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This article builds a joint memory network for modeling the dynamics of one’s emotions incurred by stressor/uplift events, and learns one's personality traits based on linguistic words and a fuzzy neural network to predict one's future stress level based. This study explores the emerging area of personality prediction using social media, emphasizing the simultaneous emphasis on improving research methods and addressing ethical concerns. Analyzing and identifying predictable time range for stress prediction based on chaos theory and deep learning.
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Predict the personality traits to explore in the social media platform using machine learning approach. The widespread use of digital technology, especially social media, presents an interesting opportunity to automatically detect personality traits from digital footprints. In this article, a memory network is constructed to predict an individual's future stress level by considering the impact of stressor/uplift events and the individual's reactions reflected from their social media posts.
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Incorporating forthcoming events and personality traits in social media based stress prediction(q115035620)
The current work comprises five stages:
