Investigating virtual production networks in Sub-Saharan Africa and Southeast Asia

by Mark Graham 03/11/2014

This mass connectivity has been one crucial ingredient for some significant changes in how work is organised, divided, outsourced, and rewarded.

by Mark Graham 03/11/2014

Ed: You are looking at the structures of ‘virtual production networks’ to understand the economic and social implications of online work. How are you doing this? Mark: We are studying online freelancing. In other words this is digital or digitised work for which professional certification or formal training is usually not required. The work is monetised or monetisable, and can be mediated through an online marketplace. Freelancing is a very old format of work. What is new is the fact that we have almost three billion people connected to a global network: many of those people are potential workers in virtual production networks. This mass connectivity has been one crucial ingredient for some significant changes in how work is organised, divided, outsourced, and rewarded. What we plan to do in this project is better map the contours of some of those changes and understand who wins and who doesn’t in this new world of work. Ed: Are you able to define what comprises an individual contribution to a ‘virtual production network’—or to find data on it? How do you define and measure value within these global flows and exchanges? Mark: It is very far from easy. Much of what we are studying is immaterial and digitally-mediated work. We can find workers and we can find clients, but the links between them are often opaque and black-boxed. Some of the workers that we have spoken to operate under non-disclosure agreements, and many actually haven’t been told what their work is being used for. But that is precisely why we felt the need to embark on this project. With a combination of quantitative transaction data from key platforms and qualitative interviews in which we attempt to piece together parts of the network, we want to understand who is (and isn’t) able to capture and create value within these networks. Ed: You note that “within virtual production networks, are we seeing a shift…

Development, Mapping

What explains the worldwide patterns in user-generated geographical content?

by Mark Graham 08/09/2014

As geographic content and geospatial information becomes increasingly integral to our everyday lives, places that are left off the ‘map of knowledge’ will be absent from our understanding of the world.

by Mark Graham 08/09/2014

The geographies of codified knowledge have always been uneven, affording some people and places greater voice and visibility than others. While the rise of the geosocial Web seemed to promise a greater diversity of voices, opinions, and narratives about places, many regions remain largely absent from the websites and services that represent them to the rest of the world. These highly uneven geographies of codified information matter because they shape what is known and what can be known. As geographic content and geospatial information becomes increasingly integral to our everyday lives, places that are left off the ‘map of knowledge’ will be absent from our understanding of, and interaction with, the world. We know that Wikipedia is important to the construction of geographical imaginations of place, and that it has immense power to augment our spatial understandings and interactions (Graham et al. 2013). In other words, the presences and absences in Wikipedia matter. If a person’s primary free source of information about the world is the Persian or Arabic or Hebrew Wikipedia, then the world will look fundamentally different from the world presented through the lens of the English Wikipedia. The capacity to represent oneself to outsiders is especially important in those parts of the world that are characterised by highly uneven power relationships: Brunn and Wilson (2013) and Graham and Zook (2013) have already demonstrated the power of geospatial content to reinforce power in a South African township and Jerusalem, respectively. Until now, there has been no large-scale empirical analysis of the factors that explain information geographies at the global scale; this is something we have aimed to address in this research project on Mapping and measuring local knowledge production and representation in the Middle East and North Africa. Using regression models of geolocated Wikipedia data we have identified what are likely to be the necessary conditions for representation at the country level, and have also identified the outliers,…

Development, Mapping

What is stopping greater representation of the MENA region?

by Mark Graham 06/08/2014

Negotiating the wider politics of Wikipedia can be a daunting task, particularly when in it comes to content about the MENA region.

by Mark Graham 06/08/2014

Wikipedia has famously been described as a project that “ works great in practice and terrible in theory”. One of the ways in which it succeeds is through its extensive consensus-based governance structure. While this has led to spectacular success—over 4.5 million articles in the English Wikipedia alone—the governance structure is neither obvious nor immediately accessible, and can present a barrier for those seeking entry. Editing Wikipedia can be a tough challenge—an often draining and frustrating task, involving heated disputes and arguments where it is often the most tenacious, belligerent, or connected editor who wins out in the end. Broadband access and literacy are not the only pre-conditions for editing Wikipedia; ‘digital literacy’ is also crucial. This includes the ability to obtain and critically evaluate online sources, locate Wikipedia’s editorial and governance policies, master Wiki syntax, and confidently articulate and assert one’s views about an article or topic. Experienced editors know how to negotiate the rules, build a consensus with some editors to block others, and how to influence administrators during dispute resolution. This strict adherence to the word (if not the spirit) of Wikipedia’s ‘law’ can lead to marginalization or exclusion of particular content, particularly when editors are scared off by unruly mobs who ‘weaponise’ policies to fit a specific agenda. Governing such a vast collaborative platform as Wikipedia obviously presents a difficult balancing act between being open enough to attract volume of contributions, and moderated enough to ensure their quality. Many editors consider Wikipedia’s governance structure (which varies significantly between the different language versions) essential to ensuring the quality of its content, even if it means that certain editors can (for example) arbitrarily ban other users, lock down certain articles, and exclude moderate points of view. One of the editors we spoke to noted that: “A number of articles I have edited with quality sources, have been subjected to editors cutting information that doesn’t fit their ideas […]…

Development, Mapping

How well represented is the MENA region in Wikipedia?

by Mark Graham 22/07/2014

There are more Wikipedia articles in English than Arabic about almost every Arabic speaking country in the Middle East.

by Mark Graham 22/07/2014

Image of rock paintings in the Tadrart Acacus region of Libya by Luca Galuzzi.

Wikipedia is often seen to be both an enabler and an equaliser. Every day hundreds of thousands of people collaborate on an (encyclopaedic) range of topics; writing, editing and discussing articles, and uploading images and video content. This structural openness combined with Wikipedia’s tremendous visibility has led some commentators to highlight it as “a technology to equalise the opportunity that people have to access and participate in the construction of knowledge and culture, regardless of their geographic placing” (Lessig 2003). However, despite Wikipedia’s openness, there are also fears that the platform is simply reproducing worldviews and knowledge created in the Global North at the expense of Southern viewpoints (Graham 2011; Ford 2011). Indeed, there are indications that global coverage in the encyclopaedia is far from ‘equal’, with some parts of the world heavily represented on the platform, and others largely left out (Hecht and Gergle 2009; Graham 2011, 2013, 2014). These second-generation digital divides are not merely divides of Internet access (so discussed in the late 1990s), but gaps in representation and participation (Hargittai and Walejko 2008). Whereas most Wikipedia articles written about most European and East Asian countries are written in their dominant languages, for much of the Global South we see a dominance of articles written in English. These geographic differences in the coverage of different language versions of Wikipedia matter, because fundamentally different narratives can be (and are) created about places and topics in different languages (Graham and Zook 2013; Graham 2014). If we undertake a ‘global analysis’ of this pattern by examining the number of geocoded articles (ie about a specific place) across Wikipedia’s main language versions (Figure 1), the first thing we can observe is the incredible human effort that has gone into describing ‘place’ in Wikipedia. The second is the clear and highly uneven geography of information, with Europe and North America home to 84% of all geolocated articles. Almost all of Africa is…

Development, Mapping

The sum of (some) human knowledge: Wikipedia and representation in the Arab World

by Mark Graham 14/07/2014

Arabic is one of the least represented major world languages on Wikipedia: few languages have more speakers and fewer articles than Arabic.

by Mark Graham 14/07/2014

Image of the Umayyad Mosque (Damascus) by Travel Aficionado

Wikipedia currently contains over 9 million articles in 272 languages, far surpassing any other publicly available information repository. Being the first point of contact for most general topics (therefore an effective site for framing any subsequent representations) it is an important platform from which we can learn whether the Internet facilitates increased open participation across cultures—or reinforces existing global hierarchies and power dynamics. Because the underlying political, geographic and social structures of Wikipedia are hidden from users, and because there have not been any large scale studies of the geography of these structures and their relationship to online participation, entire groups of people (and regions) may be marginalised without their knowledge. This process is important to understand, for the simple reason that Wikipedia content has begun to form a central part of services offered elsewhere on the Internet. When you look for information about a place on Facebook, the description of that place (including its geographic coordinates) comes from Wikipedia. If you want to “check in” to a museum in Doha to signify you were there to their friends, the place you check in to was created with Wikipedia data. When you Google “House of Saud” you are presented not only with a list of links (with Wikipedia at the top) but also with a special ‘card’ summarising the House. This data comes from Wikipedia. When you look for people or places, Google now has these terms inside its ‘knowledge graph’, a network of related concepts with data coming directly from Wikipedia. Similarly, on Google maps, Wikipedia descriptions for landmarks are presented as part of the default information. Ironically, Wikipedia editorship is actually on a slow and steady decline, even as its content and readership increases year on year. Since 2007 and the introduction of significant devolution of administrative powers to volunteers, Wikipedia has not been able to effectively retain newcomers, something which has been noted as a concern by…

Social Data Science

Past and Emerging Themes in Policy and Internet Studies

by Vili Lehdonvirta 12/05/2014

It is simply not possible to consider public policy today without some regard for the intertwining of information technologies with everyday life and society.

by Vili Lehdonvirta 12/05/2014

We can't understand, analyse or make public policy without understanding the technological, social and economic shifts associated with the Internet. Image from the (post-PRISM) "Stop Watching Us" Berlin Demonstration (2013) by mw238.

In the journal’s inaugural issue, founding Editor-in-Chief Helen Margetts outlined what are essentially two central premises behind Policy & Internet’s launch. The first is that “we cannot understand, analyse or make public policy without understanding the technological, social and economic shifts associated with the Internet” (Margetts 2009, 1). It is simply not possible to consider public policy today without some regard for the intertwining of information technologies with everyday life and society. The second premise is that the rise of the Internet is associated with shifts in how policy itself is made. In particular, she proposed that impacts of Internet adoption would be felt in the tools through which policies are effected, and the values that policy processes embody. The purpose of the Policy and Internet journal was to take up these two challenges: the public policy implications of Internet-related social change, and Internet-related changes in policy processes themselves. In recognition of the inherently multi-disciplinary nature of policy research, the journal is designed to act as a meeting place for all kinds of disciplinary and methodological approaches. Helen predicted that methodological approaches based on large-scale transactional data, network analysis, and experimentation would turn out to be particularly important for policy and Internet studies. Driving the advancement of these methods was therefore the journal’s third purpose. Today, the journal has reached a significant milestone: over one hundred high-quality peer-reviewed articles published. This seems an opportune moment to take stock of what kind of research we have published in practice, and see how it stacks up against the original vision. At the most general level, the journal’s articles fall into three broad categories: the Internet and public policy (48 articles), the Internet and policy processes (51 articles), and discussion of novel methodologies (10 articles). The first of these categories, “the Internet and public policy,” can be further broken down into a number of subcategories. One of the most prominent of these streams…

Interviews, Tools

The social economies of networked cultural production (or, how to make a movie with complete strangers)

by Isis Hjorth 28/04/2014

Looking at “networked cultural production”—ie the creation of cultural goods like films through crowdsourcing platforms—specifically in the ‘wreckamovie’ community

by Isis Hjorth 28/04/2014

Nomad, the perky-looking Mars rover from the crowdsourced documentary Solar System 3D (Wreckamovie).

Ed: You have been looking at “networked cultural production”—ie the creation of cultural goods like films through crowdsourcing platforms—specifically in the ‘wreckamovie’ community. What is wreckamovie? Isis: Wreckamovie is an open online platform that is designed to facilitate collaborate film production. The main advantage of the platform is that it encourages a granular and modular approach to cultural production; this means that the whole process is broken down into small, specific tasks. In doing so, it allows a diverse range of geographically dispersed, self-selected members to contribute in accordance with their expertise, interests and skills. The platform was launched by a group of young Finnish filmmakers in 2008, having successfully produced films with the aid of an online forum since the late 1990s. Officially, there are more than 11,000 Wreckamovie members, but the active core, the community, consists of fewer than 300 individuals. Ed: You mentioned a tendency in the literature to regard production systems as being either ‘market driven’ (eg Hollywood) or ‘not market driven’ (eg open or crowdsourced things); is that a distinction you recognised in your research? Isis: There’s been a lot of talk about the disruptive and transformative powers nested in networked technologies, and most often Wikipedia or open source software are highlighted as examples of new production models, denoting a discontinuity from established practices of the cultural industries. Typically, the production models are discriminated based on their relation to the market: are they market-driven or fuelled by virtues such as sharing and collaboration? This way of explaining differences in cultural production isn’t just present in contemporary literature dealing with networked phenomena, though. For example, the sociologist Bourdieu equally theorised cultural production by drawing this distinction between market and non-market production, portraying the irreconcilable differences in their underlying value systems, as proposed in his The Rules of Art. However, one of the key findings of my research is that the shaping force of these productions is…

Mapping, Methods, Social Data Science

Edit wars! Measuring and mapping society’s most controversial topics

by taha yasseri 03/12/2013

Although some topics are globally debated, like religion and politics, there are many topics which are controversial only in a single language edition. This reflects the local preferences and importances assigned to topics by different editorial communities.

by taha yasseri 03/12/2013

Ed: How did you construct your quantitative measure of ‘conflict’? Did you go beyond just looking at content flagged by editors as controversial? Taha: Yes we did. Actually, we have shown that controversy measures based on “controversial” flags are not inclusive at all and although they might have high precision, they have very low recall. Instead, we constructed an automated algorithm to locate and quantify the editorial wars taking place on the Wikipedia platform. Our algorithm is based on reversions, i.e. when editors undo each other’s contributions. We focused specifically on mutual reverts between pairs of editors and we assigned a maturity score to each editor, based on the total volume of their previous contributions. While counting the mutual reverts, we used more weight for those ones committed by/on editors with higher maturity scores; as a revert between two experienced editors indicates a more serious problem. We always validated our method and compared it with other methods, using human judgement on a random selection of articles. Ed: Was there any discrepancy between the content deemed controversial by your own quantitative measure, and what the editors themselves had flagged? Taha: We were able to capture all the flagged content, but not all the articles found to be controversial by our method are flagged. And when you check the editorial history of those articles, you soon realise that they are indeed controversial but for some reason have not been flagged. It’s worth mentioning that the flagging process is not very well implemented in smaller language editions of Wikipedia. Even if the controversy is detected and flagged in English Wikipedia, it might not be in the smaller language editions. Our model is of course independent of the size and editorial conventions of different language editions. Ed: Were there any differences in the way conflicts arose/were resolved in the different language versions? Taha: We found the main differences to be the topics of controversial…

Methods, Social Data Science

The physics of social science: using big data for real-time predictive modelling

by taha yasseri 21/11/2013

There are very interesting examples of using big data to make predictions about disease outbreaks, financial moves in the markets, social interactions based on human mobility patterns, election results, etc.

by taha yasseri 21/11/2013

Ed: You are interested in analysis of big data to understand human dynamics; how much work is being done in terms of real-time predictive modelling using these data? Taha: The socially generated transactional data that we call “big data” have been available only very recently; the amount of data we now produce about human activities in a year is comparable to the amount that used to be produced in decades (or centuries). And this is all due to recent advancements in ICTs. Despite the short period of availability of big data, the use of them in different sectors including academia and business has been significant. However, in many cases, the use of big data is limited to monitoring and post hoc analysis of different patterns. Predictive models have been rarely used in combination with big data. Nevertheless, there are very interesting examples of using big data to make predictions about disease outbreaks, financial moves in the markets, social interactions based on human mobility patterns, election results, etc. Ed: What were the advantages of using Wikipedia as a data source for your study—as opposed to Twitter, blogs, Facebook or traditional media, etc.? Taha: Our results have shown that the predictive power of Wikipedia page view and edit data outperforms similar box office-prediction models based on Twitter data. This can partially be explained by considering the different nature of Wikipedia compared to social media sites. Wikipedia is now the number one source of online information, and Wikipedia article page view statistics show how much Internet users have been interested in knowing about a specific movie. And the edit counts—even more importantly—indicate the level of interest of the editors in sharing their knowledge about the movies with others. Both indicators are much stronger than what you could measure on Twitter, which is mainly the reaction of the users after watching or reading about the movie. The cost of participation in Wikipedia’s editorial process…

Social Data Science

Verification of crowd-sourced information: is this ‘crowd wisdom’ or machine wisdom?

by Heather Ford 19/11/2013

The problem with computer code is that it is invisible, and that it makes it easy to regulate people’s behaviour directly and often without recourse.

by Heather Ford 19/11/2013

‘Code’ or ‘law’? Image from an Ushahidi development meetup by afropicmusing.

In ‘Code and Other Laws of Cyberspace’, Lawrence Lessig (2006) writes that computer code (or what he calls ‘West Coast code’) can have the same regulatory effect as the laws and legal code developed in Washington D.C., so-called ‘East Coast code’. Computer code impacts on a person’s behaviour by virtue of its essentially restrictive architecture: on some websites you must enter a password before you gain access, in other places you can enter unidentified. The problem with computer code, Lessig argues, is that it is invisible, and that it makes it easy to regulate people’s behaviour directly and often without recourse. For example, fair use provisions in US copyright law enable certain uses of copyrighted works, such as copying for research or teaching purposes. However the architecture of many online publishing systems heavily regulates what one can do with an e-book: how many times it can be transferred to another device, how many times it can be printed, whether it can be moved to a different format—activities that have been unregulated until now, or that are enabled by the law but effectively ‘closed off’ by code. In this case code works to reshape behaviour, upsetting the balance between the rights of copyright holders and the rights of the public to access works to support values like education and innovation. Working as an ethnographic researcher for Ushahidi, the non-profit technology company that makes tools for people to crowdsource crisis information, has made me acutely aware of the many ways in which ‘code’ can become ‘law’. During my time at Ushahidi, I studied the practices that people were using to verify reports by people affected by a variety of events—from earthquakes to elections, from floods to bomb blasts. I then compared these processes with those followed by Wikipedians when editing articles about breaking news events. In order to understand how to best design architecture to enable particular behaviour, it becomes important to…

crowd sourcing