Salman Hameed
Data Science | Machine Learning | Deep Learning | Generative AI
Data Science | Machine Learning | Deep Learning | Generative AI
In an increasingly digitized world, understanding the nuances of language goes beyond surface-level comprehension. The project "Beyond Words: Discovering the Shades of Bias, Intensity, and Sentiment" delves into the intricate dimensions of text, exploring bias, intensity, and sentiment, to unearth the hidden layers of meaning and emotions embedded within each piece of content. By leveraging advanced natural language processing techniques and machine learning models, this project aims to provide users with a comprehensive analysis of input texts, revealing insights that extend beyond the surface.
Scope:
The scope of the "Beyond Words" project is to develop a text analysis tool that assesses bias, intensity of bias, and sentiment in textual content. The project encompasses multiple stages, starting from data preprocessing and exploration to the development and deployment of a user-friendly web application. The project's primary focus is on English language texts. The tool will offer real-time analysis of user input, catering to a wide range of potential users, including researchers, content creators, educators, journalists, and curious individuals seeking to uncover the underlying characteristics of textual content.
Usability:
It can be used in various domains such as in Content Creation, Media Analysis, Educational Research, Social Media Monitoring and Academic Studies etc.
"Beyond Words" employs advanced NLP and ML techniques to reveal bias, intensity, and sentiment in text, going beyond surface-level analysis. This project encompasses data preprocessing and a user-friendly web application for real-time English text analysis. It serves researchers, educators, journalists, and professionals in content creation and media analysis, providing deeper insights into textual content characteristics.