• Prerna Suresh nikam
• Sudesh L. Farpat
• Sayali pradip patil
• Nandakishor namdev Wankhede
• S H Altab S H Rafiq

The primary objective of this project is to develop an effective system for detecting racism in social media content, specifically focusing on tweets. The system aims to analyze differential opinions expressed in tweets through sentiment analysis, identifying instances of racist language or sentiments. By doing so, the project seeks to contribute to the prevention and mitigation of online racism, which has become a significant social issue in today's digital age. Furthermore, the project aims to leverage deep learning techniques to enhance the accuracy and efficiency of racism detection in tweets. Specifically, it intends to employ a stacked ensemble deep learning model composed of a gated recurrent unit (GRU), a convolutional neural network (CNN), and a gated convolutional recurrent neural network (GCR-NN). By integrating these advanced deep learning architectures, the project aims to improve the system's ability to extract relevant features from raw text and accurately identify racist content in tweets. Another objective is to conduct comprehensive experiments and performance evaluations to assess the effectiveness of the proposed GCR-NN model in comparison to other machine learning and deep learning approaches. Through rigorous testing and analysis, the project seeks to demonstrate the superiority of the GCR-NN model in accurately detecting tweets containing racist comments, achieving high levels of accuracy, precision, recall, and overall performance. Overall, the project's objectives revolve around developing an advanced system for racism detection in tweets, leveraging deep learning techniques to enhance accuracy, and conducting thorough evaluations to validate the effectiveness of the proposed approach. By achieving these objectives, the project aims to contribute to the promotion of a safer and more inclusive online environment, free from the harmful effects of racism and discrimination.

Racism, social media, online abuse, Twitter, deep learning..

"Racism detection by analysing differential openion through centimate analysis of twit", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d8-d12, April-2024, Available :http://www.jetir.org/papers/JETIR2404302.pdf

"Racism detection by analysing differential openion through centimate analysis of twit", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd8-d12, April-2024, Available at : http://www.jetir.org/papers/JETIR2404302.pdf