Designing crowdsourcing community for the enterprise

Stewart, Osamuyimen; Huerta, Juan M.; Sader, Melissa

doi:10.1145/1600150.1600168

Cited by 44 publications

(38 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Others point out that a task should be performed for free or for much less than the costs incurred by the firm (Kleeman, Voss & Rieder, 2008). Some authors suggest that the best situation is one in which the award is not important and the motivation would be passion or participation in amusement (Stewart, Huerta & Sader, 2009). …”

Section: Dimensions Of Crowdsourcingmentioning

confidence: 99%

Virtual Knowledge Sharing in Crowdsourcing: Measurement Dilemmas

Lenart-Gansiniec

2017

JEMI

View full text Add to dashboard Cite

show abstract

Section: Dimensions Of Crowdsourcingmentioning

confidence: 99%

Virtual Knowledge Sharing in Crowdsourcing: Measurement Dilemmas

Lenart-Gansiniec

2017

JEMI

View full text Add to dashboard Cite

show abstract

“…Also, he identifies a basic pattern with respect to the structure of crowdsourcing Information System (IS), which includes four main components that perform user management (providing capabilities for user registration, user evaluation, user group formation and coordination), task management (providing capabilities for task design and assignment), contribution management (providing capabilities for contributions evaluation and selection) and workflow management (providing capabilities for defining and managing workflows), respectively. Furthermore, there are some studies that attempt to generalize the experience gained from successful applications of crowdsourcing ideas in order to develop effective practices for motivating individuals to participate (Brabham 2009;Stewart et al 2009). Rouse (2010), based on a review of relevant literature, distinguishes between two types of crowdsourcing with respect to participants' motivation: (i) individualistic (aiming to provide benefits to specific persons and firms), (ii) community oriented (aiming to benefit a community of some kind, through ideas and proposals), and (iii) mixed (combinations of the above).…”

Section: Crowdsourcingmentioning

confidence: 99%

Active and Passive Crowdsourcing in Government

Loukis

Charalabidis

2015

Policy Practice and Digital Science

View full text Add to dashboard Cite

Crowdsourcing ideas have been developed and initially applied in the private sector, first in the creative and design industries, and subsequently in many other industries, aiming to exploit the 'collective wisdom'in order to perform difficult problem solving and design activities. It was much later that government agencies started experimenting with crowdsourcing, aiming to collect from citizens information, knowledge, opinions and ideas concerning difficult social problems, and important public policies they were designing for addressing them. Therefore, it is necessary to develop approaches, and knowledge in general concerning the efficient and effective application of crowdsourcing ideas in government, taking into account its special needs and specificities. This chapter contributes to filling this research gap, by presenting two novel approaches in this direction, which have been developed through extensive previous relevant research of the authors: a first one for 'active crowdsourcing', and a second one for 'passive crowdsourcing' by government agencies. Both of them are based on innovative ways of using the recently emerged and highly popular Web 2.0 social media in a highly automated manner through their application programming interfaces (API). For each of these approaches, the basic idea is initially described, followed by the architecture of the required information and communications technology (ICT) infrastructure, and finally a process model for its practical application.

show abstract

“…A typical example is the study presented in [34], which, based on the analysis of several case studies, identifies four dominantcrowdsourcing types/approaches: i) the knowledge discovery and managementapproach (= an organization tasks crowdwith finding and reporting information and knowledge on a particular topic), ii) the broadcast search approach (= an organization tries to find somebody who has experience with solving a rather narrow and rare empirical problem), iii) the peer-vetted creative production approach (= an organization tasks crowdwith creating and selectingcreative ideas), and iv) distributed human intelligence tasking (= an organization tasks crowdwith analyzing largeamounts of information). Also, there are some studies that aim to develop methodologies for the practical application of crowdsourcing in various types of organizations, and for the motivation of individuals to participate [35] - [37].…”

Section: Crowdsourcingmentioning

confidence: 99%

Public Policy Formulation through Non Moderated Crowdsourcing in Social Media

Charalabidis

Triantafillou

Karkaletsis

et al. 2012

Electronic Participation

View full text Add to dashboard Cite

Abstract. The emergence of web 2.0 social media enables the gradual emergence of a second generation of e-participation characterized by more citizens' control, in which government agencies post content (e.g. short or longer text, images, video) to various social media and then analyze citizens' interactions with it (e.g. views, likes/dislikes, comments, etc.). In this paper we propose an even more citizens controlled third generation of e-participation exploiting web 2.0 social media as well, but in a different manner. It is based on the search by government agencies for content on a public policy under formulation, which has been created in a large set of web 2.0 sources (e.g. blogs and microblogs, news sharing sites, online forums) by citizens freely, without any initiation, stimulation or moderation through government postings. This content undergoes advanced processing in order to extract from it arguments, opinions, issues and proposals on the particular policy, identify their sentiments (positive or negative), and finally summarize and visualize them. This approach allows the exploitation of the vast amount of user-generated content created in numerous web 2.0 social media for supporting governments to understand better the needs, wishes and beliefs of citizens, and create better and more socially rooted policies.

show abstract

Designing crowdsourcing community for the enterprise

Cited by 44 publications

References 2 publications

Virtual Knowledge Sharing in Crowdsourcing: Measurement Dilemmas

Virtual Knowledge Sharing in Crowdsourcing: Measurement Dilemmas

Active and Passive Crowdsourcing in Government

Public Policy Formulation through Non Moderated Crowdsourcing in Social Media

Contact Info

Product

Resources

About