Analysis of short texts on the Web: introduction to special issue

Abstract

Analysis of web and social media data is a rapidly growing area of research. Researchers seek to extract a wide variety of information from these texts in order to address specific user needs, profile attitudes and intentions, and target advertising, etc., which may require application of the full range of natural processing techniques. However, many of the texts in question¿including news feeds, document titles, FAQs, and tweets¿exist as short, sometimes barely sentence-like snippets that do not always follow the lexical and syntactic conventions assumed by many language processing tools. Many NLP analyses rely on the repetition of specific lexical items throughout the text in order to identify topic, genre, and other features; without sufficient context to enable such analyses, and because of their often eccentric grammatical style, short texts pose a new kind of challenge for language processing research (Errecalde et al. 2008; Pinto et al. 2011).