NLP Based Recognition of False Bulletin with Hybrid Machine Learning Methodologies
Namala Madhuri, R. Tamilkodi, R. Geethika, Geeta Rani, M. Trishanth, V. Hari Prasad · 2025
In recent times, the swift spread of information via social media has dramatically influenced society. This has, in many cases, contributed to the dissemination of misinformation by malicious actors globally. Such occurrences have caused significant confusion and, on occasion, even led to loss of life. To address this urgent problem, our project proposes a hybrid machine learning approach, incorporating natural language processing (NLP), to efficiently identify & differentiate between legitimate & false news. By applying the machine learning techniques learned during our coursework, we aim to develop a solution that aids in preserving societal harmony and order. Our methodology includes examining specific patterns and characteristics within news articles, allowing us to make a robust model that can recognize and flag inaccurate reports. Through this effort, we hope to minimize the harmful impact of false information and contribute to a more well-informed and stable community.