Sentiment Classification Based on Human Behavior Using Deep Neural Model

Authors

  • Syed Saad Husain  Babasaheb Naik College of Engineering, Pusad, Maharashtra, India
  • Dr. Salim Y. Amdani  Babasaheb Naik College of Engineering, Pusad, Maharashtra, India
  • Dr. Suresh. S. Asole  Babasaheb Naik College of Engineering, Pusad, Maharashtra, India

Keywords:

Emotion Detection, Natural Language Processing, Sentiment Analysis, Text-Based Emotion Detection

Abstract

The task of automatically analyzing sentiments from a tweet has more use now than ever due to the spectrum of emotions expressed from national leaders to the average man. Analyzing this data can be critical for any organization. Sentiments are often expressed with different intensity and topics which can provide great insight into how something affects society. Sentiment analysis in Twitter mitigates the various issues of analyzing the tweets in terms of views expressed and several approaches have already been proposed for sentiment analysis in twitter. Resources used for analyzing tweet emotions are also briefly presented in literature survey section. In this paper, hybrid combination of different model’s LSTM-CNN have been proposed where LSTM is Long Short Term Memory and CNN represents Convolutional Neural Network. Due to issues such as background clutter, partial occlusion, changes in scale, viewpoint, lighting, and appearance, recognising human activities from video sequences or still, images is a di?cult process. Many applications, such as video surveillance systems, human-computer interaction, and robotics for human behavior classi?cation, necessitate multiple activity recognition systems. We ?r?vid? an e?cient approach for human activity classi?cation and extraction. In our project, we looked into the ?aws of existing human recognition systems. We proposed using multiple frames and averaging their averages to determine the activity label rather than using a single frame to solve these restrictions. This strategy is e?cient since we are averaging n frames and considering temporal storage.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2022-04-30

Issue

Volume 9, Issue 2, March-April-2022

Section

Research Articles

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How to Cite

[1]
Syed Saad Husain, Dr. Salim Y. Amdani, Dr. Suresh. S. Asole, " Sentiment Classification Based on Human Behavior Using Deep Neural Model, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 2, pp.100-107, March-April-2022.