The paper introduces a new annotated French data set for Sentiment Analysis, which is a currently missing resource. It focuses on the collection from Twitter of data related to the socio-political debate about the reform of the bill for wedding in France. The design of the annotation scheme is described, which extends a polarity label set by making available tags for marking target semantic are...

Various text mining algorithms require the process of feature selection. High-level semantically rich features, such as figurative language uses, speech errors etc., are very promising for such problems as e.g. writing style detection, but automatic extraction of such features is a big challenge. In this paper, we propose a framework for figurative language use detection. This framework is base...

In this paper, we describe the approach used by the UPF-taln team for tasks 10 and 11 of SemEval 2015 that respectively focused on “Sentiment Analysis in Twitter” and “Sentiment Analysis of Figurative Language in Twitter”. Our approach achieved satisfactory results in the figurative language analysis task, obtaining the second best result. In task 10, our approach obtained acceptable performanc...

Methods Data were collected during 2 home visits. During the “drawing interview”, children were asked to draw a picture of the last time they were sick; if they did not select an asthma attack, they were asked to do so during the second visit. During the “figurative process interview”, children were shown a piece of paper with a point on a horizontal line, which represented an asthma attack. Th...

Do listeners process literal and figurative speech differently? Research testing interpretation times has resulted in mixed findings. Some researchers have found that figurative language is processed more slowly than literal language (e.g. Noveck et.al 2001) whereas others have not (e.g. Glucksberg 2003, Gibbs & Tendahl 2006). This may be due to limitations of standard reaction time methodology...

This paper describes our contribution to the SemEval-2015 Task 11 on sentiment analysis of figurative language in Twitter. We considered two approaches, classification and regression, to provide fine-grained sentiment scores for a set of tweets that are rich in sarcasm, irony and metaphor. To this end, we combined a variety of standard lexical and syntactic features with specific features for c...

In this paper we propose a methodology for sentiment analysis of figurative language which applies Word Sense Disambiguation and, through an n-gram graph based method, assigns polarity to word senses. Polarity assigned to senses, combined with contextual valence shifters, is exploited for further assigning polarity to sentences, using Hidden Markov Models. Evaluation results using the corpus of...

In this paper, we investigate human visual perception and establish a body of ground truth data elicited from human visual studies. We aim to build on the formative work of Ren, Eakins and Briggs who produced an initial ground truth database. Human subjects were asked to draw and rank their perceptions of the parts of a series of figurative images. These rankings were then used to score the per...

the present article is about the zemakhshari’s al-kashaf commentary. in this book the author has paid a lot of attention to the literary aspects of quran.one of the most important aspects of this commentary is it’s lexical analysis of the words. the researcher then compares these analyses with those which exist in quran while providing reasons and explaining his views about them.