• Title of article

    Sentiment Analysis in the AI-Based Social Networks

  • Author/Authors

    Dehghani Kohneh Shahri ، Kamelya Department of Information Technology Management - Islamic Azad University, Science and Research Branch , Afshar Kazemi ، Mohammad-Ali Department of Industrial Management - Islamic Azad University, Central Tehran Branch , Pourebrahimi ، Ali Reza Department of Industrial Management - Islamic Azad University, Karaj Branch

  • From page
    287
  • To page
    307
  • Abstract
    Recent developments in emerging technologies have enabled users to interact with social networks. Nowadays, one of the ways of interaction is to understand the real feelings of people at the moment, the outcome of which, based on the people’s reaction and attitude, appears in analyzing feelings like facial features, type of speech, or the people’s jobs such as video, photograph, voice, and text. In this research, through deep learning and machine learning in the AI, the sentiment analysis has been studied and evaluated using AI and deep learning algorithms like motion detection, body language recognition, image processing, sound and text processing, computer vision, natural language processing and different network techniques. The paper, providing a new conceptual model design, has provided more details about sentiment analysis in social networks by incorporating AI techniques in social networks with high speed and accuracy.
  • Keywords
    Sentiment Analysis , Social Media , artificial intelligence , Deep Learning
  • Journal title
    International Journal of Information Science and Management (IJISM)
  • Journal title
    International Journal of Information Science and Management (IJISM)
  • Record number

    2773053