Can you read my mindprint?: Automatically identifying mental states from language text using deeper linguistic features

Interaction Studies 15 (3):359-387 (2014)
  Copy   BIBTEX


Humans routinely transmit and interpret subtle information about their mental states through the language they use, even when only the language text is available. This suggests humans can utilize the linguistic signature of a mental state, comprised of features in the text. Once the relevant features are identified, mindprints can be used to automatically identify mental states communicated via language. We focus on the mindprints of eight mental states resulting from intentions, attitudes, and emotions, and present a mindprint-based machine learning technique to automatically identify these mental states in realistic language data. By using linguistic features that leverage available semantic, syntactic, and valence information, our approach achieves near-human performance on average and even exceeds human performance on occasion. Given this, we believe mindprints could be very valuable for intelligent systems interacting linguistically with humans. Keywords: mental state; linguistic features; mindprint; natural language processing; information extraction



    Upload a copy of this work     Papers currently archived: 74,310

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles


Added to PP

16 (#662,230)

6 months
1 (#415,900)

Historical graph of downloads
How can I increase my downloads?

References found in this work

Cognition and Categorization.Eleanor Rosch & Barbara Lloyd (eds.) - 1978 - Lawrence Elbaum Associates.

Add more references