2017/05/02 by D. B. Skillicorn, David B. Skillicorn, Skillicorn, D. B. +9
Computer Science · Psychology · #FOS: Computer and information sciences #I.2.9 #Mental Health Research Topics #Mental Health via Writing #Personality Traits and Psychology #Robotics (cs.RO) #cs.RO
paper · pdf · doi:10.48550/arxiv.1705.00786
arxiv created 2017/05/02 · openalex publication_date 2017/05/02 · arxiv updated 2017/05/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Social robots need to understand the affective state of the humans with whom they interact. Successful interactions require understanding mood and emotion in the short term, and personality and attitudes over longer periods. Social robots should also be able to infer the desires, wishes, and preferences of humans without being explicitly told. We investigate how effectively affective state can be inferred from corpora in which documents are plausible surrogates for what a robot might hear. For mood, emotions, wishes, desires, and attitudes we show highly ranked documents; for personality dimensions, estimates of ground truth are available and we report performance accuracy. The results are surprisingly strong given the limited information in short documents.