Do metaphors shape a listener's thinking?

Comments

• Interesting and well-defined task. I am curious if the topic or theme of a talk can affect what you might classify as literal or a figurative language? E.g., In a medical domain "incisive" as in (incisive foramen) is literal, otherwise means sharp, acute remark. Does your approach account for that?

• Please detail on how do you plan to sample the test-set.

--Apappu 12:22, 11 October 2012 (UTC)

Team members

• Yulia Tsvetkov

Project Summary

Metaphors are very powerful communication tools: they help deliver complex concepts and ideas simply and effectively, they can shape listener’s opinion. We hypothesize that the semantic orientation of listener’s comments can be predicted by the amount of the figurative language in a lecture: the more metaphors the speaker uses, the more support he will get from the audience. This project will explore the relation between the amount of metaphors in text and the polarity of listeners feedback.

Dataset

The project will use the TED talks dataset, which contains 667 talks with 19752 comments from active users.

Task

Develop unsupervised, language independent approach to cluster sentences into literal and figurative. Sample a test set of lectures, and manually annotate user comments for each lecture into three categories: positive, negative and neutral. Measure correlation between literal/figurative usages and positive/negative comments.

Evaluation

We will compare our metaphor detection results to the Birke and Sarkar’s (2006) results on the subset of twenty-five verbs that appear in 1,965 sentences, manually labeled L (literal) or N (nonliteral), according to the sense of the target verb. Labeled verbs are publicly available in the TroFi (Trope Finder) Example Base. The baseline f-score obtained by Birke and Sarkar’s (2006) active learning approach is 64.9%.

Related work

C. Sporleder and L. Li. 2009. Unsupervised Recognition of Literal and Non-Literal Use of Idiomatic Expressions. In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009), pages 754–762. Association for Computational Linguistics. pdf, summary.