Psychological Analysis using Social Media Tweets

This study utilizes social media platforms to extract and analyze pertinent data for gaining a complete understanding of the psychological dimensions of depression, employing Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNNs) for enhancing the motor skills. With a focus on language and temporal context, tweets are scrutinized to unearth the underlying dynamics within the Twitter network, shedding light on the social processes influencing the concept of depression. This research study intends to enhance the understanding of mental health professionals and decision-makers in this domain. The proposed methodology encompasses tweet tokenization, followed by LSTM and CNN models to identify significant features. The primary objective is to develop a system capable of conducting psychological analysis and supporting psychotherapy, achieving a classification accuracy of up to 99.02%. This high accuracy enables the detection of changes in behavioral patterns, offering promising avenues for intervention and support in mental health care.