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Emotion Deduction from Social Media Text Data Using Machine Learning Algorithm

Journal of Computer and Communications 2023年第11期11卷 183-196页

作者： Thambusamy Velmurugan baskaran jayapradha PG and Research Department of Computer Science Dwaraka Doss Govardhan Doss Vaishnav College Chennai India PG and Research Department of Computer Science Dr. Ambedkar Government Arts College Chennai India

Emotion represents the feeling of an individual in a given situation. There are various ways to express the emotions of an individual. It can be categorized into verbal expressions, written expressions, facial expressions and gestures. Among these various ways of expressing the emotion, the written method is a challenging task to extract the emotions, as the data is in the form of textual dat. Finding the different kinds of emotions is also a tedious task as it requires a lot of pre preparations of the textual data taken for the research. This research work is carried out to analyse and extract the emotions hidden in text data. The text data taken for the analysis is from the social media dataset. Using the raw text data directly from the social media will not serve the purpose. Therefore, the text data has to be pre-processed and then utilised for further processing. Pre-processing makes the text data more efficient and would infer valuable insights of the emotions hidden in it. The preprocessing steps also help to manage the text data for identifying the emotions conveyed in the text. This work proposes to deduct the emotions taken from the social media text data by applying the machine learning algorithm. Finally, the usefulness of the emotions is suggested for various stake holders, to find the attitude of individuals at that moment, the data is produced. .

关键词： Data Pre-Processing Machine Learning Algorithms Emotion Deduction Sentiment Analysis

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