Crowd Science

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    Managing Initial Coin Offerings: Towards a Taxonomy of ICO Processes
    ( 2019-01-08) Lipusch, Nikolaus ; Dellermann, Dominik ; Ebel, Philipp
    Initial Coin Offerings are a new type of crowd-based fundraising mechanism that uses the blockchain to issue tokens to a crowd of people in exchange for funds that blockchain start-ups use to develop their business. Unfortunately, due to the recency of this new phenomenon, there is no systematic understanding of the ICO process and its underlying process characteristics. However, companies engaging in ICOs should be able to evaluate and choose the right process steps to best achieve their goal. Against this background, we develop a taxonomy for ICO processes. In contrast to previous work, this classification scheme focuses exclusively on the processual nature of ICOs and its underlying mechanisms.
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    Imperatives in Past Online Discussions: Another Helpful Source for Community Newcomers?
    ( 2019-01-08) Xiao, Lu ; Nickerson, Jeffrey
    Experienced members of online communities use discussion to familiarize newcomers with norms. These members use imperatives, a kind of directive speech act, to suggest a course of action. A method for automatically recognizing such imperatives is described here. The recognition performance of the algorithm is compared to that of human readers. In addition, to test and illustrate the technique, the imperatives in a sample of Wikipedia deletion discussions are extracted, analyzed, and discussed. The method may be used not only to understand a community’s culture and practices but also to elicit information that is beneficial to the community’s newcomers.
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    Crowds and Camera Traps: Genres in Online Citizen Science Projects
    ( 2019-01-08) Rosser, Holly ; Wiggins, Andrea
    Despite the importance of instruction for effective task completion in crowdsourcing, particularly for scientific work, little attention has been given to the design of instructional materials in crowdsourcing and citizen science. Consequences of inattention to tutorial design are further magnified by the diversity of citizen science volunteers. We use digital genre theory to identify the norms of tutorial design for the most abundant citizen science project type on the Zooniverse platform, camera trap image classification, where a highly-standardized task structure makes it a strong candidate as a specific genre of citizen science. Comparative content analysis of 14 projects’ features, tutorial design, and supporting materials identified a great deal of uniformity in some respects (indicating an emergent genre) but surprising variation in others. As further evidence of an emergent genre, the amount of mentoring the science team received and specific task features of the project appeared to impact tutorial design and supporting resources. Our findings suggest that genre theory provides a useful lens for understanding crowd science projects with otherwise disparate characteristics and identifying instances where the digital medium can be deployed more effectively for task instruction.
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    Is Quality Control Pointless?
    ( 2019-01-08) Krause, Markus ; Afzali, Farhad Mohammad ; Caton, Simon ; Hall, Margeret
    Intrinsic to the transition towards, and necessary for the success of digital platforms as a service (at scale) is the notion of human computation. Going beyond ‘the wisdom of the crowd’, human computation is the engine that powers platforms and services that are now ubiquitous like Duolingo and Wikipedia. In spite of increasing research and population interest, several issues remain open and in debate on large-scale human computation projects. Quality control is first among these discussions. We conducted an experiment with three different tasks of varying complexity and five different methods to distinguish and protect against constantly underperforming contributors. We illustrate that minimal quality control is enough to repel constantly underperforming contributors and that this is constant across tasks of varying complexity.
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    Introduction to the Minitrack on Crowd Science
    ( 2019-01-08) Prpić, John ; Kietzmann, Jan