Samyukta Hariharan - Research Engineer (Data/ AI) @ Arabesque AI
Adharsh Venkatachalam - Robotics Engineer III @ Panasonic Asia Pacific
This project aims to develop a robust system capable of automatically identifying and analyzing biases present in news articles. With the proliferation of digital media and the rise of social platforms as primary sources of news consumption, the spread of biased information has become increasingly prevalent, influencing public opinion and societal discourse. Therefore, the need for tools that can objectively assess the impartiality of news content is paramount.
This project will utilize natural language processing (NLP) techniques and machine learning algorithms to detect various forms of bias, including political, ideological, cultural, and sensational biases, among others. By leveraging large datasets of news articles across diverse sources and topics, the system will learn to recognize patterns indicative of biased reporting.
Ultimately, the "News Bias Detection" project seeks to promote media literacy, foster critical thinking, and mitigate the spread of misinformation by providing individuals with the tools necessary to discern biased reporting and engage with news content more discerningly.
The dataset has been taken from HuggingFace, titled news-bias-full-data. The dataset encompasses multiple dimensions of biases in news media, such as political inclinations, hate speech, toxicity, sexism, ageism, and more, establishing its distinctiveness in the realm of similar datasets. It's noteworthy that the dataset explicitly refrains from including any personally identifiable information (PII).