Incentive-Centered Design for User-Contributed Content

Jian, Lian; MacKie-Mason, Jeffrey K.

doi:10.1093/oxfordhb/9780195397840.013.0015

Cited by 9 publications

(4 citation statements)

References 95 publications

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“…Later developments of ICT as control systems rooted in IT (Nightingale et al, 2003) already have a flavor of applicationoriented mode. Beyond a systemic perspective of LTS theory, some studies consider specific ICT industries and mechanisms that grew atop the ICT infrastructure - Bresnahan et al (2014) for mobile applications, Moore & Anderson (2012) for internet security, Jian et al (2012) for the user-contributed production model of information goods -just to name few. In sum, in line with other studies, the results of the analysis indicate that the evolution of the ICT cluster is taking place and seems to have a direction towards agile, scalable, and omnipresent (mobile access) configuration with myriads of applications and devices.…”

Section: Results and Discussion: Inside The Ict Technology Systemmentioning

confidence: 99%

ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links

Prytkova¹

2021

SSRN Journal

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This paper seeks to contribute to the understanding of diffusion patterns and relatedness within ICT as a technology system in the EU28 region. Considering ICT as a technology system, first, I break down ICT into a set of distinct technologies employing OECD and WIPO classifications. Then, using text analysis and the Algorithmic Links with Probabilities method, I construct industrytechnology links to connect industries with ICT and track ICT's diffusion over the period 1977-2020. The analysis highlights the heterogeneity of the technologies that constitute the ICT cluster. As not all ICTs are pervasive and not all ICTs are key technologies, this leads to differences in industry reliance on them. The results indicate that the ICT cluster shows signs of a "phase transition", passing the phase of building bulk elements of the infrastructure and around the 2000s entering the phase of working on the functionality for business applications deployment and users' convenience. This transition is marked by the surging relevance of ICT technologies such as mobile communication, information analysis, security, and human interface. Studying the ICT as a cluster allows putting each ICT technology in context to compare them in relative terms; this is especially important for the discussion of novel and fast-growing technologies such as Artificial Intelligence (AI). Concerning the structure of industry reliance on the ICT cluster, ICT's penetration is characterized by increasing scope but unevenly distributed scale; depending on the industry and the distinct ICT technology the intensity of their connections varies significantly. Remarkably, looking closer at AI technologies, in line with the current literature, a wide array of "shallow" connections with industries is revealed. Finally, I calculate relatedness metrics to estimate proximity among ICT technologies. The analysis reveals differences in the underlying knowledge base among the overwhelming majority of the ICT technologies but a similar structure of their application base.

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Section: Results and Discussion: Inside The Ict Technology Systemmentioning

confidence: 99%

ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links

Prytkova¹

2021

SSRN Journal

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“…Some crowdsourcing systems (e.g., MTurk [6]) offer financial incentives for participation [18], many others are driven by social-psychological rewards, e.g., both intrinsic motivators like interest [10,12,20] or the satisfaction of benefiting a cause [9] (e.g., participating in a scientific research [13,40]), as well as extrinsic social rewards such as reputation or status [1]. There is now a growing effort in social psychology that aims to address what motivates contributors in crowdsourcing systems [2,21,23,24]. A related and well studied research problem is how to allocate rewards to incentivize desirable outcomes [18].…”

Section: Related Workmentioning

confidence: 99%

Rating Mechanisms for Sustainability of Crowdsourcing Platforms

Qiu

Squicciarini

Rajtmajer

2019

Proceedings of the 28th ACM International Conference on Information and Knowledge Management

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Crowdsourcing leverages the diverse skill sets of large collections of individual contributors to solve problems and execute projects, where contributors may vary significantly in experience, expertise, and interest in completing tasks. Hence, to ensure the satisfaction of its task requesters, most existing crowdsourcing platforms focus primarily on supervising contributors' behavior. This lopsided approach to supervision negatively impacts contributor engagement and platform sustainability. In this paper, we introduce rating mechanisms to evaluate requesters' behavior, such that the health and sustainability of crowdsourcing platform can be improved. We build a game theoretical model to systematically account for the different goals of requesters, contributors, and platform, and their interactions. On the basis of this model, we focus on a specific application, in which we aim to design a rating policy that incentivizes requesters to engage lessexperienced contributors. Considering the hardness of the problem, we develop a time efficient heuristic algorithm with theoretical bound analysis. Finally, we conduct a user study in Amazon Mechanical Turk (MTurk) to validate the central hypothesis of the model. We provide a simulation based on 3 million task records extracted from MTurk demonstrating that our rating policy can appreciably motivate requesters to hire less-experienced contributors. CCS CONCEPTS • Social and professional topics; • Theory of computation → Mathematical optimization; • Computing methodologies → Modeling and simulation;

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“…private businesses, often struggle to encourage and manage activity. Administrators of platforms face three challenges: motivating potential first-time users, making them connect to the platform and encouraging the contribution of content that is useful to others (Lerner and Tirole (2002), Jian and MacKie-Mason (2012)).…”

Section: Introductionmentioning

confidence: 99%

Centrality and content creation in networks - The case of economic topics on German wikipedia

Kummer

Saam

Halatchliyski³

et al. 2016

Information Economics and Policy

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We analyze the role of local and global network positions for content contributions to articles belonging to the category "Economy" on the German Wikipedia. Observing a sample of 7, 635 articles over a period of 153 weeks we measure their centrality both within this category and in the network of over one million Wikipedia articles. Our analysis reveals that an additional link from the observed category is associated with around 140 bytes of additional content and with an increase in the number of authors by 0.5. The relation of links from outside the category to content creation is much weaker. Beyond the econometric analysis, our study sheds light on how the discipline of economics is represented on German Wikipedia. We find non-neoclassical themes to be highly prevalent among the top articles.

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Incentive-Centered Design for User-Contributed Content

Cited by 9 publications

References 95 publications

ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links

ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links

Rating Mechanisms for Sustainability of Crowdsourcing Platforms

Centrality and content creation in networks - The case of economic topics on German wikipedia

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