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Tweester at SemEval-2016 Task 4: Sentiment Analysis in Twitter Using Semantic-Affective Model Adaptation.

, , , , , , , , and . SemEval@NAACL-HLT, page 155-163. The Association for Computer Linguistics, (2016)

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Objective Language Feature Analysis in Children with Neurodevelopmental Disorders During Autism Assessment., , , , , and . INTERSPEECH, page 2721-2725. ISCA, (2016)SAIL: A hybrid approach to sentiment analysis., , , and . SemEval@NAACL-HLT, page 438-442. The Association for Computer Linguistics, (2013)GOAALLL!: Using sentiment in the world cup to explore theories of emotion., , , , , and . Image Vis. Comput., (2017)COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization., , , , , , , and . EURASIP J. Image Video Process., (2017)Extracting Situation Frames from Non-English Speech: Evaluation Framework and Pilot Results., , and . INTERSPEECH, page 2123-2127. ISCA, (2017)Linguistic analysis of differences in portrayal of movie characters., , , , and . ACL (1), page 1669-1678. Association for Computational Linguistics, (2017)Tweester at SemEval-2017 Task 4: Fusion of Semantic-Affective and pairwise classification models for sentiment analysis in Twitter., , , , , , , , , and . SemEval@ACL, page 675-682. Association for Computational Linguistics, (2017)SAIL-GRS: Grammar Induction for Spoken Dialogue Systems using CF-IRF Rule Similarity., , and . SemEval@COLING, page 508-511. The Association for Computer Linguistics, (2014)Predicting therapist empathy in motivational interviews using language features inspired by psycholinguistic norms., , , , and . INTERSPEECH, page 1947-1951. ISCA, (2015)The ELISA Situation Frame extraction for low resource languages pipeline for LoReHLT'2016., , , , , and . Mach. Transl., 32 (1-2): 127-142 (2018)