This paper presents a headline emotion classification approach based on frequency and co-occurrence information collected from the World Wide Web. The content words of a headline (nouns, verbs, adverbs and adjectives) are extracted in order to form different bag of word pairs with the joy, disgust, fear, anger, sadness and surprise emotions. For each pair, we compute the Mutual Information Scor...

Headline summaries of multi-document clusters enable efficient navigation and selection of content, provided headlines are of sufficient quality. This study compares several methods for automated headline extraction, with considerable variation in length. The reliability of the automated evaluation is validated by a comparison with human produced headlines, taking into consideration the variabi...

Nathalie Veyrat1, Christelle Aurélie Maud Robert2, Ted Christiaan Johannes Turlings1 & Matthias 3 Erb2,* 4 1 Laboratory for Fundamental and Applied Research in Chemical Ecology, University of Neuchâtel, Rue 5 Emile-Argand 11, 2009 Neuchatel, Switzerland 6 2 Institute of Plant Sciences, University of Bern, Altenbergain 21, 3013 Bern, Switzerland 7 *Correspondence author: Email: matthias.erb@ips....

This paper suggests an explanatory functional characterization of newspaper headlines. Couched within Sperber and Wilson’s (1986) relevance theory, the paper makes the claim that headlines are designed to optimize the relevance of their stories for their readers: Headlines provide the readers with the optimal ratio between contextual effect and processing effort, and direct readers to construct...