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@article{162563,
        author = {Archana Gubba and K.Kundan Sri and Mohammed Sameer and Mr.Mohammed Ayaz Uddin},
        title = {Sentiment Analysis For Social Media Data},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {10},
        pages = {329-333},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162563},
        abstract = {This project investigates the growing significance of sentiment analysis in the era of social media dominance, providing a comparative analysis of methodologies and challenges encountered. It explores sentiment analysis's transformative impact on understanding user-generated content, employing machine learning and NLP techniques. Practical application is demonstrated through a product opinion analysis on social media. Across various domains, sentiment analysis shapes decision-making processes, particularly in business and marketing, by analyzing customer feedback to enhance product development and brand perception. The paper offers valuable insights for practitioners, aiding in the selection of appropriate methodologies for diverse social media sentiment analysis applications, categorizing sentiments into positive, negative, or neutral automatically.     },
        keywords = {Social media, Sentiment Analysis, Emotion, Review, Valuable insights. },
        month = {},
        }