Publication | Open Access
SemEval-2007 task 14
601
Citations
9
References
2007
Year
Unknown Venue
Artificial IntelligenceEngineeringIntelligent SystemsMultimodal Sentiment AnalysisEvaluation StrategyLarge-scale DatasetsCorpus LinguisticsJournalismSentiment AnalysisText MiningNatural Language ProcessingApplied LinguisticsComputational LinguisticsSemeval-2007 Task 14Affective ComputingNews HeadlinesDocument ClassificationLanguage StudiesNews SemanticsContent AnalysisComputer ScienceDataset CreationAffective TextPositive/negative PolarityAutomated ReasoningEmotionLinguisticsEmotion RecognitionOpinion Aggregation
The "Affective Text" task focuses on the classification of emotions and valence (positive/negative polarity) in news headlines, and is meant as an exploration of the connection between emotions and lexical semantics. In this paper, we describe the data set used in the evaluation and the results obtained by the participating systems.
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