Sentiment Analysis in the AI-Based Social Networks

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.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
DOI
https://doi.org/10.22034/ijism.2024.2019923.1360
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

Sentiment Analysis in the AI-Based Social Networks

SHILAP Revista de lepidopterología
Sentiment Analysis and Opinion Mining
article

Sentiment Analysis in the AI-Based Social Networks

article en

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.

SHILAP Revista de lepidopterología
Quality Education
Openalex Percentile: Top 58%
Sentiment Analysis and Opinion Mining
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