2015 | OriginalPaper | Buchkapitel
Language Variety Identification Using Distributed Representations of Words and Documents
Autoren: Marc Franco-Salvador, Francisco Rangel, Paolo Rosso, Mariona Taulé, M. Antònia Martít
Language variety identification is an author profiling subtask which aims to detect lexical and semantic variations in order to classify different varieties of the same language. In this work we focus on the use of distributed representations of words and documents using the continuous Skip-gram model. We compare this model with three recent approaches: Information GainWord-Patterns, TF-IDF graphs and Emotion-labeled Graphs, in addition to several baselines. We evaluate the models introducing the Hispablogs dataset, a new collection of Spanish blogs from five different countries: Argentina, Chile, Mexico, Peru and Spain. Experimental results show state-of-the-art performance in language variety identification. In addition, our empirical analysis provides interesting insights on the use of the evaluated approaches.
