2012
DOI: 10.1162/coli_a_00095
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Modality and Negation: An Introduction to the Special Issue

Abstract: Traditionally, most research in NLP has focused on propositional aspects of meaning. However, to truly understand language, extra-propositional aspects are equally important. Modality and negation typically contribute a lot to these extra-propositional meaning aspects. While modality and negation have often been neglected by mainstream computational linguistics, interest has grown in recent years, as evidenced by several annotation projects dedicated to these phenomena. Researchers have started to work on mode… Show more

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Cited by 100 publications
(66 citation statements)
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“…These tools use not only linguistic cues to resolve expression uncertainty problems, but also establish the factuality of events and statements using experts' opinions and additional necessary sources. For an overview of related content annotation and automation efforts, see (Morante and Sporleder, 2012) and Pustejovsky, 2009, Sauri andPustejovsky, 2012 Rubin and Vashchilko, 2012).…”
Section: Online Deception Detection Toolsmentioning
confidence: 99%
See 1 more Smart Citation
“…These tools use not only linguistic cues to resolve expression uncertainty problems, but also establish the factuality of events and statements using experts' opinions and additional necessary sources. For an overview of related content annotation and automation efforts, see (Morante and Sporleder, 2012) and Pustejovsky, 2009, Sauri andPustejovsky, 2012 Rubin and Vashchilko, 2012).…”
Section: Online Deception Detection Toolsmentioning
confidence: 99%
“…(For a comprehensive overview of the field of opinion-mining and/or sentiment analysis, see Pang and Lee (2008) and a more recent survey by Liu (2012) as well as the introductory article by Thelwall (Forthcoming, 2016) in this book which is specifically focused on sentiment analysis tools for social media. The work on identification of factuality or factivity in text-mining ((e.g., Sauri and Pustejovsky, 2009, Sauri and Pustejovsky, 2012, Morante and Sporleder, 2012) stems back to the idea that people exhibit various levels of certainty (or epistemic modality) in their speech, and that these levels are marked linguistically (e.g., "maybe", "perhaps" vs "probably" and "for sure") and can be identified with text analytical techniques (Rubin, 2006a, Rubin et al, 2004. Text analysis for factuality and writer's certainty is more beneficial to enhance deception detection capabilities than currently acknowledged in the field.…”
Section: Subjectivity and Opinion Mining Or Sentiment Analysismentioning
confidence: 99%
“…Uncertainty, in this sense, is "a linguistic and epistemic phenomenon in texts that captures the source's estimation of a hypothetical state of affairs being true" (Rubin, 2010). The work on identification of factuality or factivity in text-mining (e.g., Morante & Sporleder, 2012;Saurí & Pustejovsky, 2009 stems from the idea that people exhibit various levels of certainty in their speech and that these levels are marked linguistically (e.g., maybe, perhaps vs. probably and for sure) and can be identified with NLP techniques (Rubin, 2006;Rubin, Kando, & Liddy, 2004;Rubin, Liddy, & Kando, 2006). For example, empirically analyzed a writer's (un)certainty, or epistemic modality, as a linguistic expression of an estimated likelihood of a proposition being true.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Detecting uncertainty in natural language texts has received a considerable amount of attention in the last decade (Farkas et al, 2010;Morante and Sporleder, 2012). Several manually annotated corpora have been created, which serve as training and test databases of state-of-the-art uncertainty detectors based on supervised machine learning techniques.…”
Section: Introductionmentioning
confidence: 99%