Analysis of Emotional Model on Tweets Using Data Mining

Registration ID: IJNRD_184989

Published ID: IJNRD2212168

DOI: Click Here to Get

M.Priyadharshan , B.Gayathri

Twitter Data, Sentiment Analysis, Attention based Bidirectional LSTM, BERT, Deep Learning

This approach gives an advanced alternative to the existing Sentiment analysis models. Emotional Models are a bit trickier than the traditional Sentiment Models as they analyze human emotions by identifying the context of a text, which is different from a Sentiment Model where only the polarity of the text is calculated and the prediction is either positive or negative. The Model requires a huge dictionary of lexicons which points to different emotions. This can be used to analyze a text based on the lexicons that belong to a particular human emotion. The words in the text are embedded with low dimensional vectors, which makes it easier to use in the Neural Network Models. The purpose of emotional analysis is to identify the sentiment of a given text. In general, emotional analysis can predict emotions such as anger, happiness, surprise, sadness and so on. The classification of the emotions can only be achieved through psychological models that define human emotions in terms of mathematical values. Emotion Models are built based on Natural Language Processing and Text Analysis using Deep Learning Techniques. Tweet Analysis helps in classifying data about a specific brand or a product and its interest among the users.

Published Paper   E-Certificate

M.Priyadharshan & B.Gayathri (December-2022). Analysis of Emotional Model on Tweets Using Data Mining. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(12), b577-b581. https://ijnrd.org/papers/IJNRD2212168.pdf

Volume 7 Issue 12, December-2022

Pages : b577-b581

Paper Reg. ID: IJNRD_184989

Published Paper Id: IJNRD2212168

Downloads: 000121982

Research Area: Engineering

Country: Coimbatore, Taminadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2212168.pdf

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