International Journal of Computer Applications · 2018 · 36 citations · 4 references
ComputingComputer ScienceMachine LearningNatural Language ProcessingText AnalyticsEmotion RecognitionOpinion MiningSentiment AnalysisSocial MediaText MiningTextual AnalysisEmotion DetectionFacial Expression AnalysisPolarity DetectionSentiment ClassificationSocial Media SentimentText-based Emotion AnalysisText-based Emotion DetectionTextual Sentiment Analysis
Social media is increasingly used by humans to express their feelings and opinions in the form of short text messages. Detecting sentiments in text has a wide range of applications including identifying anxiety or depression of individuals and measuring well-being or mood of a community. Sentiments can be expressed in many ways that can be seen such as facial expression and gestures, speech and by written text. Sentiment Analysis in text documents is essentially a contentbased classification problem involving concepts from the domains of Natural Language Processing as well as Machine Learning. In this paper, sentiment recognition based on textual data and the techniques used in sentiment analysis are discussed.
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