Text Analysis of ETDs in ProQuest Dissertations and Theses (PQDT) Global (2016-2018)

Abstract The information explosion in the form of ETDs poses the challenge of management and extraction of appropriate knowledge for decision making. Thus, the present study forwards a solution to the above problem by applying topic mining and prediction modeling tools to full-text 263 ETDs submitted to the PQDT Global database during 2016-18 in the field of library science. This study was divided into two phases. The first phase determined the core topics from the ETDs using Topic-Modeling-Tool (TMT), which was based on latent dirichlet allocation (LDA), whereas the second phase employed prediction analysis using RapidMiner platform to annotate the future research articles on the basis of the modeled topics.

Metadata Tagging and Prediction Modeling: Case Study of DESIDOC Journal of Library and Information Technology (2008–17)

Abstract The present paper describes the importance and usage of metadata tagging and prediction modeling tools for researchers and librarians. 387 articles were downloaded from DESIDOC Journal of Library and Information Technology (DJLIT) for the period 2008-17 excluding guest editorials and special editions. This study was divided into two phases. The first phase determined the core Topics from the research articles using Topic-Modeling-Tool (TMT) , which was based on latent Dirichlet allocation (LDA), whereas the second phase employed prediction analysis using RapidMiner toolbox to annotate the future research articles on the basis of the modeled topics.

Mapping of topics in DESIDOC Journal of Library and Information Technology, India: a study

Abstract 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.

Author-Topic Modeling of DESIDOC Journal of Library and Information Technology (2008-2017), India

Abstract This study presents a method to analyze textual data and applying it to the field of Library and Information Science. This paper subsumes a special case of Latent Dirichlet Allocation and Author-Topic models where each article has one unique author and each author has one unique topic. Topic Modeling Toolkit is used to perform the author-topic modeling. The study further which considers topics and their changes over time by taking into account both the word co-occurrence pattern and time.

New Paradigm in Library 2.0 Sentiment Analysis of Twitter

Abstract This chapter presents a conceptual framework of Sentiment Analysis and its application in the field of Library and Information Science. Sentiment Analysis of social media platforms will help the policy makers, researchers, and market analysts to understand the views and opinions generated by the public on an international platform related to the various facets of libraries.