Search (7 results, page 1 of 1)

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Abstract

This paper presents a condensed history of Library and Information Science (LIS) over the course of more than a century using a variety of bibliometric measures. It examines in detail the variable rate of knowledge production in the field, shifts in subject coverage, the dominance of particular publication genres at different times, prevailing modes of production, interactions with other disciplines, and, more generally, observes how the field has evolved. It shows that, despite a striking growth in the number of journals, papers, and contributing authors, a decrease was observed in the field's market-share of all social science and humanities research. Collaborative authorship is now the norm, a pattern seen across the social sciences. The idea of boundary crossing was also examined: in 2010, nearly 60% of authors who published in LIS also published in another discipline. This high degree of permeability in LIS was also demonstrated through reference and citation practices: LIS scholars now cite and receive citations from other fields more than from LIS itself. Two major structural shifts are revealed in the data: in 1960, LIS changed from a professional field focused on librarianship to an academic field focused on information and use; and in 1990, LIS began to receive a growing number of citations from outside the field, notably from Computer Science and Management, and saw a dramatic increase in the number of authors contributing to the literature of the field.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.5, S.997-1016

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Abstract

This article compares doctoral students' and faculty members' referencing behavior through the analysis of a large corpus of scientific articles. It shows that doctoral students tend to cite more documents per article than faculty members, and that the literature they cite is, on average, more recent. It also demonstrates that doctoral students cite a larger proportion of conference proceedings and journal articles than faculty members and faculty members are more likely to self-cite and cite theses than doctoral students. Analysis of the impact of cited journals indicates that in health research, faculty members tend to cite journals with slightly lower impact factors whereas in social sciences and humanities, faculty members cite journals with higher impact factors. Finally, it provides evidence that, in every discipline, faculty members tend to cite a higher proportion of clinical/applied research journals than doctoral students. This study contributes to the understanding of referencing patterns and age stratification in academia. Implications for understanding the information-seeking behavior of academics are discussed.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.1045-1054

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Abstract

This brief communication presents preliminary findings on automated Twitter accounts distributing links to scientific articles deposited on the preprint repository arXiv. It discusses the implication of the presence of such bots from the perspective of social media metrics (altmetrics), where mentions of scholarly documents on Twitter have been suggested as a means of measuring impact that is both broader and timelier than citations. Our results show that automated Twitter accounts create a considerable amount of tweets to scientific articles and that they behave differently than common social bots, which has critical implications for the use of raw tweet counts in research evaluation and assessment. We discuss some definitions of Twitter cyborgs and bots in scholarly communication and propose distinguishing between different levels of engagement-that is, differentiating between tweeting only bibliographic information to discussing or commenting on the content of a scientific work.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.1, S.232-238

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Abstract

Data collected by social media platforms have been introduced as new sources for indicators to help measure the impact of scholarly research in ways that are complementary to traditional citation analysis. Data generated from social media activities can be used to reflect broad types of impact. This article aims to provide systematic evidence about how often Twitter is used to disseminate information about journal articles in the biomedical sciences. The analysis is based on 1.4 million documents covered by both PubMed and Web of Science and published between 2010 and 2012. The number of tweets containing links to these documents was analyzed and compared to citations to evaluate the degree to which certain journals, disciplines, and specialties were represented on Twitter and how far tweets correlate with citation impact. With less than 10% of PubMed articles mentioned on Twitter, its uptake is low in general but differs between journals and specialties. Correlations between tweets and citations are low, implying that impact metrics based on tweets are different from those based on citations. A framework using the coverage of articles and the correlation between Twitter mentions and citations is proposed to facilitate the evaluation of novel social-media-based metrics.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.4, S.656-669

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Source

Journal of the Association for Information Science and Technology. 66(2015) no.7, S.1323-1332

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Source

Journal of the Association for Information Science and Technology. 68(2017) no.9, S.2037-2062

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Source

Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1157-1169