The paper describes the first sophisticated negation scope detection system for Twitter sentiment analysis. The system has been evaluated both on existing corpora from other domains and on a corpus of English Twitter data (tweets) annotated for negation. It produces better results than what has been reported in other domains and improves the performance on tweets containing negation when incorp...

In this paper, we present a system for detecting negation in English text. We address three tasks: negation cue detection, negation scope resolution and negated event identification. We pose these tasks as sequence labeling problems. For each task, we train a Conditional Random Field (CRF) model on lexical, structural, and syntactic features extracted from labeled data. The models are trained a...

Negation is present in all human languages and it is used to reverse the polarity of part of statements that are otherwise affirmative by default. A negated statement often carries positive implicit meaning, but to pinpoint the positive part from the negative part is rather difficult. This paper aims at thoroughly representing the semantics of negation by revealing implicit positive meaning. Th...

BACKGROUND Most methods for negation detection in clinical text have been developed for English text, and there is a need for evaluating the feasibility of adapting these methods to other languages. A Swedish adaption of the English rule-based negation detection system NegEx, which detects negations through the use of trigger phrases, was therefore evaluated. RESULTS The Swedish adaption of N...

Negation cue detection involves identifying the span inherently expressing negation in a negative sentence. In Chinese, negative cue detection is complicated by morphological proprieties of the language. Previous work has shown that negative cue detection in Chinese can benefit from specific lexical and morphemic features, as well as cross-lingual information. We show here that they are not nec...

We propose a scheme for explicitly modeling and representing negation of word n-grams in an augmented word n-gram feature space. For the purpose of negation scope detection, we compare 2 methods: the simpler regular expression-based NegEx, and the more sophisticated Conditional Random Field-based LingScope. Additionally, we capture negation implicitly via word biand trigrams. We analyze the imp...

Several corpora have been annotated with negation scope—the set of words whose meaning is negated by a cue like the word “not”—leading to the development of classifiers that detect negation scope with high accuracy. We show that for nearly all of these corpora, this high accuracy can be attributed to a single fact: they frequently annotate negation scope as a single span of text delimited by pu...

Detecting negated concepts in clinical texts is an important part of NLP information extraction systems. However, generalizability of negation systems is lacking, as cross-domain experiments suffer dramatic performance losses. We examine the performance of multiple unsupervised domain adaptation algorithms on clinical negation detection, finding only modest gains that fall well short of in-doma...

What strategies does human vision use to attend to faces and their features? How are such strategies altered by 2-D inversion or photographic negation? We report two experiments in which these questions were studied with the flicker task of the change-blindness literature. In experiment 1 we studied detection of configural changes to the eyes or mouth, and found that upright faces receive more ...