Review Paper on Emotion Detection from social media using Machine Learning
Uzma1, Anshul Khurana2
1 M.Tech Scholar(CSE), 2HoD MTech(CSE)
Department of Computer Science & Engineering, Shri Ram Institute of Technology, Jabalpur,(M.P.)
Abstract
Social networking platforms have revolutionized the way people communicate their feelings and opinions to the world. These platforms provide a convenient and accessible way for individuals to express themselves through various forms of such as text, images, audio, and video, thoughts, emotions, and experiences with others, regardless of geographic or cultural boundaries. The vast amount of data generated on social media platforms every second is largely unstructured, which makes it difficult to analyze and interpret using traditional methods. Sentiment analysis is a useful tool that can help process this data and gain insights into human psychology and behavior. sentiment analysis may not always be sufficient for understanding an individual's emotional/mental state. Emotion detection is a more advanced technique that can help determine an individual's emotional state more precisely by detecting specific emotions, such as joy, anger, sadness, fear, and disgust. Emotion detection goes beyond just identifying the polarity of a text and instead focuses on identifying specific emotions expressed in the text. There are various models and techniques used in emotion detection. However, both sentiment analysis and emotion detection face various challenges, such as dealing with sarcasm, irony, and other forms of figurative language, handling multilingual data, and addressing cultural differences in emotional expression. Overall, this type of review paper can be valuable in helping researchers and practitioners gain a better understanding of sentiment analysis and emotion detection, as well as the challenges and limitations of these techniques. By synthesizing and summarizing existing research and knowledge, review papers can provide a useful starting point for further exploration and investigation in these areas.
