Workshop on Computational Linguistics and Clinical Psychology 2016.
Abstract
The sharing of emotional material is central to the process of
psychotherapy and emotional problems are a primary reason for seeking
treatment. Surprisingly, very little systematic research has been done
on patterns of emotional exchange during psychotherapy. It is likely
that a major reason for this void in the research is the enormous cost
of annotating sessions for affective content. In the field of NLP,
there have been major strides in the creation of algorithms for
sentiment analysis, but most of this work has focused on written
reviews of movies and twitter feeds with little work on spoken
dialogue. We have created a new database of 97,497 utterances from
psychotherapy transcripts labeled by humans for sentiment. We describe
this dataset and present initial results for models identifying
sentiment. We also show that one of the best models from the
literature, trained on movie reviews, performed below many of our
baseline models that trained on the psychotherapy corpus.
Links
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Bib Entry
@InProceedings{TDSAIS2016, title={Is Sentiment in Movies the Same as Sentiment in Psychotherapy? Comparisons Using a New Psychotherapy Sentiment Database}, author={Tanana, Michael and Dembe, Aaron and Soma, Christina S and Atkins, David and Imel, Zac and Srikumar, Vivek} booktitle = {Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality}, month = {June}, year = {2016} }