First Monday

User-generated online content 1: Overview, current state and context by Pamela J. McKenzie, Jacquelyn Burkell, Lola Wong, Caroline Whippey, Samuel E. Trosow, and Michael McNally

This paper reviews a wide range of scholarly and popular literature to provide an overview of the current state of online user–generated content (UGC). We describe the UGC value chain, introduce three varieties of content (creative content, small–scale tools, and collaboratively–created content), and describe the factors unique to each variety. We then identify the common elements across varieties: motivations for content creation, mechanisms to support content creation and control content quality, and value creation. Throughout the article we identify the interrelationships between social and commercial forces on UGC creation and distribution.


Overview and current state of user–generated content
Motivation for creating user–generated content
Creator support and quality control
Value creation




User–generated content is widespread on the Internet. In 2011, more than 25 percent of Web users browsed with an open source Web browser (Pingdom, 2011). Between 2008 and 2011, Apple paid US$2.5 billion to developers of iPhone applications (Jain, 2011). Real–time tweets about the 2011 Japanese earthquake and tsunami reshaped both news reporting and emergency management (Acar and Muraci, 2011).

The proliferation of user–generated content (UGC) is perhaps the most significant development in the field of digital content creation over the past decade. Non–trivial components of the design, development, production, marketing, and distribution of media products increasingly develop through direct user involvement and outside of corporate structures (Banks and Potts, 2010). The concepts of “crowdsourcing” (Shirky, 2008), “wikinomics” (Tapscott and Williams, 2008) and the “long tail” (Anderson, 2006) have been widely hailed in the business world as ushering in new and empowering democratic models of production and distribution where power is shared between producers and consumers.

Yet UGC remains underutilized and understudied and, with respect to public policy, greatly misunderstood. Commercial leveraging of user–generated content such as apps, videos, or photos is a complex process, and many digital media creators and potentially valuable creations fail to realize their value in the marketplace. The goal of this paper is to develop a deeper understanding of the process of user–generated content creation and distribution and particularly its complex relationship to both social engagement and commercial production.

This article synthesizes a broad range of literature to provide a snapshot of the current state of the constantly evolving world of user–generated content. First, we provide an overview of three overarching and intersecting models of content creation and distribution:

  1. Creative content: Individual textual, audio, image, video, and multimedia productions that are distributed online through software platforms such as blogs, podcasting repositories, Flickr, Twitter, YouTube, and citizen journalism sites;
  2. Small–scale tools: Software modifications or applications that are written by individuals to operate within or augment specific previously existing datasets or hardware or software platforms (e.g., mobile phone applications or “apps,” utilities that manipulate publicly available data sets, game or virtual world modifications); and,
  3. Collaborative content: Formal or informal consortia that collaboratively produce and distribute UGC, including open source software (OSS), such as Linux or Apache, and wikis, such as Wikipedia.
After identifying the distinctive features of each we will describe common considerations of the UGC value chain, including the motivations of content creators, support for content creators and quality control, and value creation. The paper will provide the context for a discussion of policy issues elaborated in a companion article (McNally, et al., this issue of First Monday).




We conducted exhaustive literature searches to identify relevant research insights, evidence, interpretations, policy, and effective practices in the private, public and not–for–profit sectors. These searches encompassed a) scholarly literature within relevant disciplines (e.g., cultural and media studies, journalism, communication, library and information science, sociology, anthropology, psychology, education, political science, law, economics, business, and computer science) along with the work of scholars drawing from multiple disciplines; b) the popular press; and, c) grey literature (relevant reports, press releases, and policy documents from government, business, and not–for–profit organizations).



Overview and current state of user–generated content

We define user–generated content as content that is voluntarily developed by an individual or a consortium and distributed through an online platform. Our definition is similar in intent to the two facets of the Organization for Economic Cooperation and Development (OECD) definition of user–created content: content “which reflects a certain amount of creative effort, and which is created outside of professional routines and practices“ [1]. Our definition is deliberately broad in scope in order to capture all forms of digital content created outside of workplace environments. Our definition therefore consciously includes open source software and other forms of voluntary user–created content distributed within proprietary hardware or software frameworks. Adopting this broad definition enables us both to consider the specific characteristics of three forms of UGC (creative content, small–scale tools, and collaborative content) and to identify common themes across these forms that a narrower definition would obscure. Our review thereby provides broader insight into creator motivations, creator support and quality control, and monetization, insights that are necessary for making effective policy decisions.

A 2007 OECD report identifies differences between off–line and user–generated online production and distribution models. Off–line, the line between amateur and professional, paid and unpaid work is both prominent and difficult to cross. Physical production and distribution are expensive and as a result gatekeepers with significant financial resources select works to be published and distributed that meet established quality standards. Consumer preference may inform the gatekeepers’ decisions about future works, and existing works may inspire the work of future creators [2]. Of the works created, however, few make it to broad distribution.

The production and distribution chain for user–generated online content is rather different. Any user with access to the tools and resources and the expertise to use them is able to create and publish content. The hardware and technological infrastructure requirements for online UGC range from the very basic (reliable electricity and a computer with a broadband Internet connection; Borgne–Bachschmidt, et al., 2008) to the highly specialized (mobile devices, data capture devices including digital cameras, video cameras, GPS units, game consoles, etc.). Given the increasing accessibility of these means of production, more and more people are in the position to create and distribute their own content.

In 2011 approximately 30 percent of the world’s population had Internet access, an increase of nearly 500 percent since 2001 (Internet World Stats, 2011). Although unequal access remains an issue, developing countries have increased their share of the world’s total number of Internet users from 44 percent in 2006 to 62 percent in 2011. In developing countries, 25 percent of homes have a computer and 20 percent have Internet access (International Telecommunications Union [ITU], 2011). At least part of the increase in online participation reflects a generational effect. Younger people are likely to be online: people under 25 make up 45 percent of Internet users worldwide (ITU, 2011), and will continue to be Internet users as they age. Mobile technology is a driving factor in user–generated content due to the ease with which devices can now capture and acquire, create and deliver content from almost any location (Zawodny, 2004; Ubalde, 2010). Global penetration of mobile–cellular subscriptions has reached 5.9 billion, approximately 87 percent worldwide and 79 percent in the developing world (ITU, 2011). Approximately 45 percent of the world’s population is covered by high–capacity 3G networks, and 2G coverage is twice that high (ITU, 2011).

In addition to these basics, UGC creators require access to content creation devices, tools, raw materials, and platforms. Compared to physical content creators they are able to create and often distribute their own content, often much more quickly than would be possible in a traditional model. User–generated content is in much higher supply than traditional media because a much larger number of active creators are able to distribute their creations. Consumers of the content select and evaluate it through recommending and rating, providing some creators with recognition that they would not have received from traditional publishers [3].

There are numerous ways to classify user–generated content. For example, UGC can be classified according to the medium or format in which it is developed, distributed, and consumed. These may include audio, video, text, augmented reality, code, or combinations of formats. UGC can also be classified according to the model of creation. Haythornthwaite (2009), for example, distinguishes between a crowdsourcing model based on micro–participation from many unconnected individuals and a virtual community model based on strong connections among a committed set of connected members.

Our classification takes advantage of both dimensions. Our first two categories, creative content and small–scale tools, are productions of individuals or small well–defined groups distinguished according to form: textual, audio, visual and multimedia for the former and code for the latter. Our third category includes large–scale collaboration forms of UGC. Each of our three categories also reflects a distinct mode of production and distribution. We understand creative content to be platform–independent, while small–scale tools build on existing platforms. They are therefore created in conjunction with formal and often proprietary organizations. We distinguish our third category, collaborative content, as consciously collaboratively produced, evaluated, aggregated, and distributed.

Our classification has the advantage of highlighting both technical media and social models of production. We acknowledge, however, that our categories are by no means mutually exclusive. For example, any content may be created individually or collaboratively and may be developed for an existing platform; for example, a citizen journalism app or a newspaper created for a virtual world. Secondly, “collaborative” creation may encompass both individual contributions to a collective and true community–based development (Haythornthwaite, 2009). Finally, many social, technical, and policy issues span the three domains. Following our descriptions of the unique characteristics of each model, we will discuss considerations common to all.

1. Creative content

Individuals, working alone or informal groups, create a wide variety of textual, audio, or visual content, which they may distribute through online platforms including social networks. Content can focus on any topic. Although its ultimate consumption may require format–specific hardware or software such as an MP3 player, the content itself is platform–independent.

Textual content may take the form of individual Web sites, blogs, reviews, or content posted to online fora, networks, discussion groups, or zines. Blogs (Larsson and Hrantinski, 2011) began as online diaries and Web logs as early as 1991 (Blood, 2002; Ammann, 2011). By December 2011, there were over 180,400,000 identified blogs online, with more than 90,000 new blogs created each day (BlogPulse, n.d.). Microblogs are short blog postings, often 140 characters or less, that describe the poster’s current status. Although only eight percent of the American population posts to the microblogging site Twitter (Webster, 2011), there are well over 140 million tweets per day (Rao, 2011).

Audio, still image, video, and multimedia are other important formats of individually produced content. Approximately 2.5 billion photos are uploaded to Facebook per month (Pingdom, 2010). Every minute, Flickr members upload over 3,000 images (Sheppard, 2010) and YouTube users upload 60 hours’ worth of videos (YouTube, 2011). Audio or video podcasts and vidcasts are normally a series of digital media released episodically like blogs and made available for download through a Web syndication service (infotechusa, 2009). Podcasting is gaining in popularity, with 45 percent of Americans aware of the format and over 20 percent listening to and viewing podcasts (Webster, 2010).

The hardware and software tools for the production of creative content can be very simple. Textual content, for example, requires only a computer and an Internet connection, and basic knowledge of software for text editing and file upload and download. The production of other content forms requires additional hardware and/or software, such as digital cameras for taking photographs, recording devices for capturing audio, video cameras for creating videos, and software for capturing, editing, and publishing content.

One key characteristic of individually created UGC is how quickly and readily content can be produced. For example, the most active publishers of user–generated video post over 1,000 videos over a few years: by contrast, a prolific commercial film director might produce 100 films in 50 years (Cha, et al., 2007). The speed of production allows content creators to post breaking news and participate in citizen journalism (Gil De Zúñiga, et al., 2011) as demonstrated by the role of social media in the 2011 “Arab spring” (Attia, et al., 2011), in elections (Small, 2011), and emergencies (Acar and Muraki, 2011; Li, et al., 2011; Murthy, 2011; Tseng, et al., 2011).

Effective aggregation and distribution sites act as a one–stop shop for distribution, aggregation, and consumption of UGC. Successful sites share a number of key characteristics: they are easy to locate, easy to access, easy to navigate and use, and they support effective mechanisms for content searching. Aggregator sites host or distribute content from many producers. Open Diary, Live Journal, Wordpress, TypePad, and Squarespace, for example, are blog hosting sites; Webshots, SmugMug, Flickr, Photobucket, and Picasa host photos; and, sites such as Twitter, Jaiku, Pownce, Posterous, Tumblr, and FriendFeed distribute microblog posts. YouTube, acquired by Google in 2006, has emerged as the primary distributor of online video content. Viewers exceed three billion per day (YouTube, 2011). Similar sites for developing audio content have developed over the past five years (e.g., Mixcloud (2011) and SoundCloud (2007–2012)). UGC aggregation and distribution sites attract a great deal of online traffic. As of 12 April 2012, sites distributing creative content rank among the highest–viewed Web 2.0 sites (eBizMBA, 2011) and the highest traffic Web sites overall (Alexa, n.d.): YouTube (first; eBizMBA/ third Alexa), Wikipedia (second/seventh), Twitter (third/ninth), Wordpress (fifth/19th), Flickr (sixth/35th), Tumblr (10th, 54th). Although Blogspot does not rank on the eBizMBA top 15 list, it ranks 10th in overall traffic (Alexa, n.d.).

Increasingly, these sites also serve as online social environments, and the distinction between repositories and social media sites is blurring (Sobel, 2010). Aggregation and distribution sites are often focused on managing a single content format, but are now incorporating social networking functions (e.g., YouTube, Flickr), and social networking sites are now widely used for sharing user–generated content (Khanra and Biswas, 2010). The desire to share albums with family and friends has led photo sharing Web sites to add social functionality such as the ability to comment, change privacy settings, include a select network of contacts, and add tags to categorize photos (Reagan, 2008; Van House, 2007).

For UGC producers, social and potential commercial interests intertwine in content distribution, and content is often distributed through multiple channels serving different functions. For example, a photo could be published to the creator’s own Web page, posted to a blog, posted to a dedicated photo sharing site, posted to a social networking site, and/or uploaded to many other online repositories. Content may be posted for the benefit of the creator’s social network, but may also serve to enhance the creator’s reputation and possibly bring financial gain or benefit, for example when a magazine editor arranges to publish a Flickr photo. Peer networks play an important role in distribution. For example, a video can be shared between friends on a Facebook wall or played in front of face–to–face group at a party. The peer setting may increase the video’s appeal and influence viewers to share it again with others. Social networks enable the broader distribution of content through linking, crediting (Ammann, 2011), and retweeting (Webberley, et al., 2011). Content creators can interact with readers, viewers, or listeners, for example through comment threads (Thelwall, et al., 2012). These interactions may themselves develop into new networks and communities (Gruzd, et al., 2011; Marwick and boyd, 2011; Panteli, et al., 2011; Cheng, 2011; van Dijck, 2011) that further feed distribution.

2. Small–scale tools

Individual users or groups of users may create small–scale tools to augment a specific hardware or software platform or to provide access to a pre–existing data set. We discuss three forms of small–scale tools: (1) modifications (mods), add–ons, virtual objects and/or tools created by users of games such as World of Warcraft (Blizzard Entertainment, 2004) or virtual worlds such as Second Life (Linden Lab, 2003); (2) user created software applications (apps) for hardware platforms such as mobile devices such as the iPhone or Android or for social media platforms such as Facebook; and, (3) apps that manipulate, analyze, or provide access to publicly available data sets as the OpenBlock initiative (Vernon, 2010).

User–generated content in video games or virtual worlds can be traced back to 1961, with the creation of Spacewar! by a group of MIT students (Kow and Nardi, 2010a). Mods (Scacchi, 2011) are an important aspect of many gaming and virtual world environments, and user/participants create mods in part to increase their own enjoyment of the environment (Nieborg, 2005). Virtual worlds and games exist on a continuum from ludic (fixed synthetic worlds and goal–oriented games, such as Super Mario Brothers) (Pearce, 2009) to paidaic (open–ended worlds designed for spontaneous play and creative contribution, such as Second Life) (Pearce, 2009; Tschang and Comas, 2010). Many ludic games allow players a limited amount of freedom to create on top of or parallel to the pre–designed game content (Burri–Nenova, 2010). For example, modification culture in the First Person Shooter (FPS) genre is well developed. Massively Multiplayer Online Games (MMOGs), such as World of Warcraft (Blizzard Entertainment, 2004) or EverQuest (EverQuest, n.d.) occupy the middle ground between ludic and paidaic. When they are published, they are not completely set in stone: they are changeable by both the developer and the player population (Humphreys, 2009). Game play in MMOGs in fact depends on this kind of participant activity. Kow and Nardi (2010b) identified nearly 4000 mods created by the player population of the highly popular MMOG World of Warcraft (WoW). Paidaic virtual worlds depend to an even greater extent on modifications. Residents of the full–scale three–dimensional virtual space Second Life (SL), for example, had created over one million objects by 2004 (Ondrejka, 2004; White, 2008).

While the term “apps” typically refers to small–scale programs designed to perform a specific task within a hardware or software environment, there is no standard industry–wide definition (Purcell, et al., 2010). Apps have become particularly important since the advent of smartphones. The release of the iPhone platform presented an unprecedented opportunity for one or two person teams to create apps that could compete against those from major companies (Wooldridge and Schneider, 2010). The potential market for apps is massive: in the past three years Apple reports 15 billion cumulative app downloads from their App Store (Jain, 2011). Because small–scale tools are built on top of or alongside existing hardware or software platforms, content creators require access to tools and relevant platform–related content. Some of these are open access while others are proprietary.

The App Bank ( aggregates and distributes social content and games for uploading to social networks. Game mods are aggregated and distributed on specialized Web sites (e.g., or Modders also want control of the distribution of their mods so they can monitor user questions and track bugs (Kow and Nardi, 2010a). The modder community considers it best practice to make mods available through free distribution sites such as and WoWInterface. These sites allow players to download mods for free and are seen as a safe place for downloading by the community.

In some cases, mods and apps rely on open data supplied by users themselves or by governments in open data initiatives. For example, Sporcle, a quiz app, (Sporcle, 2007–2011) relies on user– or crowd–sourced data. Numerous mapping applications depend on user–generated data (e.g., Waze, a crowdsourced navigation app). The blending of technologies (e.g., linking integration of GPS information with Web access) and increasing mobility of technology is allowing for geo–spatial data and location–based services such as Foursquare or Gowalla to become integrated with user–generated content (Zickuhr and Smith, 2010).

Open data and open access projects provide free access to data sets and development tools for content creators. Open source tools as Open Mashups allow users more easily to create their own data mashups, virtual worlds (Burri–Nenova, 2010), or game apps ( These tools make it easier for users to go from idea to application and are therefore likely to increase the number and range of user–generated apps and data mashups. User/creator communities may also provide needed expertise, as veterans mentor newcomers and members create fora and other resources to share the community’s content–creation expertise (White, 2008).

Numerous federal, regional, and municipal governments provide data for content creators, including British Ordnance Survey released geodata (Chilton, 2011) and the U.S. government’s (2010), part of its Open Government Directive (Orszag, 2009). has hundreds of apps available using a broad range of U.S. federal data (, 2010). The Canadian National Research Council provides citizens data at no cost and with minimal restrictions. The GeoGratis license grants users a royalty free license to exercise all the intellectual property rights in the data (Natural Resources Canada, 2011).

Users have created applications to take advantage of open access government data on topics including municipal spending (Greater London Authority, n.d.), public transit (Next Stop, 2010), garbage and recycling, and the location of child–friendly activities (City of San Francisco, 2000–2012). These innovative uses of government data sets show that by simply providing access to data along with reasonable licensing terms, the range of content citizens can create is quite broad.

3. Content collaboratively produced and disseminated

Although many UGC creators work individually or in small co–located groups, the Internet also facilitates the production and distribution of content by sustained, though evolving, self–regulating groups of geographically dispersed contributors. This paper considers two primary forms of collaborative UGC: open source software and wikis.

Open source software (OSS) refers to a model of software production that is premised on making the human–readable source code accessible, allowing users to study, change, and improve the software (Aksulu and Wade, 2010; Androutsellis–Theotokis, et al., 2010). We define the term broadly to include both open source and free/libre software. SourceForge, a distribution platform for open source software, includes 2.7 million developers, 260,000 projects, and more than 46 million consumers of open source software content (SourceForge, 2012).

Community norms play a significant role in OSS projects, where the lack of physical boundaries places an increased emphasis on social relations (von Hippel and von Krogh, 2003; Dizon, 2010; Benkler, 2002; Maxwell, 2006; Merges, 2004, Strandburg, 2009, Elkin–Koren, 2005). OSS communities typically operate with a collaborative, heterarchical rather than hierarchical management structure (Iannacci and Middleton–Kelly, 2005). By drawing on community norms, users are able to collaborate and produce works that are beyond the capacity of isolated individuals. A collaborative norm works to limit egotistical behaviour (Maher, 2000) and establishes community–specific ownership rules (Merges, 2004; Kow and Nardi, 2010a; 2010b). A range of non–financial incentives (Benkler, 2002), including the fate of the group itself, may thus become a motivator for individuals (von Hippel and von Krogh, 2003).

Leaders play a critical role in ensuring the success of OSS projects by overseeing the logistical problems involved in collaborative projects (Maher, 2000) and by attracting and retaining talented individuals (Lerner and Tirole, 2002). However, they must avoid attempting to control volunteers through a rigid hierarchical structure (Schweik and English, 2007).

While some OSS systems are now run by foundations with paid staff (such as the Mozilla Foundation that oversees the Firefox Web browser), many of the most successful OSS projects can trace their roots to student programmers (Lerner and Tirole, 2002). Collaborative open source successes such as the Linux kernel, Apache Web server, Mozilla Firefox Web browser, and Perl programming language [4] demonstrate that meritocratic, collaborative governance systems may offer advantages over the traditional firm–based approach. Benefits include superior information processing capabilities and minimal transaction costs (Benkler, 2002). The World Intellectual Property Organization (WIPO) describes OSS as a “successful alternative” to using copyright to manage software [5].

Wikis are software platforms designed to facilitate collaborative writing, posting, revision, and tracking of the history of projects. One of the largest and the best known is the online encyclopaedia Wikipedia (Ayers, et al., 2008; Myers, 2010; Okoli, 2009). Wikipedia has surpassed the amount of content found in established print encyclopedias in every language (Lih, 2009). The English version has 3.9 million pages and there have been more than half billion page edits since its creation (Wikipedia, n.d.). With its open authorship model, Wikipedia holds the potential for collective memory building as well as the sharing of factual content (Ferron and Massa, 2011; Keegan, et al., 2011).

The Wikimedia Foundation that operates Wikipedia also provides Wikitionary, a wiki dictionary; Wikiquote, a repository of famous quotations; and, Wikinews, a news wiki (Wikimedia Foundation, 2011).

Despite the distinctions among these three types of content, there are many similarities and overlaps in their production and distribution. One of the main features of UGC is that its creation by non–professional users effectively straddles market and non–market interests. The lines between waged and unwaged producers and social and financial gain are blurry and permeable. The inclusion of non–market values into production models means that creator communities may develop innovative social models for collaboration that may conflict with traditional business models.

The remainder of this paper discusses three points on the UGC value chain that illustrate the intertwining of social and economic values in UCG and have particular implications for policy: motivation, creator support and quality control, and value creation.



Motivation for creating user–generated content

In general, motivational rewards are divided into two classes: intrinsic and extrinsic (Deci and Ryan, 1985). Intrinsic motivations are motivations that stem directly from performance of the task itself, and include the motivations to do something because it is interesting, enjoyable, or inherently satisfying. Extrinsic motivations, by contrast, relate to the products, outcomes, or consequences of having done the task: monetary reward and reputational enhancement are obvious examples of extrinsic motivations. It is important to note that the categories of intrinsic and extrinsic motivation are defined relative to the task, and not relative to the individual performing the task. Thus, some rewards that are entirely internal to the individual (e.g., a feeling of satisfaction from having completed a task) are classed as extrinsic rewards.

Under this categorization, most motivations are extrinsic in that they are outcomes or consequences of task performance. These extrinsic motivations include the purely psychological effects of task performance such as self–image enhancement and personal goal attainment (Ryan and Deci, 2000). Such intra–psychic rewards, however, are clearly different in nature from monetary or reputational rewards that originate from outside the individual. This difference in the source (internal or external) of the reward leads to confusion among some researchers examining UGC motivations, who mistakenly identify internally–generated rewards (e.g., the opportunity to share thoughts and feelings with a community) as intrinsic motivations (see, e.g., Liao, et al., 2011). In our analysis of UGC motivations, we follow the standard definition of intrinsic and extrinsic motivations, identifying intra–psychic rewards as extrinsic motivations.

According to Ryan and Deci (2000), intrinsic motivations are more robust catalysts of activity than are extrinsic rewards. Ryan and Deci distinguish, however, among varieties of extrinsic motivation, noting that some extrinsic rewards, particularly those that relate to internal and self–endorsed goals (e.g., self–image enhancement), can also be powerful activity motivators (Ryan and Deci, 2000). This is particularly important given that intrinsic motivations are not the only or even the chief motivations for many activities, especially as we move into adulthood and are required by social and other demands to take on tasks for reasons other than pure enjoyment. Typically, extrinsic motivations are thought to undermine intrinsic motivation: that is, the greater the focus on rewards associated with task outcome, the less participants are intrinsically motivated to carry out the task (see, e.g., Bénabou and Tirole, 2006; Deci and Ryan, 1985). Other work, however, suggests that extrinsic and intrinsic motivations can have a synergistic relationship (Amabile, 1993). This is particularly true when the initial levels of intrinsic motivation are high, and when the extrinsic motivators support a sense of competence and do not undermine a sense of personal autonomy with respect to the activity (Amabile, 1993). In their work Ryan and Deci (2000) identify this latter type of extrinsic motivator as having a high degree of internalization or personal commitment. Extrinsic rewards that are lowest in this respect are external rewards and punishments; those that are highest in this respect are those that are assimilated into the self, essentially becoming self–regulated rather than externally regulated.

Understanding the motivations of the creators of UGC is a crucial prerequisite to the crafting of policies. We report here on motivations that predict UGC contribution across a broad range of people and contribution types. We recognize that motivational factors interact with individual psychology and individual needs, with the result that different motivations take precedence for different individuals (see, e.g., Alexy and Leitner, 2011; Chen, 2012; Füller, 2010; Nov, et al., 2008; Yang and Lai, 2010). A detailed review of these individual differences is, however, beyond the scope of this article. Motivational factors are also likely to differ across cultures (e.g., Kamata, et al., 2010), and we acknowledge a selective focus on research examining North American populations. In addition, motivational factors vary with experience or tenure: Bagozzi and Dholakia (2006), for example, demonstrate that social/community motivations are stronger for those open source software contributors who have a longer involvement with the project and the community. With respect to contribution types, there appear to be systematic differences in the factors that promote contribution to collaborative products (e.g., Wikipedia, or crowdsourced tagging, etc.) and to individual productions (e.g., blogs, photographs, videos, etc.). In general, extrinsic rewards, including financial compensation and reputation enhancement, are more influential in the context of individual productions, while intrinsic rewards are more important in the context of collaborative production. Open source software is an unusual case, in that it is a collaborative activity for which many contributors identify self–interest motives (e.g., career enhancement, skills development; Wagner and Prasarnphanich, 2007). Where relevant, we highlight the different motivations that lead to these types of contributions.

Some research identifies intrinsic motives for the production of UGC. Intrinsic motivation is an important motivator for participation in crowdsourcing (Kaufmann, et al., 2011; Zheng, et al., 2011). ‘Fun’ appears to be an important motivating factor for Wikipedians (Nov, 2007), those who contribute distributed resources to large–scale scientific endeavours (Nov, et al., 2011), producers of creative content such as videos and images (Brabham, 2008; Stoeckl, et al., 2007), and even some contributors to open source software initiatives (Baytiyeh and Pfaffman, 2010a; Bitzer, et al., 2007; Luthiger and Jungwirth, 2007). The majority of research, however, focuses on extrinsic motivations. This should not be construed to mean that intrinsic motivations are not operative, only that extrinsic motivations are more salient and/or more likely to be the focus of research.

It would be a mistake to think that all or even most creators of UGC are financially motivated: in fact, most UGC is created by non–professionals who have no expectation of monetary reward or incentive (Park and van der Schaar, 2010), and the motivation to gain money is not systematically related to UGC production (Zheng, et al., 2011; Ke and Zhang, 2009; Leimeister, et al., 2009; Roberts, et al., 2006). That is not to say, of course, that financial compensation is unwelcome, but rather to suggest that it is not the primary motivation for UGC production. There is some concern that the provision of monetary rewards could disturb intrinsic motivation (i.e., inherent enjoyment in the task; Deci, et al., 1999), but the research on this question is divided, and there is certainly no strong and consistent evidence that financial compensation reduces the influence of other motivations (Alexy and Leitner, 2011; Roberts, et al., 2006).

Financial compensation takes on particular importance as a motivating factor for some specific types of content. A number of advertisers (e.g., Heinz ketchup) have initiated contests for user–generated advertisements, with significant financial windfalls for the contest winners (Virzi, 2007). Monetary compensation is of particular importance to participants in this type of “open innovation” or crowdsourcing environment, where companies turn to the broader community for innovative ideas (Antikainen and Väätäjä, 2010). Economic incentives also operate as important motivations in open source software development (Wu, et al., 2007). There are many sites that tell users how to make money from their online contributions (e.g., tweets on Twitter, blogs, etc.) by attracting and advertising to a large audience, and some content aggregation sites even provide direct payment to contributors. News sources, for example, have experimented with nominal payment to citizen journalists who contribute stories (Thurman, 2008). Some sites such as that distribute crowdsourced content provide small payouts to contributors whose content is accessed/downloaded/used. Youtube has instituted a revenue sharing program with “more prolific and popular producers” who have “built and sustained large audiences” (CBC News, 2007): in theory at least this arrangement can result in significant financial compensation for the producers (allowing video producers to share in the profit that YouTube garners from their productions). Such a revenue–sharing arrangement could very well be the long–term goal (or dream) of some committed UGC producers, and few would refuse the less significant and often unlikely rewards offered under other systems. Most UGC production, however, must be motivated by other factors, since significant financial gain is an uncertain reward reserved for a very small minority of producers.

It seems logical that reputation development/enhancement would be a motivation for the production of UGC (see discussion by Anderson, 2006). This motivation can operate only where contributors believe that productions are identifiable (that is, attributable to a specific producer: Chen and Roth, 2011), and in these situations attention to one’s productions is often an important motivation for some UGC production (Halavais, 2009; Rui and Whinston, 2011; Wu, et al., 2009; see also Sun, et al., 2006, related to sharing of ‘tips’ in online gaming). Individual studies have identified reputation enhancement as a motive for unpaid contributors to open source software projects (Hars and Ou, 2002), bloggers (Lu and Hsiao, 2009), citizen journalists (Bowman and Willis, 2003), and participants in firm–hosted user communities (Jeppesen and Frederiksen, 2006). In the latter case, however, recognition from the firm is more important to participants than is recognition from the user community, suggesting that the scope of the recognition (wider versus in a more narrow user community) and/or the perceived status of those offering the recognition (the professional/business community or other general users) was important in determining the value of recognition/reputation rewards. Cases in which reputation enhancement acts as a motivator for UGC production tend to be limited to types of UGC in which productions are individual rather than contributions to a whole (e.g., a video uploaded to a sharing site rather than a tag contributed to a database of tags) and productions can be and are attributed to specific producers (e.g., images (Brabham, 2008; Malinen, 2010), product ideas (Brabham, 2010), or news stories (Bowman and Willis, 2003)). By contrast, these motivations are rarely identified for unattributed collaborative productions (e.g., Wikipedia; but see Anthony, et al., 2009, for an alternative perspective). One exception appears to be open source software: a number of studies have identified reputation enhancement as a motivation for contribution to these endeavours (e.g., Allyn and Misra, 2009; Hars and Ou, 2002). This may be related to the development of semi–formal ‘meritocracies’ in open source software projects (rewarding both effort and skill; Allyn and Misra, 2009) and the potential for unpaid contributions to enhance the professional reputation of a programmer within a relatively small community of participating professionals (Bitzer and Geishecker, 2010). In many other studies of UGC, reputation enhancement is at best a negligible predictor of contribution (e.g., Stoeckl, et al., 2007; Cho, et al., 2010), and contributors tend to endorse other motivations over the goal of enhancing their personal or professional reputations.

Social motivations are very commonly identified as a motive for UGC creation. Creators are not generally motivated by a sense of responsibility that they ‘should’ produce content (Daugherty, et al., 2008), nor are they motivated by a desire to ‘fit in’, or conform to the standards and expectations of some external reference group (Yang and Lai, 2011; Daugherty, et al., 2008). Instead, UGC creators gain a deep satisfaction from contributing their knowledge and expertise to a larger community. This sense is expressed by contributors to open source software projects (Baytiyeh and Pfaffman, 2010a; Cho, et al., 2010; Wu, et al., 2007), those who contribute to online knowledge repositories (e.g., Wikipedia, Baytiyeh and Pfaffman, 2010b; a database about local cycling paths, Panciera, et al., 2011; tagging of photos for organization and retrieval, Ames and Naaman, 2007), contributors to crowdsourcing applications (Brabham, 2010), and webloggers (Kjellberg, 2010; Stoeckl, et al., 2007). UGC producers are also motivated by a sense of connection to the community (separate from the pleasure they take in contribution, which may actually related to their self–images as described below). Researchers who blog, for example, note that they feel more connected to others in their research community through the process of blogging (Kjellberg, 2010), and other bloggers indicate that connecting with friends and acquaintances (Liao, et al., 2011; Lu and Hsiao, 2009). In some cases, producers identify a sense of commitment to the community (Anthony, et al., 2009), and greater participation tends to be associated with a strong sense of commitment and social connection (e.g., Chen, 2011).

Another commonly cited motivation is self–image (or internal self–concept), including the desire to feel a sense of belonging and minimize self–doubts (Daugherty, et al., 2008; Zwick, et al., 2008). When UGC production is central to one’s ego, contribution is more likely (Park, et al., 2011). Wikipedia contributors, for example, are more likely than non–contributors to identify their ‘real me’ as being located on the Internet, suggesting that online participation may be central to their self–image (Amichai–Hamburger, et al., 2008). Yang and Lai (2011) demonstrated the enhancement of self–image is a significant motivator for Wikipedia contributors, who value the opportunity to enhance their sense of self–efficacy by publicly demonstrating their knowledge and expertise in Wikipedia postings. It is not surprising, therefore, that ‘reverts’ (which undo earlier changes) are powerfully demotivating for new editors, since they suggest to a UGC producer that their contributions are not valued by the community (Halfaker, et al., 2011). Among contributors to open source software projects, contribution is influenced by personal identification as a contributor (Hertel, et al., 2003).

For some UGC producers, the motivation is the immediate benefit they experience from carrying out the activity. Among open source software contributors, for example, learning is an important motivation (Baytihey and Pfaffman, 2010a), and UGC producers participating in crowdsourcing applications welcome the opportunity to develop their creative skills (Brabham, 2010). Improved functionality is another personal benefit, and those who contribute to tagging identify this as one of the motivations for participation (Ames and Naaman, 2007; van Velsen and Melenhorst, 2009).

Producers of user–generated content are clearly motivated by a variety of different factors, both intrinsic and extrinsic. If we want to create an environment conducive to the production of this content, we need to attend to both types of motivations with an eye to developing a synergistic relationship between them (Amabile, 1993; Krishnamurthy, 2006). Ignoring one form of motivation in favour of the other is likely to be ineffective in promoting user–generated production (Krishnamurthy, 2006). Instead, a dual focus should be maintained on: 1) tools and environments that promote the fun and creativity of user–generated production; and, 2) extrinsic motivators such as reputational enhancement and financial rewards that allow users to maintain a sense of autonomy with respect to the task.



Creator support and quality control

Because so much of UGC is created and consumed within social networks, network members play crucial roles in both supporting content creation and in ensuring content quality. The large pool of contributors helps ensure the quality of open source software and the accuracy of editorial content in Wikipedia (Benkler, 2002). Open source software projects perform according to Linus’ Law, “given enough eyeballs, all bugs are shallow” (Raymond, 2000). Although open content creation models can produce new collaborative and communal notions of authorship (Hunter, 2011), collaboration can also be disrupted.

In order to encourage participation, collaborative systems and large open fora attempt to minimize barriers and maximize privileges. As a result, the model is vulnerable to users with a variety of motivations, including fakers (Wilson, 2011), trolls (Shachaf and Hara, 2010), and spammers (West, et al., 2011). While some of these creators find pleasure in playful, performative modes of communication, others have the goal of damaging the community. UGC quality therefore “varies drastically from excellent to abuse and spam” [6]. In several well–publicized instances, Wikipedia has been manipulated for partisan political purposes (Maxwell, 2006; BBC News, 2009; CBC News, 2010) and sites have been developed that document erroneous articles and incidents of plagiarism (Wiki–Watch, n.d.). These problems are not limited to large–scale collaborative endeavours. Twitter, for example, also has information integrity issues (Murthy, 2011) that disproportionately affect marginalized and vulnerable populations.

In many collaborative projects, veteran members act as gatekeepers. Senior programmers decide which code will be added to the authorized version of the program (von Hippel and von Krogh, 2003; Maxwell, 2006) and groups of senior Wikipedia editors make article inclusion, deletion, and editing decisions (Taraborelli and Ciampaglia, 2011; He, 2011; Laniado and Tasso, 2011; Geiger and Ford, 2011; Ransbotham and Kane, 2011). Despite the volume of content and the number of revisions, most articles actually reflect the work of a relatively small group of well–connected contributors rather than the collaborative efforts of the community (OECD, 2007; Kimmons, 2011). Such well–connected editors are able to gain the support of other influential groups and therefore be more likely to be elected as administrators (Cabunducan, et al., 2011).

Although the diversity of members’ knowledge contributes to the quality of content and communication norms are designed to foster supportive collaboration, there is a complex layering of debates and discussion between Wikipedia editors (Ashton, 2011), and bitter disputes are common (Reagle, 2010). Wikipedia contributors often perceive administrative processes as bureaucratic and burdensome (Arazy, et al., 2011; Müller–Seitz and Reger, 2010). Matei and Dobrescu (2011) argue that a policy advocating a “neutral point of view” is fundamentally ambiguous.

These authorship patterns have implications for participation and comprehensiveness. Antin, et al. (2011) and Lam, et al. (2011) report large gender gaps among Wikipedia editors and corresponding disparities in the content of articles. While Wikipedia contains extremely detailed articles on Madonna, Star Wars and Pokemon, subjects including African and Middle East history are noticeably less thorough (Lih, 2009). Sundin (2011) and Luyt (2011) argue the achievement of diversity is fraught with difficulty. Restatements of the status quo and stabilization of already published knowledge are likely.

Members of creator or user communities may create an additional level of quality control once content has been distributed, in the form of tags or reviews. Tags enable users to organize content around specific themes or events (Small, 2011) and facilitate retrieval by themselves or by others (Thom–Santelli, et al., 2008; Ames and Naaman, 2007; Nov, et al., 2008; van Velsen and Melenhorst, 2009).

Commercial producers of content, hardware, and software platforms may promote the development of UGC for its ability to enhance the experience of large numbers of users and to foster a sense of identity within the user community. At the same time, however, they also have a vested interest in ensuring that UGC reflects well on the original content or platform. They may also wish to retain their ability to profit from re–use of proprietary content.

The producers of games such as Unreal Tournament 2004 (Epic Games, 2004; Nieborg and van der Graaf, 2008; Nieborg, 2005) and World of Warcraft (Scacchi, 2010) have provided editors and toolkits that enable players to design parts of the game world, including new objects and levels, and customize the user interface. Inhabitants of the virtual world Second Life have access to flexible building tools that can be resized, reshaped, modified, combined, and connected (Lo, 2008; White, 2008), and to an interface that allows residents to create small programs (Ludlow and Wallace, 2007).

Some creations involve the repurposing of preexisting creative materials. Mashups and remixes are among the most important kinds of UGC. In 1997, a team of unpaid programmers began developing Alien Quake, a planned mod of the game Quake where environments and monsters from the Alien movie franchise would replace those in the original game. 20th Century Fox demanded complete destruction of this work because of the use of the Alien brand (Baldrica, 2007). Modders use the term “foxed” for situations when their creation is limited by heavy–handed tactics from large companies (Baldrica, 2007). As McNally, et al. (2012) observe, these forms of UGC are particularly challenging for policy–makers as they involve balancing the rights of the original creators against those of UGC creators.

In addition to limiting access to development tools to registered users, corporate creators may use other means to retain control over the quality and appropriateness of any user–generated content. In some cases, user agreements explicitly prevent UGC (Burri–Nenova, 2010). Second Life’s Terms of Service allow users to retain intellectual property rights over their creations (Lo, 2008) but reserve the right to use, reproduce, and delete content (Halbert, 2009).

Mobile device producers have likewise taken a variety of approaches to providing technological support for and control over user–created applications. The Software Development Kit (SDK) for the open source Android mobile operating system is free to download from the Android developer Web site. The site also contains many corporate and user–produced app development resources including developer videos and blogs. However, Android limits content creators’ access to markets. Creators of Android apps must pay a fee to load their creation onto the Android market.

Access to iPhone development tools is limited to registered developers. For an annual fee, developers are given access to the standard development kit, development tools and resources, technical support including access to the Apple developer site, the ability to test and debug code on an iPhone, and ultimate distribution of an approved application through the App store (Dudney and Adamson, 2009; Zdziarski, 2008; Woolridge and Schneider, 2010; Mark and LaMarche, 2009). iPhone/iPod/iPad apps must undergo an extensive approval process before they may be made available on the App Store.



Value creation

UGC creates cultural, symbolic, and affective benefit including personal satisfaction, enhanced skill or reputation, improved functionality for existing games or devices, community building or civic engagement. The collaborative construction of new media products is linked with more than the creation of economic value; it is argued to be inextricably linked with civic engagement (Harrison and Barthel, 2009). In many cases, content creators are aware of the value they create for others and are sophisticated practitioners participating in the network of production (Banks and Humphreys, 2008).

Economic value in UGC is increasingly cocreated by the company and the consumer (Banks and Potts, 2010). The rise of UGC has prompted the development of new financial models from both aggregators and content creators. OECD (2007) identified five models: voluntary donations, charging users for services (pay–per or subscription–based), licensing of content/technology to third parties, and advertising and selling related goods and services to the increasingly large UGC user communities.

All stages of the value chain are open for monetization. For example, the increase in UGC creates new demand for the tools of production, calling for innovation in socio–technical affordances, including functionality and architectural choices, customization and tailoring mechanisms, hardware, software and access to pre–existing proprietary content (Dörner, et al., 2009; Scacchi, 2010; Obrist, et al., 2008).

The expertise of the creator community itself may be monetized. InnoCentive ( aggregates problems in need of UGC solutions. Companies post scientific challenges on the site, inviting anyone in the Innocentive “community” to identify solutions, paying between US$10,000 and US$100,000 to the successful solver.

According to Bear Stearns (2006), a major source of value in UGC lies in packaging, aggregation, and distribution of content. Until recently, hosting sites were primarily non–commercial ventures or were start–ups with non–existent or low revenues and direct monetary compensation for content creators was rare (OECD, 2007; Cova and Dalli, 2009). Currently, YouTube is representative of hosting sites that have generated commercial value. In 2011, YouTube (2011) announced that it monetized three billion video views weekly, and that its number of advertisers had increased tenfold in a year.

Finally, content itself or ancillary products or services may be sold for financial gain. For example, although open source software is often distributed without cost, organizations can offer technical support, service, and customization (Tapscott and Williams, 2008; Weber, 2004) or bundle OSS with proprietary software (Dahlander and Magnusson, 2006). Open source products may also be given away by producers for the purposes of generating demand or eroding the position of an established market leader (Weber, 2004).




The creation and distribution models of user–generated online content sit uncomfortably with understandings and theories of work and leisure created for the physical world (Banks and Deuze, 2009; Sotamaa, 2007). Tensions between ethical and economic models of production and definitions of value relating both to social impact and to monetary accumulation destabilize many taken–for–granted ways of working and playing (Arvidsson, 2008). The importance of non–market motivations may lead to tensions over achieving economic sustainability without sacrificing non–market ideals (Chege, 2008). The collective ethic of content creators embraces unpaid rather than paid labor and offering products at no cost (Ritzer and Jurgenson, 2010). As a result, the very mechanisms that allow for creator freedom also offer avenues for entrapping the user to produce for the firm (Petersen, 2008; Zwick, et al., 2008; van Dijck and Nieborg, 2009), and leisure and social activities may be mobilized for corporate gains (Martens, 2011a; 2011b; Fortunati, 2011). At the same time, the labour of waged digital workers may be devalued, rendering their status all the more precarious (Fuchs, 2009; Banks and Humphreys, 2008; Gill and Pratt, 2008).

Not surprisingly, the destabilization of producer/consumer, labour/leisure, and economic/social value has led many to conclude that the policy infrastructure developed for a traditional market model is ineffective in a UGC model. UGC forces redefinitions of what content is, and who produces, owns, and has access to it (Grimes, 2006; Humphreys, 2009), who is liable for damage (Valcke and Lenaerts, 2010), and what constitutes fair use (Collins, 2010). It has a profound and sometimes disruptive impact on matters relating to regulation, governance and culture, and requires an expansion of what democracy means and entails in the digital networked environment (Dizon, 2010).

Understanding the current state of user–generated content is a necessary prerequisite for adapting traditional policy conceptions to fit the new realities. This paper has provided the background and context of the current state of user–generated content. Our companion article (McNally, et al., 2012) builds on this base by examining the policy dimensions of user–generated content (UGC). We argue for the creation of policy that balances creator and end users rights and allows for the flourishing of UGC production and distribution. End of article


About the authors

Pam McKenzie and Jacquelyn Burkell are Associate Professors in the Faculty of Information and Media Studies, at the University of Western Ontario in London, Ontario. Sam Trosow is an Associate Professor in the Faculty of Information and Media Studies and the Faculty of Law, at the University of Western Ontario. Lola Wong, Caroline Whippey, and Michael McNally are Ph.D. students in the Faculty of Information and Media Studies at the University of Western Ontario.
Corresponding author e–mail: pam [dot] mckenzie [at] uwo [dot] ca



This research was funded by a Social Science and Humanities Research Council of Canada Knowledge Synthesis Grant on the Digital Economy.



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Editorial history

Received 8 January 2012; revised 22 May 2012; accepted 26 May 2012.

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User–generated online content 1: Overview, current state and context
by Pamela J. McKenzie, Jacquelyn Burkell, Lola Wong, Caroline Whippey, Samuel E. Trosow, and Michael McNally
First Monday, Volume 17, Number 6 - 4 June 2012