SoHuman 2013 : 2nd International Workshop on Social Media for Crowdsourcing and Human Computation
Call For Papers
SoHuman 2013 – 2nd International Workshop on Social Media for Crowdsourcing and Human Computation, May 1, 2013, Paris
at ACM Web Science 2013
collocated with ACM HyperText'13 & ACM CHI'13 & ACM ECRC'13
GOALS OF THE WORKSHOP
This workshop invites researchers and practitioners from different disciplines to explore the challenges and opportunities of applying social media to designing novel applications of collective intelligence, with a special focus on crowdsourcing and human computation.
We are particularly interested in contributions that consider crowdsourcing and
human computation in the broader context: as specific instantiations
intelligence and social computing on the web. How can the experience gained from the design of crowdsourcing applications inform the development of new approaches to collective intelligence? And vice versa: what lessons from the broader domain of collective intelligence can inform the design of new kinds of systems for crowdsourcing and human computation?
Both crowdsourcing and human computation consider humans as distributed task-solvers, leveraging 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). Though rarely explicitly addressed as such, social media often provide the enabling methods and technologies for the realization of such models. While centralized platforms are at the core of “traditional”
approaches to both crowdsourcing (e.g. mTurk) and collective
intelligence (e.g. Wikipedia),
attention is increasingly turning to harnessing existing social platforms (e.g. Facebook, Twitter) that already gather huge numbers of users into webs of social relationships.
Such Social Clouds pose both chances and challenges for new kinds of approaches to crowdsourcing and human computation in particular and to collective intelligence in general. 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 early experiments such as expert-based crowdsourcing or solutions for task- injection across distributed social platforms. On the other hand, the design of such socially distributed computing structures relates the fields of crowdsourcing and human computation to the lessons from a broader class of collective intelligence platforms and applications.
The need to interrelate these fields is reflected in questions such as:
• How can we design effective incentive systems for large-scale
human users in structured collective intelligence systems?
• How do we design tasks at different levels of complexity that can be
through a composition of individual contributions?
• How can we use intricate webs of social relationships of existing
for new models of coordination in distributed task-solving?
• How can distributed social media enable the design of new classes of
applications (e.g. using social network analysis for new ways of task- routing)?
• How can the comparison of lessons from distributed problem-solving
computation and community-based approaches lead to novel classes of collective
We are especially interested in applications and investigations in 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.
TOPICS (include but are not limited to):
- Social media in collective intelligence systems
- Use cases and applications of social media to crowdsourcing and
- Social incentive models for crowdsourcing and human computation
- Social-network analysis for crowdsourcing and human computation
- Applications of social media visualization to collective
- Social coordination in crowdsourcing and human computation
- Social search and human computation
- Trust models for collective intelligence and crowdsourcing
- Semantic modeling in crowdsourcing and human computation
- Expert-based crowdsourcing
- Influence metering and social trust models
- Expertise-inference techniques and their application to task routing
- Reputation systems for human computation
- Quality assurance in distributed human intelligence tasks
- Social sensing in crowdsourcing and human computation
- Domain-specific challenges in crowdsourcing and human computation
- Social sensing in human computation approaches
- Use cases and applications of social media for human computation
The workshop will accept:
• Regular research papers (6-8 pages)
• Applications / Demonstrators (4 pages)
• Position papers (2-4 pages)
All submissions must be formatted according to ACM Web Science submission guidelines (http://www.websci13.org/submission/) and submitted through the SoHuman 2013 EasyChair system:
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 and attend the workshop to present the paper.
• Abstract submission: March 15, 2013 (recommended)
• Paper submission: March 20, 2013
• Notification of acceptance: April 3, 2013
• Camera-ready papers: April 17, 2013
• Workshop date: May 1, 2013
Results of the workshop (papers, findings from the discussion panel) will be published as separate workshop proceedings (either as Springer Lecture Notes in Computer Science or as CEUR-WS Proceedings). Depending on the quality of the submissions there may be an opportunity to publish extended versions of the papers as a special issue in a major journal.
Jasminko Novak, European Institute for Participatory Media, Berlin Piero Fraternali, Politecnico di Milano Petros Daras, ITI CERTH Otto Chrons, Microtask Alejandro Jaimes, Yahoo Research Mark Klein, MIT Center for Collective Intelligence
Contact: Jasminko Novak, firstname.lastname@example.org
Klemens Böhm, Karlsruhe Institute of Technology Marco Brambilla, Politecnico di Milano Simon Caton, Karlsruhe Institute of Technology Fausto Giunchiglia, University of Trento Gareth Jones, Dublin City University Pietro Michelucci, DARPA Ville Miettinen, Microtask Wolfgang Prinz, Fraunhofer FIT/RWTH Aachen Naeem Ramzan, University of West of Scotland Marcello Sarini, University of Milano-Bicocca Aaron Shaw, Harvard University Mohammad Soleymani, Geneva University Maja Vukovic, IBM T.J. Watson Research