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Evaluation Datasets for Twitter Sentiment Analysis: A survey and a new dataset, the STS-Gold.

, , , and . ESSEM@AI*IA, volume 1096 of CEUR Workshop Proceedings, page 9-21. CEUR-WS.org, (2013)

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Ontology-Based Protein-Protein Interactions Extraction from Literature Using the Hidden Vector State Model., , and . ICDM Workshops, page 736-743. IEEE Computer Society, (2008)Dynamic joint sentiment-topic model., , , and . ACM TIST, 5 (1): 6:1-6:21 (2013)Approaches for resolving dynamic IP addressing., , , and . Internet Research, 7 (3): 208-216 (1997)Neural Storyline Extraction Model for Storyline Generation from News Articles., , and . NAACL-HLT, page 1727-1736. Association for Computational Linguistics, (2018)SentiCircles for Contextual and Conceptual Semantic Sentiment Analysis of Twitter., , , and . ESWC, volume 8465 of Lecture Notes in Computer Science, page 83-98. Springer, (2014)Training the Hidden Vector State Model from Un-annotated Corpus., , and . International Conference on Computational Science (2), volume 4488 of Lecture Notes in Computer Science, page 378-385. Springer, (2007)Extracting Protein-Protein Interaction based on Discriminative Training of the Hidden Vector State Model., and . BioNLP, page 98-99. Association for Computational Linguistics, (2008)A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model., , , and . Entropy, 17 (9): 6007-6024 (2015)Learning sentiment classification model from labeled features.. CIKM, page 1685-1688. ACM, (2010)Semantic Patterns for Sentiment Analysis of Twitter., , , and . International Semantic Web Conference (2), volume 8797 of Lecture Notes in Computer Science, page 324-340. Springer, (2014)