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

The final publication is available at Springer via http://dx.doi.org/10.1007/s10579-013-9220-9[EN] 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).This special issue has been an activity of the WIQ-EI IRSES project (Grant No. 269180) within the FP 7 Marie Curie People Framework of the European Commission.Rosso, P.; Errecalde, ML.; Pinto Avendaño, D. (2013). Analysis of short texts on the Web: introduction to special issue. Language Resources and Evaluation. 47(1):123-126. https://doi.org/10.1007/s10579-013-9220-9123126471Errecalde, M. L., Ingaramo, D., & Rosso, P. (2008). Proximity estimation and hardness of short-text corpora. In Proceedings of the 2008 19th international conference on database and expert systems application, DEXA ’08 (pp. 15–19).Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies, Morgan & Claypool Publishers.Pinto, D., Rosso, P., & Jiménez-Salazar, H. (2011). A self-enriching methodology for clustering narrow domain short texts. Computer Journal, 54(7), 1148–1165