Goals of the workshop
This workshop aims at bringing together researchers and practitioners from different disciplines to explore the challenges and opportunities of novel approaches to collective intelligence, crowdsourcing and human computation that address social aspects as a core element of their design principles, implementations or scientific investigation.
As research in this quickly grown field matures, there is an increasing awareness of the need to more explicitly address social aspects of crowdsourcing and human computation in order to identify and overcome limitations – of conceptual, technical, social or ethical nature – of overly mechanistic models often underlying current approaches. However, there is still relatively little work that explicitly addresses the importance, implications and opportunities that arise when incorporating the perspective of crowd workers as social collectives into the design of crowdsourcing and human computation systems and applications.
Based on the successful experience of the two previous SoHuman workshops in 2012 and 2013, this workshop shall allow such questions to be considered in an interdisciplinary setting, from different perspectives at the intersection of the social sciences and computer science. The goal is to identify how experiences gained in the rich body of work on the design of socially-aware systems and applications and from the study of social dynamics in technologically-mediated, large-scale social systems can inform the conceptualization and the development of novel, socially-aware approaches to crowdsourcing and human computation.
Theme and topics
Both crowdsourcing and human computation consider humans as distributed task-solvers, with the latter embedding human users as a part of intelligent computational systems. They both leverage human reasoning to solve complex tasks that are easy for individuals but difficult for purely computational approaches (human computation) or for traditional organizational work arrangements (crowdsourcing). Effective realizations of these paradigms typically require participation of a large number of distributed users over the Internet, a careful design of task structures, participation incentives and mechanisms for coordinating and aggregating results of individual participants into collective solutions.
Though rarely explicitly addressed as such, social media and related technologies often provide the enabling methods and technologies for the realization of such models. Examples include crowdsourcing marketplaces (e.g. Amazon Mechanical Turk), crowdsourcing service providers (e.g. Microtask, CrowdFlower) or games with a purpose. While centralized platforms are also at the core of “traditional” approaches to collective intelligence (e.g. Wikipedia), attention is increasingly turning to the possibilities of harnessing existing social platforms (e.g. Facebook, Twitter) that already gather huge numbers of users into webs of social relationships. These new approaches to harnessing such distributed social infrastructures on the web can not only enable the design of novel kinds of crowdsourcing processes and applications but also allow us to reconsider some fundamental assumptions of current crowdsourcing architectures and conceptual models.
On one hand, the intricate social relationships allow the development of new kinds of task routing mechanisms (e.g. identifying the best or most trusted participants for a specific task). Incentive structures are intrinsically social and tend to reflect community-like phenomena (e.g. the reputation economy), thus differing strongly from single-user approaches in classical crowdsourcing. This is already leading to experiments such as expert-based crowdsourcing or solutions for task-injection across distributed social platforms. It is also partially reflected in growing research on inferring social influence, attention or trust from online social exchanges with the aim of providing mechanisms for more effective information exchanges or collective problem solving. On the other hand, designing such socially-aware models requires reconsidering the fundamental assumptions often underlying current models which basically mimic a “tayloristic” model of work division and related task-benefit ownership models harnessing work contributions of large numbers of individuals. For example, in dominant models of human computation, the users are typically considered as a part of a computational process operating without any awareness of each other’s work process, individual results or the broader task context. Accordingly, the majority of existing approaches provides little or no support for direct communication and collaboration between the users and models the user participation as private exchanges between the task-owner and the task-solver.
In contrast, experiences from the large body of knowledge on collaborative problem solving and collaborative knowledge production point to the importance of group interaction and communication in different kinds of collaborative social formations (e.g. online communities, social networks). They highlight the role of voluntary, open group participation where individual contributions form a collective good freely accessible and benefiting all users. They also show how the very nature of the context of open collaboration (though posing a number of challenges for effective coordination and operationalization) can also enable new modes of collective production, leading to otherwise unattainable solutions.
This begs the question of how such more open, participatory models of collective action can inform the development of new kinds of crowdsourcing and human computation systems and approaches: Can we conceptualize specific classes of human computation as instances of different forms of social collaboration? How can we design crowdsourcing and human computation systems where the involvement of a large number of diverse human users as providers, aggregators or “processors” of information leads to outcomes that benefit the entire collective rather than only individual contributors, task owners or commissioners of work assignments? How can the theory of collective action inform the design of such collaborative approaches to socially-aware crowdsourcing and human computation? What are the different sources of value of the “human touch” that can be brought to bear through such new approaches?
Relevance to the conference
In order to effectively address such questions the workshop will solicit contributions from researchers from social sciences and computer science working at the intersections of studying and/or designing the described classes of socio-technical systems, with a focus on socially-aware crowdsourcing and human computation. We are especially interested in novel approaches to understanding social dynamics and designing applications for a range of domains such as collective action and social deliberation, multimedia search and exploration, enterprise and medical applications, cultural heritage, social data analysis or citizen science. This also includes open social networks involving different user groups in heterogeneous settings (e.g. end-users, businesses, scientists, citizens, policy makers). By highlighting the importance of domain-specific challenges and specific use cases we can also enrich a technology-driven perspective with a user-centered view and system-level social dynamics.
By explicitly discussing the social aspects of collective systems and relating them to experiences from the practice of crowdsourcing and social computing (i.e. in terms of specific problems, conceptual models and use cases) the exchange of experiences between commonly disparate research communities from social sciences and different fields of computer science but which are working on related problems can be facilitated.
Such orientation to the social aspects of crowdsourcing and human computation and its linking to broader classes of social systems involving the shared production of collective goods and large-scale online social exchanges is a specific strength of this workshop.
The workshop is of interest to:
- 1) researchers and practitioners concerned with the development and evaluation of methods, technologies and applications for crowdsourcing and human computation, and
- 2) researchers and practitioners in social sciences, web science, computational social science and related fields working on the analysis, design, theory building and/or evaluation of large-scale social exchanges.
To ensure reaching the different audiences and participants the workshop organizers and the program committee involve experienced representatives from different fields in academic and business research.
We propose this workshop due to a high interest in our SoHuman workshop series, voiced especially by participants of our two previous workshops. The first SoHuman workshop took place in 2012, at IEEE Social Computing 2012 in Amsterdam, and the second, SoHuman 2013, at ACM WebScience 2013 in Paris. Both workshops were organized as half-day workshops. They have attracted lively interest with 29 registrations both in the first and second year. The diverse backgrounds of attendees and their active participation and discussion made them both successful events. For SoHuman 2013, we received a total of 17 paper submissions out of which 5 were presented (29% acceptance rate).
More information on the previous workshops is available at SoHuman2012 and SoHuman2013.
Workshop format and duration
This will be a full-day workshop. We expect approx. 20-30 participants (and are considering limiting the max. number of participants to ensure enough air-time for an intensive discussion).
The workshop format will be based on the well-received format of the preceding SoHuman workshops. After a short introductory talk by the workshop moderator (10-15min) followed by an invited keynote, there will be two paper sessions that each consists of 3 paper presentations. Each paper presentation will be assigned 30 min. including a Q&A slot after each presentation. The paper sessions will be followed by a discussion panel involving the participants in a moderated discussion. The discussion results will be summarized by the moderator in a final wrap-up session.
The workshop will accept contributions in the following formats:
- Regular research papers (6-8 pages)
- Applications / Demonstrators (4 pages)
- Position papers (2-4 pages)
All submissions will be reviewed in a peer-review process by at least two members of the program committee. At least one author of each paper will need to register for the conference and attend the workshop to present the paper.
Accepted workshop papers will appear in Springer’s Lecture Note Series in Computer Science as part of the conference proceedings but we also allow accepted papers to be presented without publication in the proceedings, if the authors prefer to do so. In addition, selected workshop papers will be invited for submission of an extended version to a fast-track special issue of the interdisciplinary journal Human Computation.