AI-Powered Sentiment-Aware Captions: Transforming Social Media and E-Commerce Experiences

This study introduces an AI-powered sentiment-aware captioning device that combines deep studying techniques, which includes Convolutional Neural Networks (CNNs) and lengthy short-term memory (LSTM) networks, to generate personalized, emotionally shrewd captions. The version captures detailed picture capabilities while considering user sentiment, enhancing personalization and engagement. Evaluated at the Flickr8k dataset, the system demonstrated enhancements in user interaction, in particular in social media and e-trade applications. In social media, the model fosters emotionally resonant storytelling, at the same time as in e-trade, it refines product descriptions to decorate consumer enjoy and conversion charges. The findings advocate that integrating sentiment-aware AI in captioning ends in more immersive virtual stories and better consumer engagement. The examine highlights the capability for such models to revolutionize content introduction in digital marketing and consumer interplay. future research could attention on enhancing attention mechanisms and increasing datasets to in addition decorate caption accuracy and contextual relevance.

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Publication Details

Published
2025-04-02
DOI
https://doi.org/10.23919/indiacom66777.2025.11115812
Citations
8
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
19.85
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AI-Powered Sentiment-Aware Captions: Transforming Social Media and E-Commerce Experiences

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article

AI-Powered Sentiment-Aware Captions: Transforming Social Media and E-Commerce Experiences

Meenakshi Yadav, Bhanu Duggal, Saurabh Pratap Singh Rathore, Sandip Patil, Manav Kakkar, Priyanka Kaushik
article en
8 citations

Abstract

This study introduces an AI-powered sentiment-aware captioning device that combines deep studying techniques, which includes Convolutional Neural Networks (CNNs) and lengthy short-term memory (LSTM) networks, to generate personalized, emotionally shrewd captions. The version captures detailed picture capabilities while considering user sentiment, enhancing personalization and engagement. Evaluated at the Flickr8k dataset, the system demonstrated enhancements in user interaction, in particular in social media and e-trade applications. In social media, the model fosters emotionally resonant storytelling, at the same time as in e-trade, it refines product descriptions to decorate consumer enjoy and conversion charges. The findings advocate that integrating sentiment-aware AI in captioning ends in more immersive virtual stories and better consumer engagement. The examine highlights the capability for such models to revolutionize content introduction in digital marketing and consumer interplay. future research could attention on enhancing attention mechanisms and increasing datasets to in addition decorate caption accuracy and contextual relevance.

Chandigarh University (IN)
Reduced inequalities
Openalex Percentile: Top 1%
Sentiment Analysis and Opinion Mining
19.85
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