Discourse strategies for generating natural-language text
Artificial Intelligence
Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
An empirically based system for processing definite descriptions
Computational Linguistics
Emotions from text: machine learning for text-based emotion prediction
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Fully generated scripted dialogue for embodied agents
Artificial Intelligence
Inter-coder agreement for computational linguistics
Computational Linguistics
Constructing corpora for the development and evaluation of paraphrase systems
Computational Linguistics
Mining opinion features in customer reviews
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
Computational Linguistics
Summarizing threads in blogs using opinion polarity
eETTs '09 Proceedings of the Workshop on Events in Emerging Text Types
Smokey: automatic recognition of hostile messages
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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In this paper we introduce a multi-dimensional annotation scheme for emotional and behavioural assessment in dialogue summaries. To test the soundness both of the annotation scheme and corresponding guidelines, reliability studies with nine independent annotators were carried out. As an illustration of the utility of our scheme, we have applied it to an already published study and verified whether the same conclusions hold. We hope that, in using our scheme, researchers will be able to save a lot of time and effort that, otherwise, would be spent in planning, developing and testing a scheme of their own.