Big data to assess genre-specific features of the machine translation output of online travel reviews in Spanish
DOI:
https://doi.org/10.7203/qf.0.24667Keywords:
Machine translation, post-editing, consumer generated content, big data, tourism reviews.
Abstract
Big data analysis such as user-generated content and specifically online consumer reviews has attracted considerable attention in recent years due to its numerous research opportunities and commercial applications in almost all fields of knowledge. The origin of this digital genre in the oral tradition highlights the spontaneous features of the spoken language that are reflected in the written text that has its own characteristics depending on the user’s culture and language. By comparing a corpus of 2,000 reviews, this paper proposes the identification and analysis of the unique characteristics of this new digital genre to determine the behavior of machine translation of users' reviews into Spanish. Thus, the aim of this work is to study the tourism reviews translated into Spanish and identify how MT handles the main characteristics that confer naturalness and credibility to this genre.
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Miguel Ángel Candel-Mora, Universitat Politècnica de València
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