Characterizing online social translation

Aims

Since the early days of the Internet, translators have made use of various online platforms to collaborate, socialize and otherwise interact not only with each other, but also with other social agents, including clients, subject matter experts, and non-translators interested in the profession. These platforms have included electronic mailing lists such as listserves, which translators have used to discuss terminology questions and computer problems, and chat socially about non-translation topics (Plassard 2010); specialized social networking sites such as Proz or TranslatorsCafe, where translators bid on translation contracts, and share knowledge via discussion forums, collaborative glossaries, and client-ranking databases (McDonough 2007; Pym, Orrego-Carmona, and Torres-Simón 2016; Risku and Dickinson 2009); blogs, which translators use to enhance their status and to make translation more visible to those outside of the profession (Dam 2013); and mainstream social networking sites such as Facebook and Twitter, which can help translators share content such as status updates, photos and videos related to their professional activities (Desjardins 2017).

This special issue aims to examine the social, collaborative nature of translation in online spheres under the theme of “online social translation”, a term that, as we will discuss, builds upon the concept of “community translation” described by Minako O’Hagan (2011, 12). The articles in this special issue have varying aims and discuss translation in different online platforms and geographic regions, but they all explore how translation occurs in online environments and the inherent social nature of the interactions between the various agents involved in producing, disseminating and – in some cases – receiving these translations.

The “social” in online social translation

We have drawn the modifier “social” from social media studies. As social media researcher Christian Fuchs (2007, 4) argues, information and communication technologies and society are mutually dependant, as humans in society design and use the technology that in turn “enables and constrains, human cognition, communication, and cooperation”. Such mutual dependence can be seen in the definition of social media offered by Kaplan and Haenlein (2010, 61), who use the term to refer to internet-based applications that build on Web 2.0 technologies and allow user-generated content to be exchanged. The term Web 2.0, popularized in the early 2000s, refers to a shift in World Wide Web platforms from fairly static websites to more interactive, participatory and collaboratively generated content and applications (Kaplan and Haenlein 2010, 60–61; Jiménez-Crespo 2017, 44). Some authors distinguish between Web 2.0 and Web 3.0 platforms, arguing that Web 2.0 technologies (such as discussion boards, blogs and social media) inherently support communication and competition, while Web 3.0 technologies (such as wikis) support collaboration and cooperative labor (Fuchs et al. 2010). As we will discuss, though, cooperative technologies such as wikis can also have a communicative function, and collaborative platforms like Wikipedia can be equally competitive and cooperative (Jones 2019, 78). For this reason, Fuchs et al. (2010, 50–51) suggest that their model should be seen as an integrated one, since Web platforms can include Web 1.0, 2.0 and 3.0 features to varying degrees. They argue, though, that currently the Web consists largely of Web 1.0 and 2.0 technologies, with cooperative technologies such as wikis being a minority (52): for a truly cooperative Web 3.0 to exist, social transformation – rather than just technological transformation – would need to take place (56).

More recently, José Van Dijck (2013, 8) describes four broad, but not exhaustive, categories of social media: the first are “social network sites”, such as Facebook, Twitter, and LinkedIn, which promote interpersonal contact and facilitate personal, professional geographic weak-tie connections, the second are “user-generated content sites”, such as YouTube or Wikipedia, which support creativity and allow for content created by users – professional and amateur alike – to be exchanged, the third are “trading and marketing sites”, such as Amazon and Craigslist, which exist primarily to exchange or sell products, and the fourth are “play and game sites”, such as Farmville. Overlap between these categories is, of course, possible, since a social networking site such as Twitter also allows users to share content such as photos, while user-generated content sites such as Wikipedia can also allow users to engage with one another via comment or discussion pages (2013, 8–9); likewise, blogging platforms such as WordPress and Blogger allow users to generate their own content by writing blog posts, but also to engage with other Internet users via comment feeds.

Within translation studies, research interests have leaned heavily on the first and second categories, with scholars investigating translation in/of social networking sites (Desjardins 2017; Lenihan 2011; Mesipuu 2012), mining social networking sites and blogs for insight into translator opinions (e.g. Läubli and Orrego-Carmona 2017; Flanagan 2016), studying the motivations of those who participate in user-generated content translation projects (e.g. Cámara de la Fuente 2015; McDonough Dolmaya 2012; Olohan 2014), exploring how knowledge about translation is depicted in user-generated content sites like Wikipedia (Torres-Simón 2018), or reflecting more broadly on translation practices and policies within user-generated content sites (Jones 2018, 2019; McDonough Dolmaya 2015, 2017; Sánchez Ramos 2018, 2019). Some attention has also been given to translation marketing sites such as ProZ or TranslatorsCafe (McDonough 2007; Perrino 2009; Pym, Orrego-Carmona, and Torres-Simón 2016; Risku and Dickinson 2009), although here, too, the focus often also includes the social networking or user-generated content aspects of these platforms.

Online social translation is collaborative

While translation in any form can be a collaborative endeavor, collaboration is a visible and inherent feature of online social translation. As Van Dijck (2013, 11) suggests, using the word social to modify media “implies that [social media] platforms are user centered and that they facilitate communal activities”. Maintaining that social media facilitates or enhances human networks, Van Dijck suggests that while people use these networks to disseminate their ideas and values, the networks, in turn, affect what people do and think (ibid.). Translation that takes place within such platforms is therefore inherently collaborative – an activity that both shapes and is shaped by Internet users.

To further our reflection on the notion of collaboration in online social translation, it is helpful to consider a definition proposed by Michael Schrage, who was writing in the early days of the Internet and thinking about how electronic environments could support collaboration:

Collaboration is the process of shared creation: two or more individuals with complementary skills interacting to create a shared understanding that none had previously possessed or could have come to on their own. Collaboration creates a shared meaning about a process, a product or an event. (Schrage 1990, 40)

Noteworthy in this definition is that collaboration does not imply equal contribution from all parties: just interaction and sharing of skills and ideas. Nor is collaboration restricted to cases where two or more translators work together: Schrange’s definition allows for people with complementary skills, including translators, editors, authors, clients and publishers to work together to create a shared product. And while such a notion of collaboration may seem very broad, it is in line with views expressed by scholars who have studied collaborative translation (cf. Cordingley and Manning [2017, 23] for a discussion of the challenges of defining collaborative translation).

If we apply this idea to online social translation, we can find many examples of collaborative practices where translators work not only with other translators, but also with others who will shape the translations, namely Internet users who review, comment on or otherwise influence the way the translation is produced and received. Julie McDonough Dolmaya (2015) has discussed how Wikipedians edit translated Wikipedia articles, revising and rewriting the articles until they sometimes do not resemble the source text at all; such “translations” are the work of translators and non-translators alike, and are always evolving, challenging the notion that there is a definitive, final version of a translation. In this same vein, Henry Jones (2019, 79) has argued that translation scholars need to consider both the cohesive and disruptive forces that shape the way online content is generated by the “wide range of individual voices, conflicting perspectives and divergent motivations” in spaces such as Wikipedia. Chuan Yu (2019) discusses instances in which Internet users comment upon a collaboratively produced translation, leading the translators to make changes to the text and therefore shaping the final product. And Renée Desjardins (2019), offers examples that show how even self translation can be a collaborative practice in online social media, arguing that in some cases, “self” translations are in fact produced by teams of content curators who represent a social media influencer.

Pym (2011, 77) suggests that “collaborative translation” is a synonym for crowdsourcing and community translation, and is used to describe “group translating where the work is largely voluntary”. He, therefore, suggests that “volunteer translation” would be a more appropriate term to describe this kind of translation. And yet, collaborative translation describes a broader range of activities than just crowdsourcing, has existed as a practice since long before the Internet, and does not need to be a volunteer activity, as Cordingley and Manning (2017, 15–16) discuss. While crowdsourcing is certainly a collaborative activity, in that multiple translators contribute to the translation product, it is just one form of collaborative translation, a point of view also shared by Cordingley and Manning (2017, 16).

Building on the concept of “community translation”

When O’Hagan discussed community translation in 2011, she suggested that it was “tied to the online community particularly in the specific context of Web 2.0” (2011, 12) and that it, therefore, referred to “specific translation practices that are unfolding on the Internet as the central foci”. By proposing the term online social translation, we would like to build upon the concept O’Hagan was proposing, but address the difficulty that she acknowledges – namely, that the term community translation can also be used as an analogue to community interpreting, to refer to translating public information for immigrant populations, and can, therefore, cause confusion when it is being used to refer to translation in Web 2.0 contexts (O’Hagan 2011, 12). By adopting a term that draws on the definition of social media, this ambiguity should be reduced.

We have also added the modifier “online” before “social translation” to address the potential confusion noted by Miguel Jiménez-Crespo (2017, 27), who argues that social translation is often used to refer to “translations that occur within any given society”, and that while some scholars use the term synonymously with crowdsourcing, other associate social translation with “activist approaches to translation”. Adding the modifier “online” should help limit the contexts in which social translation is deemed to take place. Moreover, it brings online social translation more in line with the term online social media, the term used to distinguish between the traditional forms of social media and the more contemporary, Web-2.0-based forms of social media (Desjardins 2017, 13–15). Finally, it also responds to Gernot Hebenstreit’s argument (2019) that technology is the main characteristic distinguishing social translation from general translation.

In response to Jiménez-Crespo’s second point, namely that social translation is sometimes used synonymously with crowdsourced translation (2017, 27), we make a distinction between the two terms. Indeed, we see crowdsourced translation as a term that overlaps to a great extent with online social translation but is more limited in scope. Crowdsourced translation refers to the practice of internet users collaboratively translating online texts for little or no financial reward (McDonough Dolmaya 2019, 124), but does not encompass activities such as fan translation, as crowdsourced translation projects are generally solicited by content owners, while fan translators are generally engaging in copyright infringement. Online social translation, by contrast, is not restricted by the project initiator: both bottom-up and top-down translation initiatives (Jiménez-Crespo 2017, 25) can be considered online social translation, provided they involve a social media platform. For that reason, online social translation overlaps with both crowdsourcing and what Jiménez-Crespo (2017, 25) describes as online collaborative translation, a term that encompasses collaborative translation initiated on the Web by self-organized online communities whose motivations are not purely monetary.

Scope of coverage of this special issue

This special issue of Translation Studies looks at the phenomenon of online collaborative practices in translation from different perspectives and scenarios. As a direct result of technological, social and cultural changes, Web 2.0 platforms provide numerous opportunities for Internet users to take part in different online activities, contributing to the idea of translation democratization and shaping technology (O’Hagan 2016, 934). The contributors to this special issue emphasize various aspects of online social translation practices. They delimit and define the scope of activities that can be considered social translation, introduce online social translation into translator training, examine the roles played by those participating in online social translation initiatives, and discuss the application of semi-automated tools in crowdsourced projects. Given that most existing translation studies research has been largely focused on user-generated content and social networking sites, it is not surprising that the proposals we received did so as well. This special issue, therefore, focuses exclusively on translation from these two categories. Nonetheless, we have attempted to include articles offering different perspectives in a range of contexts, including fansubbing communities in Argentina and Spain, Instagram and Facebook users in a largely North American context, crowdsourcing platforms in the UK and China, and Spanish Wikipedia/Wikimedia-Spain.

As discussed in the previous section, the terminology related to social translation is not well established. The first article by Gernot Hebenstreit helps shed light on this terminological quagmire. The author adopts a framework proposed by Anita Nuopponen (2007) to assess the conceptual characteristics related to the agents involved in social translation, the objects of translation projects, the instruments used to facilitate the translation process, the ways of carrying out the translation (i.e. the translation process itself), the purpose of the social translation projects and the motivations of the translators, the results of the translation process, the (virtual) location in which social translation occurs, and the phases or workflows of the translation platforms. Determining that the main characteristic that distinguishes social translation from translation in general is the technology used, Hebenstreit discusses the difficulty of coining terms for concepts that change over time and proposes “social-media-driven translation” as the most appropriate term. Hebenstreit’s contribution can serve as a guide for researchers as they wade through the terminological debates surrounding online collaborative translation practices in Web 2.0 spaces.

The next article, by Renée Desjardins, contributes to the terminological challenge posed by social translation. She argues that terms such as “social translation,” “crowdsourced translation” and “user-generated translation” are not synonyms before proposing, based on previous research (Desjardins 2017), the term “social translation” to refer to translation activity taking place on different online social media. Then, relying on a number of authentic examples, she provides a preliminary and provisional framework of what she terms “online social self-translation”, dividing the phenomenon into three categories: “real” social self-translation, where the translation is done by the same person who authored the content, “illusory” self-translation, where the translation is created by a machine and is presented to users as if it were generated by the human who authored the content, and “hyperreal” self-translation, where the translation is provided by the team managing an individual’s social media account and therefore seems to be generated by the individual account holder. Desjardins’ work will undoubtedly be of interest to researchers seeking to study self-translation in online spheres and to those considering the various forms (self-) translation can take on social networking and user-generated content platforms.

In her contribution to the pedagogical aspects of online social translation, María Calzada Pérez applies Donald Kiraly’s constructivsm and emergentism, and Roger Lewin’s complexity theory to Wikitrad, a pedagogical project introduced at the Universitat Jaume I (Castellón, Spain) during the 2011–2012 academic year. Her contribution details the implementation and design of Wikitrad, which now encompasses four different university programs whose students translate Wikipedia articles from English into Spanish or Catalan and vice versa. As the author states, social translation now plays an important role in the project, despite the fact it was less focused on social translation in the beginning. Calzada Pérez’s article helps illustrate how incorporating online social translation projects into the classroom can encourage students to develop collaborative translation skills, since Wikitrad promotes the development of collaborative learning zones where instructors, students, professional editors and Wikipedians work together to shape the final translated articles.

Fansubbing is discussed by David Orrego-Carmona, who explores the notion of quality in non-professional subtitling (NPS) communities by drawing on Andrew Chesterman’s (1993, 1997) discussion of functional quality and expectancy norms. Orrego-Carmona carries out a literature review to assess the production and reception conditions of NPS, arguing that this allows quality to be assessed more holistically than models that focus solely on the final product or the process. His study is based on two fansubbing communities: aRGENTeaM, which caters primarily to a Latin American audience, and GrupoTS, which targets Spanish speakers in Spain. In his conclusions, Orrego-Carmona argues that the two communities follow structured and highly controlled processes to ensure their subtitles meet audience needs. Moreover, he notes that there is a balance between both production and reception mainly because the producers and receivers within the NPS communities are fluid, rather than fixed groups: many of the aRGENTeaM translators and revisers were initially part of the user community.

The contribution by Michael En and Boka En examines the notion of “expertise” in online social translation and explores social practices in the LGBTIQ* movement. Building on the concept of community translation (O’Hagan 2011) and crowdsourced translation discussed by Jiménez-Crespo (2017), En and En merge the fields of science and technology studies and social movement studies to discuss knowledge and expertise in relation to what they call community translation in activist environments. The authors explore a translation project initiated by MiGaY, a Vienna-based activist organization devoted to LGBTIQ* migrants in Austria. Based on qualitative research, the authors analyze semi-structured interviews carried out with thirteen participants who had been volunteer translators for the MiGaY project. Strictly speaking, this is not an online social translation project, as the translation did not take place via a Web 2.0 platform; however, the issues discussed by En and En are crucial for online social translation researchers. Given that many online social translation initiatives involve both non-professional and professional translators (cf. Jiménez-Crespo 2017, 23–25), questions about the notion of expertise arise frequently. The questions are also likely to interest researchers in the area of non-professional translation studies, since the points raised by the volunteer translators interviewed by En and En are similar to those mentioned by non-professional translators when reflecting on their role in other volunteer contexts (cf. Antonini et al. 2017).

Much like En and En, who consider how we can define “expertise” when discussing projects that include both professional and non-professional translators, Chuan Yu reflects on how participants see themselves and others in online collaborative translation projects. She adopts an ethnographic methodology and draws on the concept of communities of practice (Wenger 1998) to analyze Yeeyan, China’s largest crowdsourcing translation platform. Yu discusses how the platform is an example of shifting identity roles and meaning negotiation among participants, since they are assigned hierarchal rankings ranging from novice to senior members within the platform itself, but can also position themselves as novices or experts in various subject fields based on their own life experience. As Yu argues, the collaborative translation process in the Yeeyan platform involves a constant back-and-forth of negotiation between members, who see themselves as experts in some contexts, but who defer to those with more expertise in others.

The special issue closes with a contribution from Alessandra Rossetti and Sharon O’Brien, who study the role of volunteers who produce, translate and disseminate healthcare content at the non-profit organization Cochrane. More specifically, Rossetti and O’Brien report on the results of two experiments. The first assesses volunteer satisfaction with a semi-automated controlled language checker (Acrolinx CL checker) in an intralingual translation context: volunteers were asked to revise their previously produced plain language summaries of English medical texts and then comment on their satisfaction with Acrolinx. The second experiment asked Spanish-speaking Cochrane volunteers to rate two machine-translation outputs: the first translation was based on a plain language summary that had not been prepared with Acrolinx, and the second translation was based on the plain language summary that had been revised with Acrolinx. Volunteers who participated in the first experiment were generally in favor of integrating a controlled language checker into the plain language summary workflow. The results of the second experiment indicated that while the MT system produced reasonably fluent results, it seemed to produce approximately the same quality of translation whether it translated the plain language summary produced with Acrolinx or the summary produced without a semi-automated controlled language checker. Given the amount of content generated online, and the need for varying levels of quality when this content is translated, machine translation can play an important role in crowdsourced projects (cf. Jiménez-Crespo 2017, 127–128). Rossetti and O’Brien’s study, therefore, helps illustrate how automated and semi-automated tools could be integrated into online social translation workflows. In particular, they caution that more research should be done to determine whether the use of automated tools as part of the translation or authoring workflow affects the motivation of volunteers.

We are aware that further research is needed on the impact of online social translation. This special issue was able to examine a limited number of social media categories, and more research is therefore needed to better understand how translation takes place in other contexts, including trading/marketing and play/game websites. Another important area that deserves closer scrutiny is the double-sided nature of the Web 2.0 platforms on which online social translation depends. As Veronica Barassi and Emiliano Treré (2012, 1271) remark, while Web 2.0 technologies offer “democratic possibilities for individual engagement and empowerment”, they also enable surveillance, corporate control of user-generated content and the exploitation of the immaterial labor provided by Internet users. Some of these issues have been discussed elsewhere in translation studies (e.g. McDonough Dolmaya 2011) but deserve further scrutiny, particularly for the social media categories other than social networking and user-generated content sites.

Finally, space constraints restricted the number of source and target language combinations that could be discussed. While the authors in this special issue offer perspectives from countries in Asia, Europe, and North and South America, greater attention needs to be given to online social translation in regions such as Australia, Southeast Asia, Africa, the Middle East and Central America. Although we received many high-quality submissions, few (if any) proposed examining these contexts, which indicates that research in this area merits more attention. In particular, endangered and minoritized languages need to be the focus of more research, particularly when it comes to their role in online social translation. We hope that this special issue will inspire additional research in some of these areas.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Julie McDonough Dolmaya is an Associate Professor in the School of Translation at York University’s Glendon campus. Her research interests range from translation, politics and oral history to translation in digital spaces, particularly crowdsourcing. She has published articles on these topics in Meta, Target, The Translator, Translation Studies, and other journals. She is the Secretary of the Canadian Association for Translation Studies and co-editor of the Journal of Internationalization and Localization, published biannually by John Benjamins.

María del Mar Sánchez Ramos is an Associate Professor in translation studies in the Department of Modern Philology at the University of Alcalá (Madrid, Spain), where she currently lectures translation technology. She holds a PhD from the University Jaume I (Castellón, Spain). She has authored numerous articles and book chapters on corpus-based translation studies, translation technology and translator training, and has co-edited volumes and special issues in different national and international journals. She is also the main coordinator of a research project on machine translation and multilingual crisis communication.