How to Manage Crowdsourcing Platforms Effectively

AbstractCrowdsourced tasks are very diverse – and so are platform types. They fall into four categories, each demanding different governance mechanisms. The main goal of microtasking crowdsourcing platforms is the scalable and time-efficient batch processing of highly repetitive tasks. Crowdsourcing platforms for information pooling aggregate contributions such as votes, opinions, assessments and forecasts through approaches such as averaging, summation, or visualization. Broadcast search platforms collect contributions to solve tasks in order to gain alternative insights and solutions from people outside the organization, and are particularly suited for solving challenging technical, analytical, scientific, or creative problems. Open collaboration platforms invite contributors to team up to jointly solve complex problems in cases where solutions require the integration of distributed knowledge and the skills of many contributors. Companies establishing crowdsourcing platforms of any type should continuously monitor and adjust their governance mechanisms. Quality and quantity of contributions, project runtime, or the effort for conducting the crowdsourcing project may be good starting points.

Download Full-text

How to Manage Crowdsourcing Platforms Effectively?

California Management Review ◽

10.1177/0008125617738255 ◽

2017 ◽

Vol 60 (2) ◽

pp. 122-149 ◽

Cited By ~ 20

Author(s):

Ivo Blohm ◽

Shkodran Zogaj ◽

Ulrich Bretschneider ◽

Jan Marco Leimeister

Keyword(s):

Case Studies ◽

Governance Mechanisms ◽

Open Collaboration ◽

Information Pooling

To profit from crowdsourcing, organizations can engage in four different approaches: microtasking, information pooling, broadcast search, and open collaboration. This article presents 21 governance mechanisms that can help organizations manage their crowdsourcing platforms. It investigates the effectiveness of these governance mechanisms in 19 case studies and recommends specific configurations of these mechanisms for each of the four crowdsourcing approaches. Also, it offers guidance to organizations that host a crowdsourcing platform by providing recommendations for implementing governance mechanisms into their platforms and building up governance capabilities for crowdsourcing.

Download Full-text

The Next Step: Acquisitions and Open Collaboration Platforms [Connected Vehicles]

IEEE Vehicular Technology Magazine ◽

10.1109/mvt.2018.2813441 ◽

2018 ◽

Vol 13 (2) ◽

pp. 14-16

Author(s):

Elisabeth Uhlemann

Keyword(s):

Connected Vehicles ◽

Open Collaboration ◽

Collaboration Platforms

Download Full-text

Impact of social features implemented in open collaboration platforms on volunteer self-organization

Proceedings of the 9th International Symposium on Open Collaboration - WikiSym '13 ◽

10.1145/2491055.2491081 ◽

2013 ◽

Cited By ~ 1

Author(s):

Junghong Choi ◽

Bruce Ferwerda ◽

Jungpil Hahn ◽

Jinwoo Kim ◽

Jae Yun Moon

Keyword(s):

Self Organization ◽

Open Collaboration ◽

Social Features ◽

Collaboration Platforms

Download Full-text

The Comparative Legislators Database

10.31235/osf.io/kapfq ◽

2020 ◽

Author(s):

Sascha Göbel ◽

Simon Munzert

Keyword(s):

Visual Information ◽

Comparative Research ◽

R Package ◽

Micro Data ◽

Public Attention ◽

Social Scientists ◽

Individual Level ◽

Open Collaboration ◽

Ready Access ◽

Collaboration Platforms

Knowledge about political representatives’ behavior is crucial for a deeper understanding of politics and policy-making processes. Yet resources on legislative elites are scattered, often specialized, limited in scope, or not always accessible. We introduce the Comparative Legislators Database (CLD), which joins micro-data collection efforts on open-collaboration platforms and other sources, and integrates with renowned political science datasets. The CLD includes political, sociodemographic, career, online presence, public attention, and visual information for over 45,000 contemporary and historical politicians from ten countries. We provide a straightforward and open-source interface to the database through an R package, offering targeted, fast, and analysis-ready access in formats familiar to social scientists and standardized across time and space. We verify the data against human-coded datasets and illustrate its use for investigating legislator prominence and turnover. The CLD contributes to a central hub for versatile information about legislators and their behavior, supporting individual-level comparative research over long periods.

Download Full-text

Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia

Information Systems Research ◽

10.1287/isre.2019.0899 ◽

2020 ◽

Vol 31 (2) ◽

pp. 491-509

Author(s):

Kai Zhu ◽

Dylan Walker ◽

Lev Muchnik

Keyword(s):

Feedback Loop ◽

Large Scale ◽

Natural Experiment ◽

Information Networks ◽

Community Governance ◽

Causal Understanding ◽

Open Collaboration ◽

Information Poverty ◽

Natural Dynamics ◽

Collaboration Platforms

Open collaboration platforms have fundamentally changed the way that knowledge is produced, disseminated, and consumed. Although the community governance and open collaboration model of Wikipedia confers many benefits, its decentralized nature can leave questions of information poverty and skewness to the mercy of the system's natural dynamics. In this paper, we leverage a large-scale natural experiment to gain a causal understanding of how exogenous content contributions to Wikipedia articles affect the attention that they attract and how that attention spills over to other articles in the information network. We find a positive feedback loop: content contribution leads to significant and long-lasting increases of attention and future contribution. Unfortunately, this also suggests that impoverished regions of information networks are likely to remain so in the absence of intervention. However, our analysis reveals a potential solution. Articles in impoverished regions of information networks are particularly positioned to benefit from the phenomenon of attention spillovers. Using a simulation that is calibrated with real-world link traffic of the Wikipedia network, we show that an attention contagion policy, which focuses editorial effort coherently on impoverished regions, can lead to as much as a twofold gain in attention relative to unguided contributions.

Download Full-text

The Comparative Legislators Database

British Journal of Political Science ◽

10.1017/s0007123420000897 ◽

2021 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Sascha Göbel ◽

Simon Munzert

Keyword(s):

Visual Information ◽

Comparative Research ◽

R Package ◽

Micro Data ◽

Public Attention ◽

Social Scientists ◽

Individual Level ◽

Open Collaboration ◽

Ready Access ◽

Collaboration Platforms

Abstract Knowledge about political representatives' behavior is crucial for a deeper understanding of politics and policy-making processes. Yet resources on legislative elites are scattered, often specialized, limited in scope or not always accessible. This article introduces the Comparative Legislators Database (CLD), which joins micro-data collection efforts on open-collaboration platforms and other sources, and integrates with renowned political science datasets. The CLD includes political, sociodemographic, career, online presence, public attention, and visual information for over 45,000 contemporary and historical politicians from ten countries. The authors provide a straightforward and open-source interface to the database through an R package, offering targeted, fast and analysis-ready access in formats familiar to social scientists and standardized across time and space. The data is verified against human-coded datasets, and its use for investigating legislator prominence and turnover is illustrated. The CLD contributes to a central hub for versatile information about legislators and their behavior, supporting individual-level comparative research over long periods.

Download Full-text