User-Generated Content

Microsoft Research
IEEE Pervasive Computing (Impact Factor: 1.55). 01/2009; 7(4):10 - 11. DOI: 10.1109/MPRV.2008.85
Source: IEEE Xplore


Pervasive user-generated content takes the traditional idea of user-generated content and expands it off the desktop into our everyday world. The six articles in this special issue give innovative examples of gathering and using such content.

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    • "Consequently those ideas of social ties are directly linked one more time with the ideas of Lévy and also with what Bruns has called 'produsage' – a term that " [...] highlights that within communities, which engage in the collaborative creation and extension of information and knowledge [...] within a wider context of new emerging concepts for describing the social, technological, and economic environment of user-led content c eation... " (Bruns, 2008, : 2). Or what is more commonly called 'Use -Gene ated ontent' – when regular people voluntary contribute with data creation, information and media creation on the Web (Krumm et al., 2008). Other studies were done related to second screen or backchannels (Doughty et al, 2011; ibid, 2012; Finger & de Souza, 2012; Canatta, 2014) and recently the social media co-viewing was investigated in the study of Cohen and Lancaster (2014), that did an exploratory study of co-viewing that suggested that social media co-viewing is able to provide social connection between viewers who watch television in physical solitude Nonetheless, previous studies were not just focused on the web, Information and Communication Technologies or Social Networks, some previous studies, with the booming of the digital TV, were about social TV – systems used to support the construction of virtual communities on TV, similar to the Web (Mantzari, 2008). "
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    ABSTRACT: Since the advent of digital media and the 2.0 environments, the way we watch television and consume audiovisual media has changed. The audience can now be also called users, users who generate content and therefore share experiences online and offline. This has an impact on how the user understands TV content. For instance, the proliferation of user–generated content has made a strong impact on the different spheres of society, as people are able to access online information from anywhere (computers, mobile phones, tablets) and also share, create, contribute or view together new and mass media content. In other words, it has generated a new way of co-viewing. This concept of co-viewing comes after an experiment made with Sesame Street in 1970 whereby it was shown that when children watch television together with adults, their capacity of learning increases. Hence why I found it necessary, in this study, to develop a brief history review of co-viewing. After having examined the concept we also try to apply generate a new definition of co-viewing, what we call co-viewing 2.0. It is done to attach the concept in the actual environment. This intent also includes the use of this concept not just in the scope of children but in general as co-viewing and discussing media content with others can be an enhancing experience in terms of acquiring knowledge at any age.
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    • "Recently, the proliferation of social media (Susarla et al. 2012) and crowdsourcing (engaging online users to work on specific tasks, see Doan et al. 2011) has further changed the IS landscape. There is growing interest in user-generated content (UGC) (Cha et al. 2007, Daugherty et al. 2008, Krumm et al. 2008), defined here as various forms of digital information (e.g., comments, forum posts, tags, product reviews, videos, maps) produced by members of the general public. These are often casual content contributors (i.e., the crowd) rather than employees or others closely associated with an organization. "
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    ABSTRACT: User-generated content (UGC) is becoming a valuable organizational resource, as it is seen in many cases as a way to make more information available for analysis. To make effective use of UGC, it is necessary to understand information quality (IQ) in this setting. Traditional IQ research focuses on corporate data and views users as data consumers. However, as users with varying levels of expertise contribute information in an open setting, current conceptualizations of IQ break down. In particular, the practice of modeling information requirements in terms of fixed classes, such as an Entity-Relationship diagram or relational database tables, unnecessarily restricts the IQ of user-generated data sets. This paper defines crowd information quality (crowd IQ), empirically examines implications of class-based modeling approaches for crowd IQ, and offers a path for improving crowd IQ using instance-and-attribute based modeling. To evaluate the impact of modeling decisions on IQ, we conducted three experiments. Results demonstrate that information accuracy depends on the classes used to model domains, with participants providing more accurate information when classifying phenomena at a more general level. In addition, we found greater overall accuracy when participants could provide freeform data compared to a condition in which they selected from constrained choices. We further demonstrate that, relative to attribute-based data collection, information loss occurs when class-based models are used. Our findings have significant implications for information quality, information modeling, and UGC research and practice.
    Information Systems Research 12/2014; 25(4):669 - 689. DOI:10.1287/isre.2014.0537 · 2.15 Impact Factor
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    • "A growing trend in organizations is to use information produced outside organizational boundaries created by various entities, such as suppliers, business partners, potential customers , and the general public [Zwass 2010, Hand 2010]. A particularly promising source of externally-produced data is user-generated content [Daugherty Eastin et al. 2008, Krumm Davies et al. 2008], defined here as various forms of digital information (e.g., comments, forum posts, tags, product reviews, videos, maps) produced by members of the general public – who often are casual content contributors (the crowd) – rather than by employees or others closely associated with an organization. There is a growing realization that ordinary users can contribute a large volume of meaningful and timely information, support discoveries and insights [Hand 2010]. "
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    ABSTRACT: As more organizations rely on externally-produced information, an important issue is how to create appropriate conceptual models of these domains to effectively guide information systems development. Considering the limitations and consequences of traditional approaches, we propose a " lightweight " modeling alternative to traditional " class-based " conceptual modeling as typified by the Entity Relationship model. We provide proof of concept and empirically evaluate the approach using a real-world crowdsourcing project, NLNature.
    Workshop on Information Technology and Systems (WITS), Milan 2013; 12/2013
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