This is a follow-up to last month’s post describing preliminary results from a survey of Wikipedia translators. To find out about the survey methodology and the respondent profiles, please read this post first.
I initially planned for this survey to be one of several with translators from various crowdsourced projects, so I wrote the participation-related questions hoping to compare the types of crowdsourced translation initiatives people decide to participate in and what roles they play in each one. I haven’t yet had time to survey participants in other initiatives (and, truth be told, I probably won’t have time to do so in the near future), so the responses to the next few questions will have to be only a partial glimpse of the kinds of initiatives crowdsourcing participants get involved in. Here’s a table illustrating the responses to the question about which crowdsourced translation initiatives respondents had participated in. As expected, virtually all respondents had helped translate for Wikipedia. The one respondent who did not report translating for Wikipedia participated in Translatewiki.net, with a focus on MediaWiki, the wiki platform originally designed for Wikipedia.
|Initiative||No. of respondents||Percentage|
|Free/Open-source software projects (software localization and/or documentation translation for F/OSS projects such as OmegaT, Concrete5, Adium, Flock, Framasoft)||7||9.2%|
|The Kamusi Project||1||1.3%|
|Science-fiction fandom websites||1||1.3%|
|Der Mundo (Wordwide Lexicon)||1||1.3%|
|The Lied, Art Song, and Choral Texts Page||1||1.3%|
A few points I found interesting. First, I was surprised to see that respondents had participated in such a diverse range of projects. I had expected that because Wikipedia was a not-for-profit initiative, participants would be less likely to have helped translate for for-profit companies like Facebook and Twitter; however, after Wikipedia, Facebook was the initiative that had attracted the most participants. Second, I was intrigued by the fact that almost 10% of respondents were involved in open-source software translation/localization projects. I hypothesized that the respondents who had reported working in the IT sector or studying computer science would be the ones involved in the F/OSS projects, but that was not always the case: when I broke down the data, I found that people from a variety of fields (a high school student, an economics student, two medical students, a translator, a software developer, a fundraiser, etc.) had helped translate/localize F/OSS projects. I think these results really indicate a need to specifically study F/OSS translation projects to see whether the Wikipedia respondents are representative of the participants.
Next, I asked respondents how they had participated in crowdsourced translation projects (as translators, revisers, project managers, etc.) and how much time per week, on average, they had spent participating in their last crowdsourced translation initiative.
Here’s a graph illustrating how respondents had participated in various crowdsourced translation projects. They were asked to select all ways they had been involved, even if it varied from one project to another. This means that the responses are not indicative of participation in Wikipedia alone:
As the graph shows, translation was the most common means of participation, but that wasn’t surprising, because I had invited respondents based on whether they had translated for Wikipedia. However, a significant number of respondents had also acted as revisers/editors, and some had participated in other ways, such as providing links to web resources and participating in the forums. I think this graph shows how crowdsourced translation initiatives allow people with various backgrounds and experiences to participate in ways that match their skills: for instance, someone with weaker second-language skills can help edit the target text in his or her mother tongue, catching typos and factual errors. And someone with a background in a particular field can share links to resources or answer questions about concepts from that field, without necessarily having to do any translating. So when we speak of crowdsourced translation initiatives, it’s important to consider that these initiatives allow for more types of involvement than translating in the narrow sense of providing a TL equivalent for a ST.
Finally, I asked participants how many hours they spent on average, per week, participating in the last crowsourced translation initiative in which they were involved. Here’s a graph that illustrates the answers I received:
As you can see, most respondents spent no more than five hours per week participating in a crowdsourced translation initiative. On the surface, this may seem to provide some comfort to the professional translators who object to crowdsourcing as a platform for translation, since these Wikipedia respondents did not spend enough time per week on a translation to equal a full-time job; however, hundreds of people volunteering four or five hours per week can still produce enough work to replace several full-time professionals. Not-for-profit initiatives like Wikipedia, where article authors, illustrators and translators all volunteer their time are probably not as problematic to the profession, since professional translators would probably never have been hired to translate the content anyway, but for-profit initiatives such as Facebook are more ethically ambiguous. I’ve discussed some of these ethical problems in an article that will be published in Linguistica Antverpiensia later this year, in an issue focusing on community translation.
In a few weeks, I’ll post the results of the last few survey questions, the ones focusing on motivations for participating, the rewards/incentives participants have received and the effect(s) their participation has had on their lives and careers.