Shodh Prabha: A Multidisciplinary Journal

How Social Media Peoples Perceive ‘One Nation One Subscription’ Initiative: A Sentiment Analysis

The "One Nation One Subscription" (ONOS) initiative, launched by the Government of India in January 2025, aims to democratize access to scholarly research by providing free access to over 13,000 high-impact journals for approximately 18 million users across 6,400 institutions. This study investigates public sentiment towards ONOS by analyzing Twitter data using sentiment analysis techniques. A total of 137 comments were collected using the hashtag #ONOS, with a focus on posts from the Ministry of Education and ANI, which garnered the highest engagement. The data were preprocessed through cleaning, tokenization, stopword handling, and vectorization using TF-IDF. Sentiment classification was performed using lexicon-based methods (TextBlob and VADER) and machine learning models including Logistic Regression, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The results revealed that 41.6% of the tweets expressed positive sentiment, 52.6% were neutral, and only 5.8% were negative. Linear SVC achieved the highest classification accuracy at 89%, followed by Logistic Regression (86%) and KNN (82%). Word cloud analysis highlighted frequently used terms such as “research,” “India,” and “access,” while sentiment-specific word clouds identified “great,” “good,” and “free” as positive indicators, and “useless” and “mean” as negative ones. The findings suggest a predominantly positive or neutral public perception of ONOS, with minimal negative sentiment. This study underscores the utility of sentiment analysis in gauging public opinion on policy initiatives and highlights the potential of social media analytics in informing evidence-based decision-making.