Crowd Dynamics: Exploring Conflicts and Contradictions in Crowdsourcing 

Call for papers: Deadline December 21, 2015.

Crowd Dynamics: Exploring Conflicts and Contradictions in Crowdsourcing A one-day workshop at CHI 2016, 7 or 8 May 2016, San Jose, CA, USA

In this workshop we explore the reasons, processes, power relations, and dynamics of conflicts within crowdsourcing. We invites participants to contribute with insights from different types of crowd-work, and thereby deepen our understanding about the relations in contexts such as crowdsourcing, crowd-funding, peer-production and citizen science. Furthermore, we examine strategies for accommodating differences in crowdsourcing environments. This one-day workshop explores the topics in mini presentations and brainstorming sessions, and will result in a research agenda for addressing these questions.

Subthemes and topics can for example be:

Citizen empowerment versus control in open government

Various levels of transparency in the implementation of crowdsourcing

Clash of needs between people and systems

Conflict management and conflict resolution in crowdsourcing

Conflicting discourses and theories about crowd work: E.g. solidarity versus the “economic man”

Conflicts of expectations in crowd contexts

Distribution of labor and capital in crowd work

Dynamics of inclusion/exclusion in crowd work, reflecting societal issues of race, gender, identity, and geography

Social capital and community engagement in crowd work conflicts

Research ethics in citizens’ science (or other types of crowd work)

The position-paper should be 2-4 pages and follow the CHI formatting guidelines for the CHI extended abstract format <;. Send submissions and inquiries to the following email address: <>

Deadline is Monday, December 21, 2015.

At least one author of the position paper must attend the workshop. All participants must register for both the workshop and for at least one day of the conference.

The workshop is organized by: Karin Hansson (Stockholm University), Michael Muller (IBM Research), Tanja Aitamurto (Stanford University), Lilly Irani (University of California), Athanasios Mazarakis (Kiel University), Neha Gupta (University of Nottingham), and Thomas Ludwig (University of Siegen).

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