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Translation Crowdsourcing: The Facebook Way – in Search of Crowd Motivation Magdalena Dombeck


Translation Crowdsourcing: The Facebook Way – in Search of Crowd Motivation Magdalena Dombek SALIS The paper addresses the relatively recent phenomenon of translation crowdsourcing, which makes an open call to unspecified users of the Internet as volunteers to provide translations of given material. This new translation procurement model is closely linked to advances in Internet technology. The so-called Web 2.0 environment promotes user participation in the creation of content on the Internet and presents online crowds with tools to voluntarily undertake translation tasks. Using Facebook translation crowdsourcing initiatives as a case study the paper aims to gain an insight into the factors that may motivate Internet users to contribute free translations. Drawing on research on human motivation, particularly with regard to online collaboration, the paper suggests the design of a collaborative translation platform employed in translation crowdsourcing as a possible factor influencing the motivation of volunteer translators. Further concrete evidence will only be gained through more longitudinal studies.

Keywords: translation crowdsourcing, motivation, Facebook, collaborative translation platform

Introduction

Jeff Howe (2006, 2008) refers to crowdsourcing as a phenomenon which harnesses the power of networked members of the online crowd, who, on their own initiative, undertake tasks that traditionally would be assigned to a group of trained employees or a contractor. Based on this model for work organization, a new form of translation practice has emerged on the Internet – 1


translation crowdsourcing. In this model, Internet users contribute their time and skills voluntarily translating given material at a request of a group, company or organization, usually without being financially rewarded for their efforts.

The use of crowdsourcing to obtain translations is in line with recent advances in Internet technologies which have facilitated new forms of human activity in the online environment. Among these is translation performed with the use of tools and resources such as Machine Translation (MT) engines, collaborative translation platforms, translation memories and terminology databases. Apart from MT which may be targeting lay users, other translation tools used to be specifically designed for professionals but now are made accessible to millions of general Internet users. One such collaborative translation platform was purpose-built in 2008 to introduce crowdsourcing methods into the translation of Facebook, the most renowned social network service.

The aim of this paper is to gain an insight into the motivation of the volunteers who respond to the request of Facebook to translate its content such as user interface (UI) components. While this paper is located in the field of Translation Studies, the paucity of published studies1 on this relatively new phenomenon of translation crowdsourcing or volunteer participation means the nature of this paper is largely exploratory. The paper will first explain what crowdsourcing is and how it has been incorporated into translation, presenting in more detail the translation model 1

However, more recently there is a sign of increasing interest in the topic. For example, at the end of 2011 a special issue of the translation journal Linguistica Antverpiensia NS -Themes in Translation Studies (10/2011) dedicated to the topic was published. Nevertheless, motivational issues are only mentioned in passing by DÊsilets and van der Meer, Kageura et al., and McDonough Dolmaya. More relevant is O’Brien and Schäler (2010) who offer a study of motivation in translation crowdsourcing albeit in the context of crowdsourcing by non-profit organization working for humanitarian causes which may introduce additional variables in terms of motivation.

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adopted by Facebook, the incorporated collaborative translation platform, and the role of users in the processes of Facebook translation. To elucidate what may drive volunteers to contribute free translations, literature on human motivation and, more specifically, the study on motivation to cooperate in online environments will be reviewed. This analysis will be further complemented with the exploration of the design of a translation platform implemented in translation crowdsourcing and a new framework for the study of motivation in scenarios where translation is crowdsourced will be suggested.

Crowdsourcing: The Origins

According to Jeff Howe (2006, 2008), crowdsourcing as a new model of work organization emerged as an alternative to existing outsourcing practices. In the case of the latter, a third-party, purposefully pre-selected to comply with the requirements of a particular task, is employed to perform the assignment specified by the contractor in exchange for payment agreed upon in advance. By contrast, in the crowdsourcing model the contributor is a crowd of self-selected individuals whose education and professional experiences are typically of no importance and thus often remain unknown. The key element is the eagerness of the crowd members to become involved and to exercise the skills they possess. In most cases financial rewards are not offered to those who participate. The contributors are typically driven by their interest in a particular project and a desire to make an attempt at the practices traditionally done only by professionals such as photography or the solving of scientific problems in the cited by Howe (2006) examples of iStockphoto and InnoCentive.

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Crowdsourcing and Web 2.0

Crowdsourcing, a primarily Internet-based phenomenon, relies on recent advances in technology, which have broadened the scope of user cooperation and information exchange in the online environment (Howe 2008). The second generation of the World Wide Web, branded by O’Reilly and Battelle as Web 2.0 (O’Reilly and Battelle 2009), promotes networking and allows people to build, share and work together. Web 2.0 is being developed by the Internet users themselves, who actively participate in the generation of the Web content through collaboration, data contribution and sharing of resources (Shuen 2008). Users of the Internet are no longer perceived solely as passive media consumers. They have become active co-creators and participants in the generation of the online content. They participate turning the Internet into a platform which serves as a display of human talents and creative potential. What further characterizes the online environment of Web 2.0 is the blurring of the boundary between professionals and nonprofessionals, as members of the general public can easily access specialist knowledge, technologies and software once available to support specific job-related practices. What we experience today is the emergence of a new generation of amateurs, or, as described by Leadbeatter and Miller (2004), Pro-Amateurs: networked, educated and working to professional standards.

Translation Crowdsourcing

Of those translation scholars who are investigating crowdsourcing and its application to translation, many consider this phenomenon to be the consequence of the impact that Web 2.0

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technologies have exerted on the whole translation industry. Cronin (2010), Désilets (2007, 2011) and O’Hagan (2009a, b) emphasize that the online environment that strengthens interaction and user collaboration, opens up a whole new opportunity for the generation of translation.

Perrino (2009) uses the concept of user-generated translation (UGT) to refer to the production of translated versions of the digital media created or edited by users of the Internet and distributed online. He points out that UGT practices avail of Web 2.0 technologies and imply collaboration between translators, be they amateurs or experts. According to Hartley (2009), the growing demand for translation by and for the users of the Internet further strengthens the collaborative aspect of translation. Consequently, he identifies collaborative translation as a practice adopted by groups of self-organizing enthusiasts who try to meet the needs of communities requiring availability of online content in different languages. As an example of collaborative translation, he cites the sphere of open-source software development and translation of user generated applications.

For many years now, media users have been involved in translation-related practices such as the generation of subtitles produced for Japanese anime (O’Hagan 2009a, b, Trykowska 2009), online subtitling of films and other audiovisual content (Bogucki 2009, Díaz Cintas and Muños Sánchez 2006) and even ROM-hacking of video games with the aim of replacing the professionally translated script with a fan-generated one (O’Hagan 2009a). O’Hagan (2009a) indicates that the volunteer fan translators who show interest in such practices are usually inclined to make the media content accessible to any interested audiences. In this way their

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translation act is also often a manifestation of their disapproval of official translations which they perceive to be over-edited in the process of adaptation for markets other than the country of origin.

However, as emphasized by O’Hagan (2009b), the translations produced by fans or gamers are usually intended for other enthusiasts of the same media content. Moreover, fan activities which avail of copyrighted materials without permission are not considered legitimate. On the contrary, the translations received by implementing crowdsourcing are “solicited” (O’Hagan 2009b), i.e. requested from the crowds in the form of an open call and then published as official. Consequently, translation crowdsourcing is a form of collaborative, user-generated translation that is not a breach of law. What further differentiates this practice from other forms of UGT is the fact that in most cases crowdsourcing is applied as a business model with translations being requested from the online crowd usually for free, albeit serving commercially-oriented purposes.

As the Web has provided a platform for user collaboration in translation-related activities, the incorporation of advances in technology in the translation industry is considered to have had the most noticeable impact on the growth of the number of online translation initiatives carried out by the users of the Internet (Cronin 2010, Désilets 2011, O’Hagan forthcoming). The most significant of these initiatives from the perspective of crowdsourcing have been the extensions to translation technologies, now commonly referred to as Computer-Aided Translation (CAT) tools, which have led to their appearance on the Internet where they support a variety of collaborative translation-related activities (Désilets 2011). Many of them are available for free, such as the platform for sharing translation memories developed by the Translation Automation User

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Society (TAUS), open-source translation management systems (e.g. GlobalSight2), open-source translation tools (e.g. OmegaT3), or platforms combining translation memory tools with MT engines (e.g. Google Translator Toolkit4).

The act of “soliciting” translation through crowdsourcing is currently being widely applied by a growing number of for-profit corporations, product developers and service providers including Microsoft, Plaxo, Sun (DePalma and Kelly 2011), Adobe (Petras 2011), HootSuite, Twitter and Facebook (McDonough Dolmaya 2011). The practices implemented by Facebook – a global brand and developer of a social networking service with the same name – exemplify the use of crowdsourcing in commercially-oriented contexts (McDonough Dolmaya 2011) aimed at obtaining free translations in a vast range of languages in a timely manner. The following section describes the structure of translation processes and technological solutions implemented to facilitate translation crowdsourcing on Facebook.

Translation Crowdsourcing by Facebook5

Facebook has been one of the very first to successfully introduce crowdsourcing methods for the translation of its online service. Employing the innovative concepts and services of Web 2.0, the company designed a purpose-built platform that has enabled efficient collaborative translation of

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http://www.globalsight.com/ http://www.omegat.org/ 4 http://translate.google.com/toolkit/TOS.html 5 The following description is based on the material indicated in the text as well as on the author’s observation of the community of Polish Facebook users participating in the Facebook translation crowdsourcing initiative and also the author’s own experimentation with the Facebook Translations application. 3

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Facebook into numerous languages. The initiative started in 2008 with a community of 1500 Spanish-speaking Facebook users who, after only four weeks of translation work, produced a Spanish-language version of Facebook which was immediately made available to the global audience (Facebook Press Room 2008). Following this success, Facebook requested users of their service representing different language communities to get involved in the Facebook translation process so as to produce as many language versions of the service as possible.

As defined by Facebook in its patent application submitted to the United States Patent and Trademark Office (Wong et al. 2009), the translation module that has been developed by the company enables the users of a social networking website to translate text content including commands, menus, toolbars, instructional text, button labels and text describing other objects that are part of the infrastructure of Facebook or additional applications that can be installed there. Facebook embedded their translation module within a separate Translations application that needs to be incorporated by individual users into their own Facebook profiles to grant them access to the collaborative translation platform, which supports the translation crowdsourcing model. Phrases or sentences extracted for translation are displayed here in the form of short segments listed randomly (see Figure 1) as usually one segment will not be in any way related to the previous or following ones. The translation is inserted into the space provided and submitted by clicking on the ‘Translate’ button (circled).

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Figure 1 A list of segments for translation displayed from within the Translations application on Facebook

Also available is the ‘inline’ mode of translation, which allows users to translate segments while engaging with Facebook for normal day-to-day activities. In this mode, the untranslated UI elements are underlined in red and, when selected, a pop-up window is displayed where the translation can be provided.

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Apart from translating the elements of Facebook’s infrastructure, the volunteer translators can also vote on quality of translations provided by others. The voting (see Figure 2) is based on a two-score system, i.e. a given translation may be either voted-up or voted-down depending on how the voter perceives its quality (circled). The system additionally assigns values to individual votes depending on the reputation of the person submitting them so that they represent “an estimate of the ability of the voter to translate content (...) or evaluate translated content� (Wong et al. 2009). On the basis of the received votes, the translation with the highest score is selected and then displayed in the final target language version of Facebook. All translations provided by the community are subject to review by the internal professional translators (DePalma and Kelly 2011).

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Figure 2 A list of segments presented for voting displayed from within the Translations application on Facebook.

Facebook also provides a number of additional functions to support volunteers in their translation efforts. These include a discussion board where all translation-related issues may be examined collaboratively, a glossary which supports consistency while working with phrases containing words recognized as terms (see Figure 1a) and also a set of stylistic guidelines written for each language individually by a member of the volunteer translator community.

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While not offering any financial remuneration in exchange for the translations provided, Facebook acknowledges the volunteer translators by adding ‘awards’ in the form of icons displayed on their individual profile pages or listing their names on a leader board. The latter is a rank of all the contributors, where the position occupied by a given volunteer translator depends on how active they are and how good the quality of their contribution is (on the basis of the voting).

As announced at Facebook’s own f8 developer conference in September 2011, the company aims to improve the experience of using Facebook and its many features in an attempt to meet the needs of current and future users (Lessin 2011, Zuckerberg 2011). On the 1st of November 2011, a new redesigned version of Translations was introduced, though some of the application’s features, such as the glossary or the stylistic guidelines, are not currently available. Nevertheless, a new element that has already been introduced is a ‘Community’ section, which all translators working with a particular language are invited to join. The community members may then exchange ideas, discuss problematic translations and offer support on Facebook in real time, which further reinforces the collaborative aspect of the whole translation process embraced by Facebook.

Motivation in Translation Crowdsourcing

With sixty-four language versions of Facebook already released and millions of users working on the translation of Facebook into the recently added languages, translation of new Facebook features as well as improving the existing translations, the incorporation of the crowdsourcing

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model for translation purposes by Facebook is one of the most successful and most widely discussed examples of translation by crowdsourcing (Kageura et al. 2011, Kelly, Ray and DePalma 2011). The company has developed their own technological solution that supports translation collaboration, and, by adapting the crowdsourcing model to the specific environment of social network, has involved in the translation processes the Facebook community of millions of international Facebook users. Nevertheless, a community and a tool do not guarantee an instant success to any translation crowdsourcing project. Discussing different collaborative translation initiatives, DĂŠsilets (2011) indicates some of the challenges they may present, for example, the need to select a collaborative translation scenario appropriate to a particular business goal, or to control quality in the highly decentralized environment. But when referring specifically to translation crowdsourcing practices, DĂŠsilets as the most critical issue highlights motivation of the members of the crowd to persist in their efforts to participate and contribute.

The next sections discuss prior research on human motivation and relate them to factors motivating the users of the Internet to participate in translation crowdsourcing. It is relevant to note that the literature search on motivation uncovered almost no research that is applicable to the current discussion on professional and volunteer translator motivation in the field of Translation Studies. Consequently, this led to an approach located within a broader framework of Self-Determination Theory (SDT) (Deci and Ryan 2008, Ryan and Deci 2000), which is further complemented with factors motivating cooperation in the online environment put forward by Kollock (1999) and also a consideration of a collaborative translation platform design as a yet another element affecting the motivation of participants in translation crowdsourcing.

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Human Motivation

The examination of factors that lead people to perform certain activities as well as the explanation of what influences behaviour and its intensity are the fundamental problems in research on motivation. Reeve (2009: 10) stresses that motivation itself is a “private, unobservable, and seemingly mysterious experience�. Nevertheless, through analyzing the behavioral manifestations of motivation (such as effort, persistence, personal investment, physiology and self-report) it is possible to deduce and ascribe to a particular person his or her internal motives - needs, cognitions and emotions that energize and direct behaviour. As Reeve notes, apart from the internal processes, further sources of motivation also come from the environment in the form of external events (incentives, stimuli) and also broader social and cultural contexts (ibid.). Consequently, motivational analysis of human behavior should combine the study of internal drivers with the study of drivers coming from the environment in which a given individual resides.

An understanding of human motivation as being driven by what is internal (intrinsic sources of motivation) and by what comes from the environment (extrinsic sources of motivation) has been reflected in SDT postulated by Ryan and Deci (2000). In SDT competence, autonomy and relatedness are specified as the innate human growth tendencies that are essential for human selfmotivation. According to SDT, intrinsic motivation arises when engaging in an activity allows one to feel free (autonomous), effective (competent) and emotionally close (related to others). These internal developmental tendencies, however, may be undermined by external factors such

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as regulation and control. Consequently, Deci and Ryan (2008) draw a distinction between intrinsic motivation, emerging from the natural human inclination to learn and develop, and extrinsic motivation, arising under the influence of external incentives. In the case of intrinsic motivation, an activity will be performed because it brings satisfaction, while extrinsic motivation indicates that an activity is engaged in for the purpose of attaining an independent outcome. This does not mean, however, that extrinsically motivated behaviour is completely non-autonomous. Deci and Ryan (2008) indicate that behaviour varies depending on the level of its relative autonomy and thus different types of extrinsic motivation can be specified. They further stress that motivation yields more effective performance and results in greater persistence in the cases where the external regulation is more internalized and consequently the levels of autonomy are perceived to be higher.

From the perspective of translation crowdsourcing initiative on Facebook, SDT appears to be a very relevant theory of motivation. In accordance with SDT, the voluntarily participation of Facebook users may be interpreted as an intrinsically motivated pursuit of the needs for competence, autonomy and relatedness. Furthermore, the volunteer Facebook translators do not work in a vacuum - they are influenced by the online environment in which the translation takes place as well as the social context of cooperation and the structure of the translation process as dictated by the Facebook’s technology for collaborative translation. These factors, which may be perceived as sources of external regulation and control, further need to be analyzed to apprehend the nature of the motivation of the users translating Facebook without financial compensation.

Motivation and the Online Environment

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The phenomenon of translation crowdsourcing as exemplified by Facebook is an example of translation collaboratively produced on a social network in the virtual environment of the Internet. Discussing the particular conditions of collaborative work online, Kollock (1999) outlines four motivations for providing public good by means of cooperation on the Internet.

The first motivation is rooted in the belief in mutual exchange and reciprocity, where a contribution is made with an expectation to receive information or help from others in return. Kollock stresses that this type of motivation will be strengthened where the interactions between the community members are maintained at high levels, and where the members of the community can easily identify the other contributors and keep track of the contributions made by others over time.

The second factor that has an effect on the motivation of contributors is reputation. In online communities, members are aware that individual contributions are witnessed by many others in the community. To increase the prestige in the community, one is driven to provide contributions higher in volume and better in quality. Lampel and Bhalla (2008) further point out that the online environment is often perceived as a desirable place for constructing one’s identity, an identity that is closer to the ‘ideal self’. They add that each online contribution functions as a message about the self that is sent to others on the Internet. The wish to build a positive image of oneself thus initiates participation and encourages contribution.

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The third source of motivation indicated by Kollock is the level of self-efficacy possessed by a contributor. Self-efficacy, as defined by Bandura (1997), is a belief about one’s own ability to perform on a designated level in order to exercise influence upon future events affecting one’s life. Kollock continues that having the opportunity to contribute to the group makes a person believe that his or her actions have a greater impact on a significantly larger number of people. This boosts self-image and leads to the perception of the self as being efficacious, strengthening the motivation to get involved.

The fourth motivator discussed by Kollock manifests itself when an individual is strongly attached to the group to which he or she contributes. The consequence that follows is their identification with the needs of the group. These needs are then satisfied by contributing, which helps to achieve the key objectives of the collective.

The analysis of general studies on motivation in crowdsourcing applied to a wide range of tasks other than translation (Lakhani et al. 2007, Brabham 2008, 2010) nevertheless indicates a number of likely reasons for volunteering in crowdsourcing initiatives. Among them are the ability to further develop the skills that one already possesses, the opportunity to make friends with other contributors and to develop a network of people sharing similar interests and the chance to do what one does best and that is thus fun and enjoyable. It can be expected that the motivations of volunteer Facebook translators will likely correspond at least with some of these. Nevertheless, in the case of the translation processes that take place on Facebook, an additional motivating factor may be the purpose-built collaborative translation platform. The following section addresses this aspect.

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Collaborative Translation Platform Design and Motivation

As described earlier, the collaborative translation platform developed by Facebook constitutes the central part of the whole translation model employed by Facebook. It serves as a tool through which the translations are obtained from the volunteering crowd and functions as a quality control mechanism supporting the translation voting system. However, in the light of studies on motivation in crowdsourcing, motivation for online cooperation as well as more general analysis of human motivation, there emerges yet another role of the translation platform incorporated in translation crowdsourcing. As the core element of the environment in which the volunteer translators work and provide their translations, the platform not only supports the translation process itself but may also influence the motivation of those who decide to participate in translation initiative. The technologies which are applied to facilitate crowdsourcing – not exclusively in translation – must function in a way that lets their users achieve all the outcomes they expect to achieve by joining the crowd and getting involved in a particular crowdsourcing initiative. Consequently, when these expectations are met, they continue with their efforts and keep contributing. In the particular case of translation crowdsourcing, the functionality and usability of the implemented platform plays a role in defining the actions that are taken by its users and subsequently has an impact on all the translation-oriented activities that they are able to undertake. As indicated by research in the field of Human-Computer Interaction, a computer system or an application may and should be designed in a way that encourages people to use the system or application on an ongoing basis (Porter 2008). However, to achieve this, the design must recognize, support and encourage people’s motivation to use the system in the first place.

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Discussions and Further Work

As presented in the paper, the study of motivation to contribute to translation crowdsourcing, where financial remuneration is often non-existent, opens up a number of other possible factors that drive human behaviour, ranging from mobilizing initial involvement to maintaining volunteers’ efforts to offer their time and skills to produce translations. As applied in this paper, Self-Determination Theory indicates in particular that as much as human behavior depends on an individual’s self-motivation, it is also subject to regulation and control from outside. Thus, the structure of crowdsourcing processes, the features of the environment in which they are applied and also the tools through which these processes are exercised, are likely to have a direct impact upon crowd motivation and further performance in translation.

The architecture of the translation crowdsourcing model which Facebook has designed for the purposes of obtaining translations from their own community of users displays a number of characteristic features specifically catering for the participating volunteer translators. Furthermore, the volunteering translators are given the space where they can discuss their work among themselves while the technological solution in the form of a collaborative translation platform supports different aspects of the actual translation process of which they want to be part.

As indicated earlier by Reeve (2009), human motivation is to a large extent a private experience and thus an attempt to infer the factors driving human behaviour in any particular case should not be based only on a close analysis of observed actions but should further allow for self-reporting

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and expression of feelings assisting an individual in a given situation. This has been exemplified by a number studies focusing on participants in crowdsourcing initiatives such as the work on motivation for participating in the crowdsourcing of photography at iStockphoto (Brabham 2008) or t-shirt designs at Threadless (Brabham 2010), motivation for participating in solving a highly scientific and technical challenge for InnoCentive (Lakhani et al. 2007) and the online survey of crowd translators mentioned at the beginning (O’Brien and Schäler 2010). Still, there is a paucity of work in Translation Studies which addresses the role of technologies in the motivation of professional translators, let alone volunteers. Thus, the current paper is merely a first step towards uncovering what motivates the user-translators of Facebook to contribute to the its translation. The next step will involve gaining access to a group of volunteer Facebook translators to collect data, which will enable a detailed analysis of behaviours and attitudes in translation crowdsourcing. It is hoped that such data, in combination with a longitudinal study of the same community actively cooperating on translation tasks in the dedicated space provided by Facebook, will offer more concrete empirical evidence that may help shed light on motivation for participation in initiatives where crowdsourcing is applied as a means of procuring translations online.

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Profile for Jennifer Bruen

Translation Crowdsourcing: The Facebook Way – in Search of Crowd Motivation by Magdalena Dombek  

The paper addresses the relatively recent phenomenon of translation crowdsourcing, which makes an open call to unspecified users of the Inte...

Translation Crowdsourcing: The Facebook Way – in Search of Crowd Motivation by Magdalena Dombek  

The paper addresses the relatively recent phenomenon of translation crowdsourcing, which makes an open call to unspecified users of the Inte...

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