Review Paper On A Prompt Based Modal for Hateful Meme Classification

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Tejal Sudhakarrao Mohod; Dr. Ashish A. Bardekar

Review Paper On A Prompt Based Modal for Hateful Meme Classification

Authors: Tejal Sudhakarrao Mohod, Dr. Ashish A. Bardekar

Unique Paper ID: 178000
Volume: 11
Issue: 12
PageNo: 4046-4050

Keywords: BLIP Hateful Meme Detection Multimodal Learning OCR RoBERTa Emotion Detection PDF Report Generation

Abstract:
This paper presents a prompt-based multimodal framework for hateful meme classification and emotional content analysis, integrating visual and textual cues to identify and interpret harmful content in online memes. The proposed system leverages EasyOCR to extract embedded text from meme images, BLIP for generating descriptive image captions, and RoBERTa for contextual hatefulness classification. Additionally, an emotion detection module based on a DistilRoBERTa model captures the emotional undertone of the memes. To enhance usability, the system generates a comprehensive PDF report summarizing the extracted text, caption, hate classification, and emotion distribution. This architecture addresses the challenges in meme analysis by combining vision-language processing with transformer-based models, delivering a scalable and practical solution for real-world deployment.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 4046-4050

Review Paper On A Prompt Based Modal for Hateful Meme Classification

Available:https://ijirt.org/article?manuscript=178000

02 May, 2025

A Prompt Based Modal for Hateful Meme Classification

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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