International Journal of Interactive Multimedia and Artificial Intelligence · 2014 · 14 citations · 3 references
ComputingComputer SciencePsychologyMachine LearningSocial Media AnalyticsText AnalyticsAffective ComputingAffective State DetectionPersonality TraitsSocial MediaText MiningTrait TheoryAffect ClassificationAffective FeaturesAutomatic Emotion RecognitionEmotion DetectionEysenck Personality TheoryText-based Emotion AnalysisText-based Emotion DetectionText-based Emotion Recognition
This work proposes a platform for estimating personality and happiness. Starting from Eysenck's theory about human's personality, authors seek to provide a platform for collecting text messages from social media (Whatsapp), and classifying them into different personality categories. Although there is not a clear link between personality features and happiness, some correlations between them could be found in the future. In this work, we describe the platform developed, and as a proof of concept, we have used different sources of messages to see if common machine learning algorithms can be used for classifying different personality features and happiness.
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Automatic recognition of personality in conversation
François Mairesse, Marilyn Walker · 2006 · 80 citations · Full text