This study analyzed 928 full-text research articles retrieved from DESIDOC Journal of Library and Information Technology for the period of 1981-2018 using Latent Dirichlet Allocation. The study further tagged the articles with the modeled topics. 50 core topics were identified throughout the period of 38 years whereas only 26 topics were unique in nature. Bibliometrics, ICT, information retrieval, and user studies were highly researched areas in India for the epoch. Further, Spain and Taiwan showed common research trends and areas as India whereas India has quite distinct research interests from America and China. Therefore, researchers in Library and Information Science in India should pay more attention to the topics which are under-researched. Further, it was found that there were some unique sub-fields to Indian Library and Information Science research, such as open access; online exhibition; virtual libraries; multimedia libraries; open source software; library automation; and library management system. With the passage of time topics evolve over time, new topics emerge, and old ones become obsolete. Topic modeling not only helps the researcher to determine the trending themes or related fields with respect to their field of interest but also helps them to identify new concepts and fields over time.
The 21 authors of this study, 19 of whom are non-native English speakers, reflect on the barriers to publishing academic journal articles in top international journals. Each author responded to the same set of questions pertaining to educational (PhD) opportunities for emerging scholars, financial conditions for researchers, and challenges in publishing their work. Limited English language skills, lack of research funding, and different research topics were identified as the most significant barriers to publish in the journals. Recruiting volunteers or using electronic translations for accepted articles for journals, reducing software and subscription to academic journals costs, expanding journal scope, and providing guidance and collaboration across borders are possible measures to reduce the negative impact of the barriers.
Purpose Social interaction applications and reference tools are actively used by researchers to share and manage their research publications. Thus, this paper aims to determine the scholarly impact of selected Indian central universities. Design/methodology/approach This study analyzed 669 articles having both Dimensions citations and Altmetric attention scores published by 35 Indian central universities for 4 subfields of Computer Science using Altmetric Explorer. This paper determined each university’s contribution in the studied subfields of Computer Science and the correlation among Altmetric attention score (aggregated and individual), Dimensions citation, and Mendeley readership counts for all 669 articles and stratified percentile sets of top 25%, and top 50% of the overall number of articles. Findings The findings showed that Jawaharlal Nehru University had the maximum Altmetric attention score, Banaras Hindu University received the maximum Dimensions citation, and University of Hyderabad (UoH) received the maximum number of Mendeley readers. Each central university was examined individually and then ranked based on their median values of Dimensions citations and Altmetric attention scores. Further, Twitter had the maximum Altmetric coverage, followed by Google+, Patent and Facebook for the retrieved articles. A significant strong positive correlation was observed between the Dimensions citation and Mendeley readership counts for all the three categories. Research limitations/implications Both Altmetric attention scores and Dimensions citations can help funding agencies to assess and evaluate the research productivity of these universities, thus, making important decisions such as increasing, decreasing, re-distributing their funds. Originality/value The current body of research is focused mostly on relationships between citations and individual Altmetric indicators predominantly. For most of the studies, the citations were retrieved from Scopus, Web of Science or Google Scholar database. It was observed that by far, no study had examined the relationship between citations retrieved from Dimensions database, Altmetrics scores (both aggregated and individual) and Mendeley readership counts.
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