Abstract
[full article, abstract in English; abstract in Lithuanian]
 Accessing ready-made corpora may not be always easy. This is especially true for less dominant languages such as Persian for which the number of available corpora is very limited. Moreover, most existing corpora are domain specific, which implies that they supply a limited range of genres and text types. They, thus, may not always contain the information the translator is looking for. Drawing on the world wide web as a big corpus, however, is not subject to such limitations. The web, in fact, can be considered as a very large multilingual corpus containing texts in almost all languages and all text types. The present paper reports the results obtained from a collaborative experience in which undergraduate English translation students from the Department of translation Studies of Allameh Tabataba’i University made use of Google search engine and webascorpus web concordancer to extract translationally-relevant data from the web.
Highlights
When language corpora first entered Translation Studies as a discipline, their application was limited to the research on the language of translation and its distinctive features (Baker 1993)
Regarding this feature of corpora, Gileva (2005, 5) states, “ the web cannot really be called a yardstick it may be a very lucrative source of information, which structured in an appropriate way, may present a linguistic playground not worse than that offered by other well-known corpora”
Accessing ready-made corpora may not be always easy. This is especially true for less dominant languages such as Persian for which the number of available corpora is very limited
Summary
When language corpora first entered Translation Studies as a discipline, their application was limited to the research on the language of translation and its distinctive features (Baker 1993). Corpora of different types were used in studies on translation universals (Baker 1993), translator’s style and ideology (Baker 2000) and translation evaluation (Bowker 2000). Among other things, were shown to enhance learner’s source text understanding (Bowker 1998), their understanding of specialized terms (Gavioli & Zanettin 1997) and their knowledge of different text types (López-Rodríguez and Tercedor-Sánchez 2008). They proved useful in providing the student translators with unpredictable and incidental learning (Aston, 1999; Zanettin, 2001). To see whether the Web can really provide translators with the benefits associated with using corpora in translation, it is necessary to first discuss the nature of the Web as a big corpus
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