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Chimpanzees combine pant hoots with food calls into larger structures
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Spatial agency bias and word order flexibility : a comparison of 14 European languages
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44 |
Studying the behavioural, physiological, and neural indices of associative learning in multi-trial paradigms: methodological and analytical considerations
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Improving video game conversations with trope-informed design
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A lexicon-based approach to detecting suicide-related text on Twitter.
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A lexicon-based approach to detecting suicide-related text on Twitter.
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Abstract:
Expression of emotion is an indicator that can contribute to the detection of mental health-related disorders. Suicide causes death to many people around the globe, and despite the suicide prevention strategies that have been employed over the years, only a few studies have explored the role of emotions in predicting suicidal behavior on social media platforms. This study explored the role of emotions from Twitter messages in detecting suicide-related content. We extracted and analyzed the characteristics of Twitter users' sentiment and behavior response (anger, fear, sadness, joy, positive, and negative) using NRC Affect Intensity Lexicon and SentiStrength techniques. A semi-supervised learning method was applied using the YATSI classifier or “Yet Another Two-Stage Idea” to efficiently recognize suicide-related tweets. The results showed that tweets associated with suicide content were exclusively related to fear, sadness, and negative sentiments. The classification results showed the potential of emotions in facilitating the detection of suicide-related content online. Our findings offer valuable insights into ongoing research on the prevention of suicide risk and other mental-related disorders on Twitter. The proposed mechanism can contribute to the development of clinical decision support systems that deal with evidence-based guidelines and generate customized recommendations.
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Keyword:
BF Psychology
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URL: https://orca.cardiff.ac.uk/137402/1/A%20lexicon-based%20approach%20to%20detecting%20suicide-related%20messages%20on%20Twitter%20_%20Post-print.pdf https://orca.cardiff.ac.uk/137402/ https://doi.org/10.1016/j.bspc.2020.102355
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Functional and structural properties of spatial processing networks in the brain
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Investigating the role of image meaning and prior knowledge in human eye movements control
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The “Good is Up” metaphoric effects on recognition: True for source guessing but false for item memory
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Using an educational psychologist led psychoeducation group skills intervention to develop the emotion regulation skills of further education students
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Individual differences in neural architecture supporting mental time travel
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Group interventions for the reduction of psychological distress in university students
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Statistical and sequence learning lead to persistent memory in children after a one-year offline period
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Empowering communication through speaking, reading and writing
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Conducting thematic analysis on brief texts: The structured tabular approach
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Indicatives, subjunctives, and the falsity of the antecedent
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Super-recognisers: some people excel at both face and voice recognition
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The part-whole effect in super-recognisers and typical-range-ability controls
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The ‘comparative logic’ and why we need to explain interlanguage grammars
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