Citation contexts as a data source for evaluation of scholarly consumption

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441579" target="_blank" >RIV/00216208:11320/21:10441579 - isvavai.cz</a>

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=U9y.2W0GDK" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=U9y.2W0GDK</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11192-021-04165-w" target="_blank" >10.1007/s11192-021-04165-w</a>

Result language

angličtina

Original language name

Citation contexts as a data source for evaluation of scholarly consumption

Original language description

In recent years, large datasets of citation contexts from research publications have become available for scientometric studies. Such citation contexts contain different characteristics of relationships between citing and cited papers, including information about publications that were in some way used by citing authors, about the motivations of this use, etc. Some of these characteristics can be considered as indicators of scholarly consumption of the citing authors. Based on the citation contexts data, the scholarly consumption can be characterized by four indicators: (a) data on cited (consumed) publications and their authors (suppliers); (b) types of scholarly consumption; (c) its thematics; and (d) temporary changes in these data. The indicators can be grouped and merged in various ways based on belonging to common citation contexts and/or on the coincidence of their values. By this way, one can create datasets for various objects and tasks of scientometric evaluation of scholarly consumption. The article proposes a general approach for building the scholarly consumption indicators, and presents the results of the experiments on evaluating a thematic structure of scholarly consumption. For this, thematically significant groups of words (topics) were selected from the citation contexts by using the LDA topic modeling method. Topics are obtained from the citation contexts for three groups of publications: (1) publications of a given author, (2) publications cited by a given author (suppliers), and (3) publications citing a given author (consumers). Thematic structures of scholarly consumption for a given author, as well as for his suppliers and consumers have been built. The features of the thematic structure representation in the forms of a tree of words and a flowchart are considered.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Scientometrics

ISSN

0138-9130

e-ISSN

1588-2861

Volume of the periodical

126

Issue of the periodical within the volume

11

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

17

Pages from-to

9249-9265

UT code for WoS article

000699882500003

EID of the result in the Scopus database

2-s2.0-85115731009