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In today's modern age, the use of internet resources has expanded at an exponential rate. In recent decades, the usage of social media platforms such as Twitter, Facebook, and Instagram has increased. It gives raw data to several commercial enterprises and organizations, in addition to providing entertainment. This Natural Language Processing (NLP) tool may be immensely helpful in monitoring social media. It allows us to get a sense of how the public feels about particular topics. Businesses across the world are adopting the strategy of getting insights from social data. Several algorithms for…mehr

Produktbeschreibung
In today's modern age, the use of internet resources has expanded at an exponential rate. In recent decades, the usage of social media platforms such as Twitter, Facebook, and Instagram has increased. It gives raw data to several commercial enterprises and organizations, in addition to providing entertainment. This Natural Language Processing (NLP) tool may be immensely helpful in monitoring social media. It allows us to get a sense of how the public feels about particular topics. Businesses across the world are adopting the strategy of getting insights from social data. Several algorithms for Twitter Sentiment Analysis are compared in this paper's comparison research.
Autorenporträt
Professor Assistente, Universidade Manipal Jaipur, Jaipur