Showing papers on "Crowdsourcing published in 2009"

The Value of Crowdsourcing: Can Users Really Compete with Professionals in Generating New Product Ideas?

Abstract: Generating ideas for new products used to be the exclusive domain of marketers, engineers, and/or designers. Users have only recently been recognized as an alternative source of new product ideas. Whereas some have attributed great potential to outsourcing idea generation to the “crowd” of users (“crowdsourcing”), others have clearly been more skeptical. The authors join this debate by presenting a real-world comparison of ideas actually generated by a firm’s professionals with those generated by users in the course of an idea generation contest. Both professionals and users provided ideas to solve an effective and relevant problem in the consumer goods market for baby products. Executives from the underlying company evaluated all ideas (blind to their source) in terms of key quality dimensions, including novelty, customer benefit, and feasibility. The study reveals that the crowdsourcing process generated user ideas that score significantly higher in terms of novelty and customer benefit, and somewhat lower in terms of feasibility. However, the average values for feasibility – in sharp contrast to novelty and customer benefit – tended to be relatively high overall, meaning that feasibility did not constitute a narrow bottleneck in this study. Even more interestingly, it is found that user ideas are placed more frequently than expected among the very best in terms of novelty and customer benefit. These findings, which are quite counterintuitive from the perspective of classic new product development (NPD) literature, suggest that, at least under certain conditions, crowdsourcing might constitute a promising method to gather user ideas which can complement those of a firm’s professionals at the idea generation stage in NPD.

Leveraging Crowdsourcing: Activation-Supporting Components for IT-Based Ideas Competition

Abstract: Ideas competitions appear to be a promising tool for crowdsourcing and open innovation processes, especially for business-to-business software companies Active participation of potential lead users is the key to success Yet a look at existing ideas competitions in the software field leads to the conclusion that many information technology (IT)-based ideas competitions fail to meet requirements upon which active participation is established The paper describes how activation-enabling functionalities can be systematically designed and implemented in an IT-based ideas competition for enterprise resource planning software We proceeded to evaluate the outcomes of these design measures and found that participation can be supported using a two-step model The components of the model support incentives and motives of users Incentives and motives of the users then support the process of activation and consequently participation throughout the ideas competition This contributes to the successful implementation and maintenance of the ideas competition, thereby providing support for the development of promising innovative ideas The paper concludes with a discussion of further activation-supporting components yet to be implemented and points to rich possibilities for future research in these areas

Crowdsourcing the Public Participation Process for Planning Projects

Abstract: Public involvement is a central concern for urban planners, but the challenge for planners is how best to implement such programs, given many difficulties inherent in the typical public involvement...

Community engineering for innovations: the ideas competition as a method to nurture a virtual community for innovations

Abstract: ‘Crowdsourcing’ is currently one of the most discussed key words within the open innovation community. The major question for both research and business is how to find and lever the enormous potential of the ‘collective brain’ to broaden the scope of ‘open R&D’. Based on a literature review in the fields of Community Building and Innovation Management, this work develops an integrated framework called ‘Community Engineering for Innovations’. This framework is evaluated in an Action Research project – the case of an ideas competition for an ERP Software company. The case ‘SAPiens’ includes the design, implementation and evaluation of an IT-supported ideas competition within the SAP University Competence Center (UCC) User Group. This group consists of approximately 60,000 people (lecturers and students) using SAP Software for educational purposes. The current challenges are twofold: on the one hand, there is not much activity yet in this community. On the other, SAP has not attempted to systematically address this highly educated group for idea generation or innovation development so far. Therefore, the objective of this research is to develop a framework for a community-based innovation development that generates innovations, process and product ideas in general and for SAP Research, in particular, combining the concepts of idea competitions and virtual communities. Furthermore, the concept aims at providing an interface to SAP Human Resources processes in order to identify the most promising students in this virtual community. This paper is the first to present an integrated concept for IT-supported idea competitions in virtual communities for leveraging the potential of crowds that is evaluated in a real-world setting.

Crowdsourcing and its application in marketing activities

Abstract: Crowdsourcing is a newly developed term which refers to the process of outsourcing of activities by a firm to an online community or crowd in the form of an ‘open call’. Any member of the crowd can then complete an assigned task and be paid for their efforts. Although this form of labour organisation was pioneered in the computing sector, businesses have started to use ‘crowdsourcing’ for a diverse range of tasks that they find can be better completed by members of a crowd rather than by their own employees. This paper examines how firms are utilising crowdsourcing for the completion of marketing-related tasks, concentrating on the three broad areas of product development, advertising and promotion, and marketing research. It is found that some firms are using crowdsourcing to locate large numbers of individuals willing to complete largely menial repetitive tasks for limited financial compensation. Other firms utilise crowdsourcing to solicit solutions to particular tasks from a crowd of diverse and/or expert opinions. Conclusions are drawn regarding the advantages and the limitations of crowdsourcing and the potential for the future use of crowdsourcing in additional marketing-related applications. Keywords: Crowdsourcing, Outsourcing, Wikinomics

Data Quality from Crowdsourcing: A Study of Annotation Selection Criteria

Abstract: Annotation acquisition is an essential step in training supervised classifiers. However, manual annotation is often time-consuming and expensive. The possibility of recruiting annotators through Internet services (e.g., Amazon Mechanic Turk) is an appealing option that allows multiple labeling tasks to be outsourced in bulk, typically with low overall costs and fast completion rates. In this paper, we consider the difficult problem of classifying sentiment in political blog snippets. Annotation data from both expert annotators in a research lab and non-expert annotators recruited from the Internet are examined. Three selection criteria are identified to select high-quality annotations: noise level, sentiment ambiguity, and lexical uncertainty. Analysis confirm the utility of these criteria on improving data quality. We conduct an empirical study to examine the effect of noisy annotations on the performance of sentiment classification models, and evaluate the utility of annotation selection on classification accuracy and efficiency.

Crowdsourcing and all-pay auctions

Abstract: In this paper we present and analyze a model in which users select among, and subsequently compete in, a collection of contests offering various rewards. The objective is to capture the essential features of a crowdsourcing system, an environment in which diverse tasks are presented to a large community. We aim to demonstrate the precise relationship between incentives and participation in such systems.We model contests as all-pay auctions with incomplete information; as a consequence of revenue equivalence, our model may also be interpreted more broadly as one in which users select among auctions of heterogeneous goods. We present two regimes in which we find an explicit correspondence in equilibrium between the offered rewards and the users' participation levels. The regimes respectively model situations in which different contests require similar or unrelated skills. Principally, we find that rewards yield logarithmically diminishing returns with respect to participation levels. We compare these results to empirical data from the crowdsourcing site Taskcn.com; we find that as we condition the data on more experienced users, the model more closely conforms to the empirical data.

Crowdsourcing for Enterprises

Abstract: Crowdsourcing is emerging as the new on-line distributed problem solving and production model in which networked people collaborate to complete a task. Enterprises are increasingly employing crowdsourcing to access scalable workforce on-line. In parallel, cloud computing has emerged as a new paradigm for delivering computational services, which seamlessly interweave physical and digital worlds through a common infrastructure.This paper presents a sample crowdsourcing scenario in software development domain to derive the requirements for delivering a general-purpose crowdsourcing service in the Cloud. It proposes taxonomy for categorization of crowdsourcing platforms, and evaluates a number of existing systems against the set of identified features. Finally, the paper outlines a research agenda for enhancing crowdsourcing capabilities, with focus on virtual team building and task-based service provisioning, whose lack has been a barrier to the realization of a peer-production model that engages providers from around the world.

Crowdsourcing, attention and productivity

Abstract: We show through an analysis of a massive data set from YouTube that the productivity exhibited in crowdsourcing exhibits a strong positive dependence on attention, measured by the number of downloads. Conversely, a lack of attention leads to a decrease in the number of videos uploaded and the consequent drop in productivity, which in many cases asymptotes to no uploads whatsoever. Moreover, short-term contributors compare their performance to the average contributor's performance while long-term contributors compare it to their own media.

A crowdsourceable QoE evaluation framework for multimedia content

Abstract: Until recently, QoE (Quality of Experience) experiments had to be conducted in academic laboratories; however, with the advent of ubiquitous Internet access, it is now possible to ask an Internet crowd to conduct experiments on their personal computers. Since such a crowd can be quite large, crowdsourcing enables researchers to conduct experiments with a more diverse set of participants at a lower economic cost than would be possible under laboratory conditions. However, because participants carry out experiments without supervision, they may give erroneous feedback perfunctorily, carelessly, or dishonestly, even if they receive a reward for each experiment. In this paper, we propose a crowdsourceable framework to quantify the QoE of multimedia content. The advantages of our framework over traditional MOS ratings are: 1) it enables crowdsourcing because it supports systematic verification of participants' inputs; 2) the rating procedure is simpler than that of MOS, so there is less burden on participants; and 3) it derives interval-scale scores that enable subsequent quantitative analysis and QoE provisioning. We conducted four case studies, which demonstrated that, with our framework, researchers can outsource their QoE evaluation experiments to an Internet crowd without risking the quality of the results; and at the same time, obtain a higher level of participant diversity at a lower monetary cost.

Optimal design of crowdsourcing contests

Abstract: This paper provides a game theoretic model of a crowdsourcing contest. Special attention is given to the asymptotic behavior of the contest outcome. We show that all significant outcomes of crowdsourcing contests will be determined by contestants in a small neighborhood (core) of the most efficient contestant type; in particular, the asymptotic structure of the crowdsourcing contests is distribution-free. Our formal analysis yields a managerially implementable and easily understood rule of thumb for the optimal division of the contest budget among multiple prizes. When agents are risk-neutral, the principal should optimally allocate all of its budget to the top prize even if it values multiple submissions. In contrast, if agents are sufficiently risk-averse, the principal may optimally offer more prizes than the number of submissions it desires. Our paper represents the first general analysis of the economics of crowdsourcing contests, provides a simple rule of thumb for determining the optimal prize structure for practitioners who are considering designing such contests, and also discusses the welfare implications of organizing production or R&D as a Web-based contest of this kind.

mCrowd: a platform for mobile crowdsourcing

Abstract: Crowdsourcing is a new paradigm for utilizing the power of "crowds" of people to facilitate large scale tasks that are costly or time consuming with traditional methods. Crowdsourcing has enormous potential that can be truly unleashed when extended to sensor-rich mobile devices, such as smart phones. In this paper, we demonstrate mCrowd, an iPhone based mobile crowdsourcing platform that enables mobile users to post and work on sensor-related crowdsourcing tasks. mCrowd enables mobile users to fully utilize the rich sensors equipped with iPhone to participate and accomplish crowdsourcing tasks at fingertips, including geolocation-aware image collection, image tagging, road traffic monitoring, and others.

Crowdsourcing: What can be Outsourced to the Crowd, and Why ?

Abstract: Why should a firm outsource certain activities in countries where labor is inexpensive, when by using the Internet, firms are a mouse click away from an eclectic, university educated, population ready to invest in intellectually stimulating projects for little or no remuneration ? The word Crowdsourcing –a compound contraction of Crowd and Outsourcing, was used by Howe in order to define outsourcing to the crowd. Beyond cost, benefits for the company can be substantial. It can externalize the risk of failure and it only pays for products or services that meet its expectations. The aim of this paper is to characterize Crowdsourcing from a management science perspective. Our approach is mainly theoretical, although we rely on extensive illustrations. First we discuss the definition of Crowdsourcing, and provide examples that illustrate the diversity of Crowdsourcing practices. Then, we present similarities and differences between Crowdsourcing and established theories (Open Innovation, User Innovation) and a phenomenon that has inspired many studies in Economics and Management, Open Source Software. Our goal is to avoid future misunderstandings and to show that Crowdsourcing is a concept per se. Finally, we propose and illustrate a typology of Crowdsourcing practices based on two criteria: the integrative or selective nature of the process and the type of tasks that are crowdsourced (routine, complex and creative tasks). In either case, the client firm seeks to mobilize external competencies. Relying upon the crowd can be an adequate method, because of its unique characteristics that are fostered by the Internet.

Evolution of User-generated Translation: Fansubs, Translation Hacking and Crowdsourcing

Abstract: Most conspicuous initially with Japanese anime fansubs, fan-based translation has been developing since the 1980s. In the advent of widespread availability of Web 2.0 platforms, fan translation has become a global phenomenon despite its dubious legal status. Extending the emerging interest in fansubs and scanlation in translation studies to the little discussed translation hacking by video game fans, this article brings readers‘ attention to participatory culture manifest in user-generated content in the field of translation and localisation. The article describes the evolution from unsolicited fan translation to solicited community translation now called crowdsourcing and considers them in the framework of user-generated translation (UGT). The article provides interdisciplinary perspectives, drawing on insights from media and game studies to address UGT which could profoundly impact the profession of translation and localisation as new technological environments unleash the technical competence, genre-knowledge and unparalleled devotion of the otherwise untrained Internet crowd as translators.This article is made available under a CC BY-NC 4.0 license.

Vox Populi: Collecting High-Quality Labels from a Crowd

Abstract: With the emergence of search engines and crowdsourcing websites, machine learning practitioners are faced with datasets that are labeled by a large heterogeneous set of teachers. These datasets test the limits of our existing learning theory, which largely assumes that data is sampled i.i.d. from a fixed distribution. In many cases, the number of teachers actually scales with the number of examples, with each teacher providing just a handful of labels, precluding any statistically reliable assessment of an individual teacher’s quality. In this paper, we study the problem of pruning low-quality teachers in a crowd, in order to improve the label quality of our training set. Despite the hurdles mentioned above, we show that this is in fact achievable with a simple and efficient algorithm, which does not require that each example be repeatedly labeled by multiple teachers. We provide a theoretical analysis of our algorithm and back our findings with empirical evidence.

Who are the Turkers? Worker Demographics in Amazon Mechanical Turk

Abstract: Amazon Mechanical Turk (MTurk) is a crowdsourcing system in which tasks are distributed to a population of thousands of anonymous workers for completion. This system is becoming increasingly popular with researchers and developers. In this paper, we survey MTurk workers about their demographic make-up and usage behavior. We find that this population is diverse across several notable demographic dimensions such as age, gender, and income, but is not precisely representative of the U.S. as a whole. Indeed, certain homogeneous aspects of the population, such as education level and nationality, may impose limits on the appropriateness of Turkers as a target community for some interventions or research areas. An awareness of the demographics and behaviors of MTurk workers is important for understanding the capabilities and potential side effects of using this system.

Crowds and communities: Light and heavyweight models of peer production

Abstract: Two collaborative forms of organizing dominate discussion of open participation and production on the Internet: a crowdsourcing model based on microparticipation from many, unconnected individuals, and a virtual community model, based on strong connections among a committed set of connected members. This paper argues that dimensions such as task interdependence, authority control, and group focus underpin behaviors associated with participation in such open systems, resulting in contributory behaviors that can be described at one end as ‘lightweight’, functioning by weak-tie attachment to a common purpose, enacted through authority-determined, rule-based contribution, and at the other end as ‘heavyweight’, operating through strong-tie affiliation with community members and community purpose, enacted through internallynegotiated, peer-reviewed contribution. Examination and articulation of these dimensions, and the resulting patterns of contributory behavior they engender, help reconcile peer production and virtual community approaches to online collaboration, explain motivational and structural aspects of new forms of collaborative production, and inform design for building and sustaining collective contributory systems.

Mapping for the Masses

Abstract: The authors describe how we are harnessing the power of web 2.0 technologies to create new approaches to collecting, mapping, and sharing geocoded data. The authors begin with GMapCreator that lets users fashion new maps using Google Maps as a base. The authors then describe MapTube that enables users to archive maps and demonstrate how it can be used in a variety of contexts to share map information, to put existing maps into a form that can be shared, and to create new maps from the bottom-up using a combination of crowdcasting, crowdsourcing, and traditional broadcasting. The authors conclude by arguing that such tools are helping to define a neogeography that is essentially ‘‘mapping for the masses,’’ while noting that there are many issues of quality, accuracy, copyright, and trust that will influence the impact of these tools on map-based communication.

Leveraging crowdsourcing – activationsupporting components for IT-based idea competitions

Abstract: Ideas competitions appear to be a promising tool for crowdsourcing and open innovation processes, especially for business-to-business software companies. Active participation of potential lead users is the key to success. Yet a look at existing ideas competitions in the software field leads to the conclusion that many information technology (IT)–based ideas competitions fail to meet requirements upon which active participation is established. The paper describes how activation-enabling functionalities can be systematically designed and implemented in an IT-based ideas competition for enterprise resource planning software. We proceeded to evaluate the outcomes of these design measures and found that participation can be supported using a two-step model. The components of the model support incentives and motives of users. Incentives and motives of the users then support the process of activation and consequently participation throughout the ideas competition. This contributes to the successful implementation and maintenance of the ideas competition, thereby providing support for the development of promising innovative ideas. The paper concludes with a discussion of further activation-supporting components yet to be implemented and points to rich possibilities for future research in these areas.

Designing crowdsourcing community for the enterprise

Abstract: In this paper, we describe the design principles used for implementing crowdsourcing within the enterprise. This is based on our distinction between two kinds of crowdsourcing: enterprise (inside a firewall) versus the public domain. Whereas public domain crowdsourcing offers monetary rewards in exchange for participation, we show that identifying the right social objects and using these in designing the incentive model is sufficient to incent, motivate, and sustain participation levels in enterprise crowdsourcing. Finally, we show that the systematic integration of the characteristics of levels of participation into the design, e.g., the distinction between direct and indirect crowdsourcing, is sufficient for optimizing users' participation and contributions.

Coordinating tasks on the commons: designing for personal goals, expertise and serendipity

Abstract: How is work created, assigned, and completed on large-scale, crowd-powered systems like Wikipedia? And what design principles might enable these federated online systems to be more effective? This paper reports on a qualitative study of work and task practices on Wikipedia. Despite the availability of tag-based community-wide task assignment mechanisms, informants reported that self-directed goals, within-topic expertise, and fortuitous discovery are more frequently used than community-tagged tasks. We examine how Wikipedia editors organize their actions and the actions of other participants, and what implications this has for understanding, and building tools for, crowd-powered systems, or any web site where the main force of production comes from a crowd of online participants. From these observations and insights, we developed WikiTasks, a tool that integrates with Wikipedia and supports both grassroots creation of site-wide tasks and self-selection of personal tasks, accepted from this larger pool of community tasks.

Outsourcing labour to the cloud

Abstract: Various forms of open sourcing to the online population are establishing themselves as cheap, effective methods of getting work done. These have revolutionised the traditional methods for innovation and have contributed to the enrichment of the concept of 'open innovation'. To date, the literature concerning this emerging topic has been spread across a diverse number of media, disciplines and academic journals. This paper attempts for the first time to survey the emerging phenomenon of open outsourcing of work to the internet using 'cloud computing'. The paper describes the volunteer origins and recent commercialisation of this business service. It then surveys the current platforms, applications and academic literature. Based on this, a generic classification for crowdsourcing tasks and a number of performance metrics are proposed. After discussing strengths and limitations, the paper concludes with an agenda for academic research in this new area.

Peoplecloud for the globally integrated enterprise

Abstract: Crowdsourcing has emerged as the new on-line distributed production model in which people collaborate and may be awarded to complete a task. While many existing services enable enterprises to employ the wisdom of crowd, there is no existing practice defined for integration of crowdsourcing with the business processes. We propose PeopleCloud, as the (1) mechanism to enable access to scalable workforce on-line, connecting it to the enterprise and (2) an interface to services required for crowdsourcing tasks. We define requirements for PeopleCloud, based on our experiences in employing wisdom of crowd to source business and IT information within the enterprise.

The Spectral Game: leveraging Open Data and crowdsourcing for

Abstract: We report on the implementation of the Spectral Game, a web-based game where players try to match molecules to various forms of interactive spectra including 1D/2D NMR, Mass Spectrometry and Infrared spectra. Each correct selection earns the player one point and play continues until the player supplies an incorrect answer. The game is usually played using a web browser interface, although a version has been developed in the virtual 3D environment of Second Life. Spectra uploaded as Open Data to ChemSpider in JCAMP-DX format are used for the problem sets together with structures extracted from the website. The spectra are displayed using JSpecView, an Open Source spectrum viewing applet which affords zooming and integration. The application of the game to the teaching of proton NMR spectroscopy in an undergraduate organic chemistry class and a 2D Spectrum Viewer are also presented.

Crowdsourcing and the question of expertise

Abstract: There is an in inherent weakness to crowdsourcing that should bother computer scientists and computer users alike. It’s the fact there is no clear difference between “the wisdom of the crowd” and “the mob that rules.” What’s missing is a measure of discernment. The Internet is awash in information that demands selectivity, leading Newsweek among others to predict the rise of online experts and reliable information (http://www.newsweek.com/id/119091). The assessment seems overly optimistic. There are some efforts to rate expertise on the Internet (http://cacm.acm.org/ news/42206), but most of us are left with coping strategies that limit where you go, what you see, and who you trust. It is not the kind of open investigation that promotes learning or understanding. Crowdsourcing doesn’t really help sort through or synthesize information, in fact, it might do the opposite. Research shows that it favors popular opinion and therefore reinforces homogeneity (http://cacm.acm.org/news/42525). That’s not hospitable to unconventional or idiosyncratic views. There is an upside, for sure. Luis von Ahn’s GWAP (http://www.gwap.com/ gwap/about/) uses computer games “to solve problems for humans all over the world.” And Galaxy Zoo tapped about 250,000 visitors to classify nearly one million galaxies (http://cacm.acm.org/magazines/2009/10/42492). Now the downside: The limitations of crowdsourcing are becoming apparent, even to its defenders. Blogger Josh Berkus summarizes key weaknesses, saying the term is “evil” and carries too much baggage (http://it.toolbox.com/ blogs/database-soup/never-say-crowdsourcing-34331). In the end he concludes that the problem is mainly about improper usage. But the issue is bigger than that. The problem with crowdsourcing is that there is no verity. In fact, “correctness [is]...anathema to crowdsourced systems” (http://cacm.acm.org/magazines/2009/7/32094). That’s a small concern when rating movies, but researchers and scientists need something more. Science needs higher standards. This was illustrated by Newsweek when it decried science education in the U.S. and showed how “wisdom of the masses” is an oxymoron. It described how John Holdren, director of the White House Office of Science and Technology Policy, trades candor for political timidity when discussing science policy (www.newsweek.com/id/216505). “He must sell his ideas to people who couldn’t pass high-school algebra—and who believe they know more than he does.” Crowdsourcing empowers followers. It risks weakening leaders. DOI:10.1145/1610252.1610258 David Roman

Effectiveness of Temporal Snippets

Abstract: We introduce the notion of time-centered snippets, called TSnippet, as document surrogates for document retrieval and exploration. We propose an alternative document snippet based on temporal information that can be useful for supporting exploratory search. The idea of using sentences that contain the most frequent chronons (units of time) can be used for constructing document surrogates. We conducted a series of experiments to evaluate this new approach using a crowdsourcing approach. The evaluation against two Web search engines shows that our technique produces good snippets and users like to see time-sensitive information in search results.

Rule-Based Problem Classification in IT Service Management

Abstract: Problem management is a critical and expensive element for delivering IT service management and touches various levels of managed IT infrastructure. While problem management has been mostly reactive, recent work is studying how to leverage large problem ticket information from similar IT infrastructures to probatively predict the onset of problems. Because of the sheer size and complexity of problem tickets, supervised learning algorithms have been the method of choice for problem ticket classification, relying on labeled (or pre-classified) tickets from one managed infrastructure to automatically create signatures for similar infrastructures. However, where there are insufficient preclassified data, leveraging human expertise to develop classification rules can be more efficient. In this paper, we describe a rule-based crowdsourcing approach, where experts can author classification rules and a social networkingbased platform (called xPad) is used to socialize and execute these rules by large practitioner communities. Using real data sets from several large IT delivery centers, we demonstrate that this approach balances between two key criteria: accuracy and cost effectiveness.

Relevance criteria for e-commerce: a crowdsourcing-based experimental analysis

Abstract: We discuss the concept of relevance criteria in the context of e-Commerce search. A vast body of research literature describes the beyond-topical criteria used to determine the relevance of the document to the need. We argue that in an e-Commerce scenario there are some differences, and novel and different criteria can be used to determine relevance. We experimentally validate this hypothesis by means of Amazon Mechanical Turk using a crowdsourcing approach.

Online Knowledge Crowds and Communities

Abstract: While much has been written about virtual knowledge communities, particularly in how to create and sustain long-term, strong-tie relationships, the connection has not been made to newer forms of online organizing such as crowdsourcing. This paper addresses the way knowledge collectives are organized online, considering the organizational and motivational structures that support these new knowledge collectives, and contrasting the social mechanisms that support crowdsourced knowledge from those that support community-based knowledge. Examination of the literature and cases of crowds and virtual communities suggest a number of important dimensions that distinguish these two forms of organizing, including contribution type and size, personal coorientation and commitment to the knowledge topic, interpersonal ties among contributors, authority and control of contributory practices, and recognition and reward systems. Exploring these different models of organizing knowledge provides insight into the ways to establish and maintain crowdand community-based knowledge collectives, and also show why strong knowledge communities such as those found in academia come to change their knowledge distribution practices, notably from print to online publication.