Sentimental Analysics on Social Media
Year: 2025
Type: article
Abstract: This project aims to combat misinformation on social media by developing a system that combines sentimentanalysis, fake news detection, and deep fake recognition. Using VADER lexicon, the sentiment analysis modulewill categorize social media posts into positive, negative, or neutral sentiment. A fake news detection modulewill identify misleading content using advanced techniques, while a deep fake recognition system, powered byPyTorch and LSTM networks, will analyze media for anomalies indicative of synthetic manipulation. Thisintegrated approach seeks to enhance trust and accountability in online information, contributing to a moreinformed and safer digital environment.
Authors: Dr. Shobha Hugar, Sinchana C, Sreevatsa S, Tejaswini S S, V Vishnu
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W6912148947
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