POST Exploration

POST exploration, encompassing the analysis of user-generated content on various platforms, aims to extract meaningful information and insights from social media posts and emails. Current research focuses on applying natural language processing (NLP) techniques, including transformer-based models like BERT and advanced architectures such as CNN-BiLSTMs, to detect sentiment, mental health indicators (e.g., depression, suicidal ideation), and other relevant attributes within text data. This research is significant for its potential applications in improving mental health monitoring, enhancing cybersecurity through phishing detection, and informing social science studies on topics like value expression and public opinion.