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Colour Coded Emotion Classification in Mental Health Social Media
Vaughan, Neil Mulvenna, Maurice Bond, Raymond
Vaughan, Neil
Mulvenna, Maurice
Bond, Raymond
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2018-07-06
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Abstract
This research applies emotion detection to messages from online mental health social media. In particular, this focusses on specialised social media for users to report health or mental health problems. Automatically detecting the emotion in social media can help to rapidly identify any concerning problems which could benefit from intervention aiming to prevent self-harming or suicide. Detecting emotions enables messages to be colour coordinated according to the emotion to enhance the human-computer interaction. A supervised classification method is applied to a labelled dataset and results presented. A prototype user interface system is developed based on detecting emotion, colour coding the message to display detected emotions to users in real-time.
Citation
Vaughan, N., Mulvenna, M., & Bond, R. (2018). Colour Coded Emotion Classification in Mental Health Social Media. Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI 2018). Swindon, United Kingdom: BCS.
Publisher
BCS: The Chartered Institute for I.T.
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DOI
10.14236/ewic/HCI2018.172
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PubMed Central ID
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Article
Language
en