Machine Learning Approaches to Assess Mood of the News Editorial
2022 IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2051953
ABSTRACT
Social media and news channels have always been vital sources for spreading information and raising awareness about recent occurrences. As reported by a survey, 82 percent of respondents from India stated that they sourced their news online, which included social media, as of the year 2021, making it a popular form of accessing news1. For a long time, information about COVID - 19 has been one of the most popular topics. News channel networks and editorials were one of the first places where knowledge regarding COVID - 19 was widely disseminated. In this study, sentiment analysis models have been developed to categorize tweets by some of India's most well-known news stations into positive and negative during the COVID - 19 virus was new in India from June 2020 to July 2020. We attempted to do so by developing nine various models based on different datasets and classification algorithms to investigate the news channels' tweets more thoroughly. According to our findings, the model that provided us with the highest accuracy and performance has been trained using the NLTK Dataset and the Logistic Regression Classifier. © 2022 IEEE.
COVID-19; Machine learning; Natural Language Processing; News; Pandemic; Sentiments; Classification (of information); Learning algorithms; Sentiment analysis; Social networking (online); Surveys; Viruses; Language processing; Machine learning approaches; Machine-learning; Natural languages; Sentiment; Social media; Social news
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
2022 IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2022
Year:
2022
Document Type:
Article
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