Crowdsourcing Systems and Social Media

This track focuses on socio-technical systems that create value through the collective actions of many. These actions include producing, appraising and sharing content, as well as performing various types of work.

Papers are expected to contribute a new algorithm, new data analysis results, new applications of practical relevance, new frameworks, etc. Papers should be clearly positioned with respect to previous work, convey clearly the importance of the contribution and findings, and report in detail the methodology used and the obtained results, including a comparison with state-of-the-art methods when appropriate.

Topics include:

  • Modeling, design and operation of crowdsourcing systems and social media platforms.
  • Workflow optimization based on expertise, compatibility, time constraints, etc.
  • Engagement, motivations, incentives, and gamification.
  • Trust, reputation, security, privacy, and ethics.
  • Mining of social media and crowd-generated data; studying off-line phenomena with on-line data.
  • Trend identification, tracking, and forecasting; time-sensitive and real-time analysis.
  • Interactions of human computation and machine intelligence.
  • Virtual communities including massive multi-player games, massive courses, fora, and others.
  • Impacts and applications in traditional/mainstream media, governments, non-governmental organizations and business, and in sectors such as health care, science, and education.
  • Impacts in employment, labor, legislation, politics, governance, democracy and economics; changes in homes, workplaces, schools, and the city.

If the core elements of your contribution are graph algorithms or graph analysis, please also check the call for papers of the social networks and graph analysis track.

For questions related to this call, please email:

Area Chairs

  • Lada Adamic, Facebook
  • Carlos Castillo, Qatar Computing Research Institute
  • Nick Koudas, University of Toronto

Program Committee

  • Jussara Almeida, UFMG
  • Marcos Baez, Dipartimento di Ingegneria e Scienza dell’Informazione, University of Trento
  • Roja Bandari, UCLA
  • Fabio Casati, University of Trento
  • Justin Cheng
  • Michele Coscia, National Research Council, Pisa
  • Munmun De Choudhury, Georgia Institute of Technology
  • Yashar Ganjali, University of Toronto
  • Daniel Gatica-Perez, Idiap and EPFL
  • Daniel Gayo Avello, University of Oviedo
  • Werner Geyer, IBM T.J. Watson Research
  • Manuel Gomez-Rodriguez
  • Sandra Gonzalez-Bailon, University of Pennsylvania
  • Bahareh Heravi
  • Andreas Hotho, University of Wuerzburg
  • Yun Huang, Syracuse University
  • Panos Ipeirotis, New York University
  • Venky Iyer
  • Anupam Joshi
  • David Jurgens, McGill University
  • Brian Keegan, Northeastern University
  • Emre Kiciman, Microsoft Research
  • Patty Kostkova, City ehealth Research Centre (CeRC), City University, London
  • Ee-Peng Lim, Singapore Management University
  • Yu-Ru Lin, University of Pittsburgh
  • Peter Marbach
  • Winter Mason, Facebook
  • Michael Mathioudakis
  • Julian Mcauley, UC San Diego
  • Panagiotis Metaxas, Wellesley College
  • Tanushree Mitra, Georgia Institute of Technology
  • Andres Monroy-Hernandez
  • Sue Moon, KAIST
  • Michael Muller, IBM Research
  • Aditya Pal, IBM
  • Stelios Paparizos, Microsoft Research
  • Walter Quattrociocchi, Labss,Institute of Cognitive Sciences and Technologies
  • Daniele Quercia, Yahoo Labs
  • Bruno Ribeiro, Carnegie Mellon University
  • Daniel Romero, University of Michigan
  • Derek Ruths, McGill University
  • Antonio Scala
  • Anna Squicciarini, The Pennsylvania State University
  • Markus Strohmaier, University of Koblenz-Landau
  • Arun Sundararajan, New York University
  • Siddhart Suri
  • Maja Vukovic, IBM Research
  • Claudia Wagner, GESIS-Leibniz Institute for the Social Sciences
  • Ingmar Weber, Qatar Computing Research Institute
  • Cong Yu, Google Research
  • Haiyi Zhu, Carnegie Mellon University