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NEW EDUCATION POLICY, 2020: QUALITATIVE (CONTENTS) ANALYSIS AND TWITTER MINING (SENTIMENT) ANALYSIS
Author(s) -
Rahul Pratap Singh Kaurav,
Kalyani Suresh,
Sumit Narula,
Ruturaj Baber
Publication year - 2020
Publication title -
journal of content, community and communication
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.183
H-Index - 4
eISSN - 2456-9011
pISSN - 2395-7514
DOI - 10.31620/jccc.12.20/02
Subject(s) - sentiment analysis , globe , christian ministry , policy analysis , data science , representation (politics) , resource (disambiguation) , public relations , focus (optics) , political science , computer science , public administration , psychology , artificial intelligence , computer network , physics , optics , neuroscience , politics , law
The year 2020 has been an exceptional year for countries across the globe. In India, apart from Covid19, one of the important changes that took place was the development of the New Education Policy (NEP) 2020. Time by time, various committees have recommended increasing the allocation of the budget for education to 6% of the GDP, this has lead to the interests of researchers. This paper aims to identify the concerns and focus of NEP 2020. The authors have utilized qualitative data analysis techniques to understand critical areas of focus of policy documents and computer-assisted qualitative data analysis software to address the issues. The research also uses data from Twitter. The data (policy documents) was downloaded from the Ministry of Human Resource Development (MHRD) website. For a better understanding of the collected data, Word Cloud, TreeMap, Project Map, and The Mind Map, along with the graphical representation of sentiments of stakeholders, is presented in the paper. The paper identifies three crucial aspects of the policy – course, language, and students, for the higher education sector. This paper also discusses the sentiment analysis, related to NEP 2020. It was found that most people consider the policy as a positive and welcoming step.

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