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This study provides a longitudinal scientometric analysis of global trypanosomiasis research between 1988 and 2017 as indexed in Clarivate Analytics' Web of Science (WoS). Contributions by researchers from different countries and continents are outlined based on publication productivity, international collaborations, citation analysis, and keyword analysis. Bibliographic records of research publications indexed by WoS were downloaded based on a broad search of related terms. The authors compared the growth of literature by continent using 5-year increments, conducted a citation and co-authorship analysis by country, and a keyword analysis by publication using the scientometric visualization software VOSviewer. The trypanosomiasis research literature has seen more than a fourfold annual increase in production over the study period. Contributions by authors affiliated with European and South American countries proportionately account for the most research literature. The United States and Brazil, however, occupy central roles for citations and as national contributors to the literature. The terms 'trypanosomiasis cruzi' and 'chagas disease' have become more prominent, reflecting the regional growth of research from South America. Relative contributions from regions where the disease is prevalent show mixed developments. Contributions by African authors have declined proportionately to other areas of the world. However, South American contributions have increased during the study period. The contributing countries to the literature do not necessarily represent regions in which the diseases are prevalent. The same is true of the citation relationships, where European and North American contributions are more frequently cited. [ABSTRACT FROM AUTHOR]

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Data citation, where products of research such as data sets, software, and tissue cultures are shared and acknowledged, is becoming more common in the era of Open Science. Currently, the practice of formal data citation—where data references are included alongside bibliographic references in the reference section of a publication—is uncommon. We examine the prevalence of data citation, documenting data sharing and reuse, in a sample of full text articles from the biological/biomedical sciences, the fields with the most public data sets available documented by the Data Citation Index (DCI). We develop a method that combines automated text extraction with human assessment for revealing candidate occurrences of data sharing and reuse by using terms that are most likely to indicate their occurrence. The analysis reveals that informal data citation in the main text of articles is far more common than formal data citations in the references of articles. As a result, data sharers do not receive documented credit for their data contributions in a similar way as authors do for their research articles because informal data citations are not recorded in sources such as the DCI. Ongoing challenges for the study of data citation are also outlined. [ABSTRACT FROM AUTHOR]

The domain of knowledge organization (KO) represents a foundational area of information science. One way to better understand the intellectual structure of the KO domain is to apply bibliometric methods to key contributors to the literature. This study analyzes the most prolific contributing authors to the journal Knowledge Organization, the sources they cite and the citations they receive for the period 1993 to 2016. The analyses were conducted using visualization outcomes of citation, co-citation and author bibliographic coupling analysis to reveal theoretical points of reference among authors and the most prominent research themes that constitute this scientific community. Birger Hjørland was the most cited author, and was situated at or near the middle of each of the maps based on different citation relationships. The proximities between authors resulting from the different citation relationships demonstrate ho w authors situate themselves intellectually through the citations they give and how other authors situate them through the citations received. There is a consistent core of theoretical references as well among the most productive authors. We observed a close network of scholarly communication between the authors cited in this core, which indicates the actual role of the journal Knowledge Organization as a space for knowledge construction in the area of knowledge organization. [ABSTRACT FROM AUTHOR]

A similarity comparison is made between 120 journals from five allied Web of Science disciplines (Communication, Computer Science-Information Systems, Education & Educational Research, Information Science & Library Science, Management) and a more distant discipline (Geology) across three time periods using a novel method called citing discipline analysis that relies on the frequency distribution of Web of Science Research Areas for citing articles. Similarities among journals are evaluated using multidimensional scaling with hierarchical cluster analysis and Principal Component Analysis. The resulting visualizations and groupings reveal clusters that align with the discipline assignments for the journals for four of the six disciplines, but also greater overlaps among some journals for two of the disciplines or categorizations that do not necessarily align with their assigned disciplines. Some journals categorized into a single given discipline were found to be more closely aligned with other disciplines and some journals assigned to multiple disciplines more closely aligned with only one of the assigned disciplines. The proposed method offers a complementary way to more traditional methods such as journal co-citation analysis to compare journal similarity using data that are readily available through Web of Science. [ABSTRACT FROM AUTHOR]

Relationships between authors based on characteristics of published literature have been studied for decades. Author cocitation analysis using mapping techniques has been most frequently used to study how closely two authors are thought to be in intellectual space based on how members of the research community co-cite their works. Other approaches exist to study author relatedness based more directly on the text of their published works. In this study we present static and dynamic word-based approaches using vector space modeling, as well as a topic-based approach based on latent Dirichlet allocation for mapping author research relatedness. Vector space modeling is used to define an author space consisting of works by a given author. Outcomes for the two word-based approaches and a topic-based approach for 50 prolific authors in library and information science are compared with more traditional author cocitation analysis using multidimensional scaling and hierarchical cluster analysis. The two word-based approaches produced similar outcomes except where two authors were frequent co-authors for the majority of their articles. The topic-based approach produced the most distinctive map. [ABSTRACT FROM AUTHOR]

Abstract: Recitation patterns for individual publications are examined and mathematically modeled by focusing on the origin of citations (citers) using data from Thomson Reuters Web of Science. The authors outline oeuvre citation exhaustivity, or the practice of citing across the body of work of an author, and model the resulting frequency distributions to identify research disciples and admirers. A Geeta distribution provided the best fits for both recitation frequency and oeuvre citation exhaustivity distributions. The findings provide a novel way to identify the influence of an author based on citer analysis. [Copyright &y& Elsevier]

Author research impact was examined based on citer analysis (the number of citers as opposed to the number of citations) for 90 highly cited authors grouped into three broad subject areas. Citer-based outcome measures were also compared with more traditional citation-based measures for levels of association. The authors found that there are significant differences in citer-based outcomes among the three broad subject areas examined and that there is a high degree of correlation between citer and citation-based measures for all measures compared, except for two outcomes calculated for the social sciences. Citer-based measures do produce slightly different rankings of authors based on citer counts when compared to more traditional citation counts. Examples are provided. Citation measures may not adequately address the influence, or reach, of an author because citations usually do not address the origin of the citation beyond self-citations. [ABSTRACT FROM AUTHOR]

• A conceptualization and an operationalization framework of effectiveness of Altmetric.com scores are proposed. • Altmetric.com scores can help to reflect multidimensional impact but are not currently effective indicators. • The strongest indicator of Altmetric.com scores to reflect scholarly impact of SSH researches is Readers. Altmetric.com is one of the leading and widely used commercial providers of altmetrics. Altmetrics is a broad term that encapsulates the collection of multiple digital indicators related to scholarly work (NISO, 2016). In this paper, the group of altmetrics provided by Altmetric.com is called Altmetric.com scores. This study assesses whether Altmetric.com scores are currently effective indicators to evaluate the research impact of social sciences and humanities (SSH). This research covers 1,253,028 records from the SSCI and A&HCI for five years (2013–2017), three publication types (articles, reviews, and proceedings papers), and 10 altmetrics provided by Altmetric.com to test the effectiveness of Altmetric.com scores through four proposed dimensions, including transparency, fairness, availability, and validity. Results show that the transparency of Altmetric.com scores is underexposed. And Altmetric.com scores favored English publications authored by North American researchers. Except for Altmetric attention score, Posts, Readers, and Tweeters, the data presence of most Altmetric.com scores was insufficient. As to research impact, Altmetric.com scores can help to reflect different impacts of SSH research. Overall, the results suggest that Altmetric.com scores are not yet sufficiently effective for evaluating the impact of SSH research though they can provide new insights into impact evaluation. [ABSTRACT FROM AUTHOR]