Trends in Information Management

Library and Information Science

University of Kashmir

ISSN: 0973-4163

Time spent by academics on research quality assessment might be reduced if automated approaches can help. Whilst citation-based indicators have been extensively developed and evaluated for this, they have substantial limitations and Large Language Models (LLMs) like ChatGPT provide an alternative approach. This article assesses whether ChatGPT 4o-mini can be used to estimate the quality of journal articles across academia. It samples up to 200 articles from all 34 Units of Assessment (UoAs) in the UK’s Research Excellence Framework (REF) 2021, comparing ChatGPT scores with departmental average scores. There was an almost universally positive Spearman correlation between ChatGPT scores and departmental averages, varying between 0.08 (Philosophy) and 0.78 (Psychology, Psychiatry and Neuroscience), except for Clinical Medicine (rho=-0.12). Although other explanations are possible, especially because REF score profiles are public, the results suggest that LLMs can provide reasonable research quality estimates in most areas of science, and particularly the physical and health sciences and engineering, even before citation data is available. Nevertheless, ChatGPT assessments seem to be more positive for most health and physical sciences than for other fields, a concern for multidisciplinary assessments, and the ChatGPT scores are only based on titles and abstracts, so cannot be research evaluations.

Smart technologies form the foundation of smart library services in advanced countries and are gradually being adopted in academic libraries of developing nations. This paper, based on a systematic literature review, identifies and recommends suitable smart technologies such as robots, drones, big data, mobile apps, and blockchain for enhancing library operations and improving user services. Despite their potential, challenges such as power outages, poor funding, and weak internet penetration hinder effective implementation, particularly in Africa. Addressing these barriers through adequate funding and efficient management will enable academic libraries to integrate smart technologies and deliver demand-driven, techno-centric services to better meet users’ information needs.

This study examines the sentiment analysis of public responses to the Indian Finance Minister’s budget speeches from 2019 to 2023, leveraging Python programming and NLP techniques. Objectives include evaluating video characteristics such as duration, resolution, view count, and likes; ranking videos based on engagement metrics; analyzing sentiments in speeches and viewer comments; and exploring trends in comment growth and gender-wise variation. Findings reveal that the Union Budget 2023-24 video garnered significant attention and positive reception, demonstrating the importance of engaging content despite longer durations. Viewer comments for this budget highlight substantial engagement, reflecting its relevance. Sentiment analysis uncovers frequent mentions of government policies, taxation, and economic figures, indicating public interest in financial and policy-related aspects. Overall, the sentiment expressed in both videos and comments is predominantly positive, with moderate subjectivity, showcasing diverse perspectives.

Social Media Influencers (SMIs) have evolved as a valuable marketing tool for promoting products, services and even destinations. The collaboration with SMIs is surging in a commercial context as credible SMIs substantially influence the buying/ visit intention of their followers. The study investigates the impact of influencer credibility (IC) on the visit intention of students to the library. The study adopted a pre- and post-experimental design using the Source Credibility Model as the foundation. The sample consists of 30 MBA (Master of Business Administration) students studying at the Central University of Kashmir, India. Data analysis was done using SPSS 27 software with statistical techniques such as linear regression and t-tests. The findings reveal that IC has a significant and positive impact on the library visit intention of the students to the library. Further, the study also finds that library visit intentions significantly improve post-exposure to influencers’ content. The study adds to the influencer marketing literature in an academic context and provides some noteworthy implications for various stakeholders.

Precision oncology heavily relies on dividing cancer into different subtypes. Single omics data do not accurately reflect the complex ways in which molecules interact and collaborate in tumor growth and development. Advances in high-throughput methods have enabled the generation of genomic, transcriptomic, epigenomic, and proteomic data, providing new opportunities to examine cancer. However since various types of data must be used together, there are large computational obstacles involved. In this paper, we look into ways that combine different machine learning (ML) methods for integrating various kinds of data to find cancer subtypes. We describe the main data forms, methods for data integration, model design strategies, testing techniques, and new difficulties. In addition, we address the impact of biological significance, easy understanding, and medical application on the future of intelligent cancer subtyping.

This study analyses sentiments expressed on Twitter following the repeal of the Farmer Bills 2020/2021 in India, aiming to understand the role of social media during crises and its capacity to promote or endorse specific views. Using content analysis of 14,444 tweets collected from verified and non-verified accounts across nine relevant hashtags, the data were pre-processed through transformation, tokenisation, filtering, and normalisation, and analysed with the VADER Sentiment Module of Orange Software. The findings reveal trends in tweet counts and sentiment over 12 days, showing an initial surge followed by a gradual decline in activity, with most tweets conveying positive sentiments supportive of the farmer protests and the repeal of the laws. The study underscores Twitter’s role in shaping public opinion and disseminating information, while acknowledging limitations related to reliance on Twitter data and the defined timeframe. Its originality lies in providing insights into public perceptions and reactions to legislative changes following the repeal.

Fake news refers to incorrect information presented as news, whether on social media or through mainstream media. The rising prevalence of fake news, particularly with the advent of social media, underscores the need for effective fact-checking. Fact checking is a process involving the verification of facts and debunking fake information. The study analysed the working style of four fact-checking sites in India (AltNews, BoomLive, TheQuint (Webqoof) and The LogicalIndian), dissecting 805 stories into elements to determine their accuracy. The study provides an insight into how fake news is debunked. It has been found that fake news outweighs genuine news, as consumption of viral content is higher. The main reason behind this is people’s shortened attention span. Those spreading fake news exploit this vulnerability. Besides, mainstream media nowadays picks up news from social media, which is a hub of fake news. Fact-checkers have consistently debunked such cases. Much like traditional news reporting, the fact-checking process is guided by news values and ethics.

This study investigates the evolution and growth of digital humanities research from 2012 to 2022 using data from the Web of Science, analysed through Orange Data Mining, MS Excel, VOSviewer, and Microsoft Office tools. It examines key research areas, thematic trends, top contributing countries, and interdisciplinary linkages, revealing a steady increase in publications since 2002, with dominant themes including digital humanities, libraries, databases, archives, mathematics, and neurosciences. The United States leads global contributions, followed by England and Germany, with diverse journals across literature, arts, humanities, history, and computer science publishing in this field. As a novel work, the study highlights global participation and the integration of digital humanities into multiple academic disciplines, offering valuable insights for researchers and experts across domains.