Miner, Adam and Chow, Amanda and Adler, Sarah and Zaitsev, Ilia and Tero, Paul and Darcy, Alison and Paepcke, Andreas Conversational Agents and Mental Health: Theory-Informed Assessment of Language and Affect. Technical Report. Stanford InfoLab.
A study deployed the mental health Relational Frame Theory as grounding for an analysis of sentiment dynamics in human-language dialogs. The work takes a step towards enabling use of conversational agents in mental health settings. Sentiment tendencies and mirroring behaviors in 11k human-human dialogs were compared with behaviors when humans interacted with conversational agents in a similar-sized collection. The study finds that human sentiment-related interaction norms persist in human-agent dialogs, but that humans are twice as likely to respond negatively when faced with a negative utterance by a robot than in a comparable situation with humans. Similarly, inhibition towards use of obscenity is greatly reduced. We introduce a new Affective Neural Net implementation that specializes in analyzing sentiment in real time.
|Item Type:||Techreport (Technical Report)|
|Deposited By:||Andreas Paepcke|
|Deposited On:||13 May 2016 15:12|
|Last Modified:||13 May 2016 15:24|
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