The following blog post describes the ongoing Wikipedia research by members of the SOCIAM project in the University of Southampton, and contains some of the highlights of the Wikimania 2014 conference, held in London, August 2014. In short, this blog post contains our thinking and current insights of our analysis of Wikipedia as an evolving and dynamic social machine. As part of this we question pre-existing research fields and paradigms in our quest to better understand the complexities of the Wikipedia ecosystem.
One of the core drivers of the SOCIAM project is to understand the emergence and growth of social machines. Scale and granularity are central to how we theoretically frame our analysis, thus understanding social machines involves examining them as individual systems and as interconnected networks of interaction. We also consider that the knowledge learned from understanding how they operate in terms of social and technical level is critical if we are to understand the factors that contribute to their success and failure, and thus help us develop adequate measures and theory to support them. Increasingly we have been examining them as socio-technical heterogeneous networks of people and technology, and in light of this, we’ve been developing new methods, metrics, and analytics that takes this into consideration.
Wikipedia is a fantastic example of an maturing, yet ever-changing social machine, and In recent months, the SOCIAM team have have been investigating it as a means to better understand the characteristics that have enabled it to prosper and continue to evolve. As Professor Sir Nigel Shadbolt described in his keynote at Wikipedia 2014, one of the core areas we have been focusing on is the various activities that emerge from within the social machines, these are often described as “Wikipedia Emergent Phenomenon”, which contain both social and technological re-configurations. One specific example of this is the formation of WikiProjects, which as Wikipedia states: “A WikiProject is a group of contributors who want to work together as a team to improve Wikipedia.” Wikiprojects vary in topic and size, with some containing as little as 2 participants, with larger projects containing communities of over 10,000. Each WikiProject typically has its own project statements and goals, and also associate themselves with the editing or creation of specific Wikipedia articles (which contribute to the main corpus of Wikipedia articles).
From a research(er’s) perspective, what makes WikiProjects so interesting is how these communities emerge and are able to gain mobility and sustained participation over an extended amount of time. This raises numerous questions of community building, incentives, motivations, as well as agency, power and (self) governance. But understanding this kind of emergent phenomenon is not only interesting for researchers, such activities could potentially have a direct impact on the operation and future growth of Wikipedia. Over recent years there has been a growing concern that the number of active and new Wikipedians is in decline, which could have implications for the development of additional articles, and the refinement of existing ones.
Such concerns are of course just, and are based on statistics metrics such as active edits and number of newly created Wikipedia accounts. However, as we have been investigating, perhaps these metrics do not reflect or consider the current phase of Wikipedia. As our studies of other social machines have shown, traditional measures of activity are not adequate or granular enough to interpret the socio-technical changes within these classes of Web systems. Social machines such as Wikipedia have multiple dimensions that need to be understood and analysed in order appreciate its well-being or even its current state of operation.,
In our current analysis of Wikipedia through the lens of WikiProjects (more can be found on the Southampton Web Observatory - http://webobservatory.soton.ac.uk), we have already identified a number of important metrics that need to be taken into account if we are to develop a reasonable level of insight into the operation of these complex systems.Our previous work studying citizen science platforms such as Zooniverse has shown us that observing the primary purpose of a social machine (i.e. classifying galaxy images) may miss a whole area of activity, thus we are developing an observational lens on Wikipedia which explores multiple aspects of activity, including the role of “talk” or discussion.
Our initial findings has already shown the role (and potential importance) of discussion within WikiProjects, and as we investigate further we hope to expose how projects and Wikipedians engage with discussion as a means to further project progress and gain sustained support from the community. We have also already exposed a number of characteristics that differentiate different types of Wikipedians contributing to WikiProjects, which may provide some insight into the size and growth of particular projects.
The research that we've currently been doing raises a number of important and fundamental questions regarding how we study not only Wikipedia, but the Web in general. Our studies are showing how the Web is a thriving, evolving, and re-configuring ecosystem, partly technology, partly human. Is the Web as the output of human beings - which are are the most advanced organism on earth - organic itself? Shall we consider methods from evolutionary biology to understand the complex interrelations in this socio-technical ecosystem of humans, information and services? Can we define utility functions and what is the target of the potentially selfish maximization interest of the individual components when biological offspring cannot happen?
Such questions pose methodological, analytical, and philosophical challenges, and are central to many of the SOCIAM lines of research. In the coming weeks we’ll be posting more on these topics, including the development of a new approach to search, and how we can use this to conceptualize Wikipedia within a Web of data streams and information flows.