Using eye-tracking, we investigate on-line processing of idioms in a biasing story context by native and non-native speakers of English. The stimuli are idioms used figuratively (at the end of the day – ‘eventually’), literally (at the end of the day – ‘in the evening’), and novel phrases (at the end of the war). Native speaker results indicate a processing advantage for idioms over novel phras...

This report summarizes the objectives and evaluation of the SemEval 2015 task on the sentiment analysis of figurative language on Twitter (Task 11). This is the first sentiment analysis task wholly dedicated to analyzing figurative language on Twitter. Specifically, three broad classes of figurative language are considered: irony, sarcasm and metaphor. Gold standard sets of 8000 training tweets...

Language is the main communication device to represent the environment and share a common understanding of the world that we perceive through our sensory organs. Therefore, each language might contain a great amount of sensorial elements to express the perceptions both in literal and figurative usage. To tackle the semantics of figurative language, several conceptual properties such as concrete...

The present study aimed firstly at investigating the impact of translators' style on figurative language translation from English into Persian. Secondly, it intended to find which strategies were most frequently adopted by Persian translators to translate figures of speech into Persian. Lastly, the study sought to check the extent of transference of figurative features of literary texts in Engl...

Metaphor and simile research has traditionally focused on the projection of content from vehicle to topic, thereby revealing new meaning in the topic. We show that the meaning of vehicles also changes during figurative language understanding. Participants read a poem that likens the temporal self to a snake being divided by a machete, and were asked to draw the snake. Against prototypical snake...

This paper describes the system used by the ValenTo team in the Task 11, Sentiment Analysis of Figurative Language in Twitter, at SemEval 2015. Our system used a regression model and additional external resources to assign polarity values. A distinctive feature of our approach is that we used not only wordsentiment lexicons providing polarity annotations, but also novel resources for dealing wi...

Cognitive linguists contend that learners’ awareness of motivations is the key in not only second language acquisition but also figurative language learning. Two cognitive-oriented methods are proposed to raise L2 learners’ awareness on metaphoric/metonymic expressions and to enhance retention: instruction involving conceptual metaphors (CM) and instruction involving metaphoric mappings (MM). T...

Similes are easily obtained from web-driven and casebased reasoning approaches. Still, generating thoughtful figurative descriptions with meaningful relation to narrative context and author style has not yet been fully explored. In this paper, the author prepares the foundation for a computational model which can achieve this level of aesthetic complexity. This paper also introduces and evaluat...

In the past we have witnessed our machine learning method for sentiment analysis coping well with figurative language, but determining with uncertainty the polarity of mildly figurative cases. We have shown that for these uncertain cases, a rule-based system should be consulted. We evaluate this collaborative approach on the ”Rotten Tomatoes” movie reviews dataset and compare it with other stat...

Figurative language poses a serious challenge to NLP systems. The use of idiomatic and metaphoric expressions is not only extremely widespread in natural language; many figurative expressions, in particular idioms, also behave idiosyncratically. These idiosyncrasies are not restricted to a non-compositional meaning but often also extend to syntactic properties, selectional preferences etc. To d...