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Document details - Emotion Detection and Sentiment Analysis for Hindi Movie Reviews

Journal Volume 10, Issue 1, January - February 2021, Article 9882215 Mariya A. Ali, Sonali B. Kulkarni , " Emotion Detection and Sentiment Analysis for Hindi Movie Reviews" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 10, Issue 1, January - February 2021 , pp. 032-038 , ISSN 2278 - 6856.

Emotion Detection and Sentiment Analysis for Hindi Movie Reviews

    Mariya A. Ali, Sonali B. Kulkarni


Abstract:Sentiment Analysis and Emotion Detection is an emerging research field and this task is very important because peoples spent their most of the time on Internet. Text Mining has achieved amazing momentum currently in English language, As India is the multilingual society, this technology plays a very crucial role especially for Regional Language for better Understanding about the content web and Make it friendlier to native users .Obtaining Emotion from text is comparatively progressing slowly when compared with speech and other features. Movie reviews play an important role in recognizing the Sentiments of people and are used as a measure to determine the performance of a film. However, providing the reviews of the film can help in knowing the success or failure of a movie. A collection of movie reviews from distinct users provides us deep insights on different elements of a movie. There is a need to analyze the Hindi language content and get insight of sentiment and emotion expressed by people about movies. The study of public opinion can provide us with valuable information. In recent years, it has been demonstrated that deep learning area gives promising solution to the challenges of Natural Language Processing, using term frequency-inverse document frequency (TF-IDF). The primary objective of this study is to Analyze Sentiment and Detect Emotion from a collection of Hindi movie reviews. This research work may be used by the movie industry to facilitate better user experience. Keywords: Natural language,Word net, Sentiment Analysis, Emotion Detection

  • ISSN: 22786856
  • Source Type: Journal
  • Original language: English

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