TY - JOUR ID - TI - Sentiment Analysis of Text and Emoji Data for Twitter Network AU - Paramita Dey, Soumya Dey PY - 2023 VL - 3 IS - 1 SP - 1 EP - 10 JO - Al-Bahir Journal for Engineering and Pure Sciences مجلة الباهر للعلوم الهندسية والصرفة SN - 23125721 23130083 AB - Twitter is a social media platform where users can post, read, and interact with 'tweets'. Third party like corporateorganization can take advantage of this huge information by collecting data about their customers' opinions. The use ofemoticons on social media and the emotions expressed through them are the subjects of this research paper. The purposeof this paper is to present a model for analyzing emotional responses to real-life Twitter data. The proposed model isbased on supervised machine learning algorithms and data on has been collected through crawler “TWEEPY” forempirical analysis. Collected data is pre-processed, pruned and fed into various supervised models. Each tweet isassigned to sentiment based on the user's emotions, positive, negative, or neutral

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