ABSTRACT
The technologization of translation, a process that has been under way for some time, took a new turn with the advent of the Internet. The creation of a digitally connected world has contributed to an increased and more varied demand for translations, and also a wider range of solutions, including online machine translation (MT) and multilingual resources, made accessible to translation users and providers alike via ever-expanding networks. More recently, the second-generation Web technologies commonly known as ‘Web 2.0’ have turned the Internet into a locus of distributed problem solving that taps into human intelligence through online participation. Described as ‘a connective and collaborative technological environment that enables individuals to get involved in internet-mediated social participation, communication, and collaboration’ (Zhao and Zhu 2014: 418), the second-generation Internet has become a highly connected and interactive place that forms people into networks. In particular, Web 2.0 has focused attention on general Internet users who contribute usergenerated content (UGC) that is distributed and shared among the global online population (Howe 2006). It is in this context that translation itself has emerged as user-generated (O’Hagan 2009; Perrino 2009), with translation being carried out in a collaborative network, as in the case of ‘fan translation’, whereby dedicated fans translate their favourite foreign-language content (O’Hagan 2009). In contrast to this popular, yet largely illegal, form of UGC is the relatively recent phenomenon of the purportedly legitimate solicitation of labour through ‘translation crowdsourcing’. Web 2.0 applications provide a mechanism for the formation of an ad hoc translation workforce through open calls from nonprofit and for-profit organizers of various translation initiatives. Often seen as the catalyst for ‘the rise of the amateurs’ (Howe 2006), the Internet opened up translation as an everyday online activity performed by self-declared translators who produce translations in response to open requests. Facebook’s translation campaign has most comprehensively demonstrated the crowdsourcing model in translation, whereby Facebook user communities were asked to help to translate its website. Unsurprisingly, this caused outrage among professional translators,
who perceived it as nothing but a cost-cutting measure. Despite the controversy and protests, however, the Facebook initiative, officially launched in 2008, succeeded in making the originally English-only Facebook website available in 75 languages within two years (Drugan 2013: 174), rising to 104 languages and dialects by late 2013 (Dombek 2014: 4). Furthermore, the custom-designed translation platform illustrates the key role in translation crowdsourcing played by technology, especially tailored with social networking in mind (Wong et al. 2014). Consequently, this phenomenon has attracted research interest in translation studies focused on key concepts such as ‘collaborative translation’ (Désilets 2007), ‘community translation’ (O’Hagan 2011) and ‘non-professional translation’ (Susam-Saraeva and Pérez-González 2012), among others.
