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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]

• We analyze the prevalence of research software citation in Clarivate Analytics' Data Citation Index (DCI). • To date, most software citations have been limited to research software hosted by a small number of repositories. • Research software remains highly uncited in the DCI, or the reuse of research software is not well reflected in the DCI. • The use of persistent identifiers, which can help to identify research software did not necessarily result in higher citation rates. The aim of this study is to explore the phenomenon of research software citation and, in particular, to draw attention to the increasing importance of this form of citation in scholarly communication. This research sheds light on the current status of formal software citation that is captured by citation databases. Data for the study were gathered from more than 67,000 research software records available in public repositories indexed by Clarivate Analytics' Data Citation Index (DCI). The metadata characteristics of the indexed records and citation data were then analyzed. Research software was rarely cited in the DCI, suggesting that the documented reuse of research software rarely occurs or is not well documented. Institutional repositories attracted few citations and had low rate of citation. It proved impossible, however, using the available data to isolate specific identifiers that can promote formal software citation. The findings presented here offer insights into research software citation that will be of interest to funding agencies, publishers, researchers, and research organizations. [ABSTRACT FROM AUTHOR]

Social media platforms, search engine transaction logs, Web portal transaction logs, large text corpora, and other data sources offer users a variety of invaluable data sources. Data generated based on social media platforms and other data sources have become important sources of big data for researchers in information science. Big data provide not only challenges but also opportunities for information science. Emerging big data trends inevitably have an impact on research methods in information science. The authors of this paper discuss the impact of big data on research methods in information science. This paper addresses these challenges and opportunities through the lens of research methods, ranging from data processing, to sampling, to information visualization, to temporal analysis, to sentiment analysis, to correlation, to cause-effect relationship, to data accessibility, to data privacy, and data ethics issues. The discussions on related aspects of research methods provoke a healthy reflection and debate for the information science research community, which can help researchers in the field produce sound research designs for big data-oriented research studies and assist information practitioners in solving problems they face in the big data age. Research methods are fundamental and essential for any research studies. Big data analysis has a natural relationship with research methods. The paper discusses an emerging and important research topic big data from the unique angle of research methods. [ABSTRACT FROM AUTHOR]

We introduce the author keyword coupling analysis (AKCA) method to visualize the field of information science (2006–2015). We then compare the AKCA method with the author bibliographic coupling analysis (ABCA) method in terms of first- and all-author citation counts. We obtain the following findings: (1) The AKCA method is a new and feasible method for visualizing a discipline's structure, and the ABCA and AKCA methods have their respective strengths and emphases. The relation within the ABCA method is based on the same references (knowledge base), whereas that within the AKCA method is based on the same keywords (lexical linguistic). The AKCA method appears to provide a less detailed picture, and more uneven sub-areas of a discipline structure. The relationships between authors are narrow and direct and feature multiple levels in AKCA. (2) All-author coupling provides a comprehensive picture; thus, a complete view of a discipline structure may require both first- and all-author coupling analyses. (3) Information science evolved continuously during the second decade of the World Wide Web. The KDA (knowledge domain analysis) camp became remarkably prominent, while the IR camp (information retrieval) experienced a further decline in hard IR research, and became significantly smaller; Patent analysis and Open Access emerged during this period. Mapping of Science and Bibliometric evaluation also experienced substantial growth. [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]

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]

Abstract: Recent studies have concluded that American contributions to science literature have been in relative decline, whereas contributions from other parts of the world such as the European Union and Asia have increased. Is the same true for the areas of bibliometrics, informetrics and scientometrics? This study investigates the growth and geographic distribution of metrics research for the period 1987–2008. Similar to studies of other disciplines or science in general, the findings reveal that the United States continues to dominate, but there has been a recent relative decline in North American contributions overall. European and Asian contributions have grown substantially. National and institutional collaborations that contribute to this growth do not necessarily follow close geographic proximity, although European nations have been more active with international collaborations overall, both within Europe and elsewhere. [Copyright &y& Elsevier]

• 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]