Presentation Open Access
Systems have emerged in the Web over the past decade that people have used to solve a wide range of problems. These systems are often defined as crowdsourcing systems. Any system can be defined as a crowdsourcing system if it involves a crowd of humans in a problem-solving process. Examples include Wikipedia, Stackoverflow or Mechanical Turk-based systems. Previous academic research on Wikipedia, for example, has almost exclusively focused on social structures, which represent existing community practices.
Although the role of humans in such complex problem-solving processes is important, researchers have only recently started to emphasize the importance of bots for crowdsourcing systems. Geiger (2009), for example, states that: “such tools transform the nature of editing and user interaction.”. In another study, Geiger shows “how a weak but pre-existing social norm was controversially reified into a technological actor” (Geiger, 2009). Müller-Birn et al. (2013) extend this line of research by showing that Wikipedia’s governance system consists of social mechanisms (e.g. formal and informal rules) as well as algorithmic mechanisms that are defined by software features and bots. Geiger & Halfaker (2013) show in a constitutive study how a distributed cognitive network of human and algorithmic actors works efficiently together to detect and revert vandalism on Wikipedia.
This research suggests that bots are more important to the success of crowdsourcing projects than expected previously. In my talk, I look at another representative of a crowdsourcing system – the Wikidata community. The goal of my research is to provide participation patterns for both humans and machines alike.