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Confirmation of Candidature - Candidate : Christopher Wigell

Sentiment Analysis for Detection of Depressive Users on Social Networks
13 APR 2023
2.00 PM - 3.30 PM

Social networks and communications data, with the advent of machine learning, have enhanced our knowledge in human behaviour due to their ubiquity and investigative value. Despite the field of psychology contributing much to human research, its lack of more precise, scalable tools and mounting ethical/bureaucratic barriers have stymied its progress (Stevens 2017). This is only further compounded by its dependence on raters for screening, with inter-rater reliability heavily influenced by test choice, mood, cultural and lexical bias (Reynolds & Suzuki 2012; Fiske 2020).  Consequently, we posit the use of an automated screening process to reduce these barriers.

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