We compare experimentally, using a large dataset, first-order with second-order similarities with respect to the overall quality of partitions of the dataset, where the partitions are obtained on the basis of optimizing weighted modularity. The quality of a partition is defined in terms of textual coherence. The results show that the second-order approach consistently outperforms the first-order approach. Each difference between the two approaches in overall partition quality values is significant at the 0.01 level.

Place, publisher, year, edition, pages
Budapest, Hungary: Akademiai Kiado, 2012
Keywords
Bibliographic coupling, Cluster analysis, Document–document similarity, Science mapping, Similarity order, Textual coherence
National Category
Other Computer and Information Science
Research subject
biblioteks- och informationsvetenskap
Identifiers
urn:nbn:se:umu:diva-46805 (URN)10.1007/s11192-011-0491-x (DOI)
Available from: 2011-09-15 Created: 2011-09-15 Last updated: 2018-06-08Bibliographically approved
Ahlgren, P., Colliander, C. & Persson, O. (2012). Field normalized citation rates, field normalized journal impact and Norwegian weights for allocation of university research funds. Scientometrics, 92(2), 767-780
Open this publication in new window or tab >>Field normalized citation rates, field normalized journal impact and Norwegian weights for allocation of university research funds
2012 (English)In: Scientometrics, ISSN 0138-9130, E-ISSN 1588-2861, Vol. 92, no 2, p. 767-780Article in journal (Refereed) Published
Abstract [en]

We compared three different bibliometric evaluation approaches: two citationbased approaches and one based on manual classification of publishing channels into quality levels. Publication data for two universities was used, and we worked with two levels of analysis: article and department. For the article level, we investigated the predictive power of field normalized citation rates and field normalized journal impact with respect to journal level. The results for the article level show that evaluation of journals based on citation impact correlate rather well with manual classification of journals into quality levels. However, the prediction from field normalized citation rates to journal level was only marginally better than random guessing. At the department level, we studied three different indicators in the context of research fund allocation within universities and the extent to which the three indicators produce different distributions of research funds. It turned out that the three distributions of relative indicator values were very similar, which in turn yields that the corresponding distributions of hypothetical research funds would be very similar.

Place, publisher, year, edition, pages
Springer, 2012
Keywords
Field normalized citation rates, Journal impact, Norwegian model, Research fund allocation
National Category
Other Computer and Information Science
Research subject
biblioteks- och informationsvetenskap
Identifiers
urn:nbn:se:umu:diva-51940 (URN)10.1007/s11192-012-0632-x (DOI)
Available from: 2012-02-05 Created: 2012-02-05 Last updated: 2018-06-08Bibliographically approved
Colliander, C. & Ahlgren, P. (2011). The effects and their stability of field normalization baseline on relative performance with respect to citation impact: a case study of 20 natural science departments. Journal of Informetrics, 5(1), 101-113
Open this publication in new window or tab >>The effects and their stability of field normalization baseline on relative performance with respect to citation impact: a case study of 20 natural science departments
2011 (English)In: Journal of Informetrics, ISSN 1751-1577, E-ISSN 1875-5879, Vol. 5, no 1, p. 101-113Article in journal (Refereed) Published
Abstract [en]

In this paper we study the effects of field normalization baseline on relative performance of 20 natural science departments in terms of citation impact. Impact is studied under three baselines: journal, ISI/Thomson Reuters subject category, and Essential Science Indicators field. For the measurement of citation impact, the indicators item-oriented mean normalized citation rate and Top-5% are employed. The results, which we analyze with respect to stability, show that the choice of normalization baseline matters. We observe that normalization against publishing journal is particular. The rankings of the departments obtained when journal is used as baseline, irrespective of indicator, differ considerably from the rankings obtained when ISI/Thomson Reuters subject category or Essential Science Indicators field is used. Since no substantial differences are observed when the baselines Essential Science Indicators field and ISI/Thomson Reuters subject category are contrasted, one might suggest that people without access to subject category data can perform reasonable normalized citation impact studies by combining normalization against journal with normalization against Essential Science Indicators field.

Keywords
bibliometrics, stability analysis, field normalization baseline, journal, ISI/Thomson Reuters subject category, Essential Science Indicators field, citation impact, scientometrics
National Category
Information Studies
Research subject
biblioteks- och informationsvetenskap
Identifiers
urn:nbn:se:umu:diva-37582 (URN)10.1016/j.joi.2010.09.003 (DOI)000285626000009 ()
Available from: 2010-11-09 Created: 2010-11-09 Last updated: 2018-06-08Bibliographically approved
Ahlgren, P. & Colliander, C. (2009). Document-document similarity approaches and science mapping: experimental comparison of five approaches. Journal of Informetrics, 3(1), 49-63
Open this publication in new window or tab >>Document-document similarity approaches and science mapping: experimental comparison of five approaches
2009 (English)In: Journal of Informetrics, ISSN 1751-1577, E-ISSN 1875-5879, Vol. 3, no 1, p. 49-63Article in journal (Refereed) Published
Abstract [en]

This paper treats document-document similarity approaches in the context of science mapping. Five approaches, involving nine methods, are compared experimentally. We compare text-based approaches, the citation-based bibliographic coupling approach, and approaches that combine text-based approaches and bibliographic coupling. Forty-three articles, published in the journal Information Retrieval, are used as test documents. We investigate how well the approaches agree with a ground truth subject classification of the test documents, when the complete linkage method is used, and under two types of similarities, first-order and second-order. The results show that it is possible to achieve a very good approximation of the classification by means of automatic grouping of articles. One text-only method and one combination method, under second-order similarities in both cases, give rise to cluster solutions that to a large extent agree with the classification.

Place, publisher, year, edition, pages
Elsevier BV, 2009
Keywords
Bibliometrics, Citation data, Text mining, Cluster analysis, Data source combination, Science mapping
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:umu:diva-37580 (URN)10.1016/j.joi.2008.11.003 (DOI)000262496700005 ()
Available from: 2010-11-09 Created: 2010-11-09 Last updated: 2018-06-08Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-7653-4004

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