News Coverage of Libraries in India: An NLP-based Analysis of News indexed in Google

Abstract

The purpose of the study is to analyse the news coverage of libraries in India from April 2023 to March 2024. A total of 166 news titles and metadata were collected manually using a structured query using Google. Natural Language Processing (NLP) techniques including topic modelling, Named Entity Recognition (NER), and Sentiment Analysis were used to explore trends in news coverage, news topics, entities, and sentiments from the news titles. Major Findings of the study revealed that August 2023 is the most common month in terms of news coverage; the Times of India is the significant news source; “Academic Library” related topics dominated the news discourse; Organisations and location-based entities as the top entities found in the news titles, and neutral and positive sentiments expressed mostly in the news titles. The findings hold implications for library stakeholders and media professionals and provide valuable information regarding the portrayal of libraries in the news media landscape. This study uses a unique approach using mixed NLP techniques to get insights into library news topics, named entities, and sentiments and shows how libraries in India receive media attention.