In recent years we have witnessed a significant growth of social-computing communities—online services in which users share information in various forms. As content contributions from participants are critical to the viability of these communities, it is important to understand what drives users to participate and share information with others in such settings. We extend previous literature on user contribution by studying the factors that are associated with various forms of participation in a large online photo-sharing community. Using survey and system data, we examine four different forms of participation and consider the differences between these forms. We build on theories of motivation to examine the relationship between users' participation and their motivations with respect to their tenure in the community. Amongst our findings, we identify individual motivations (both extrinsic and intrinsic) that underpin user participation, and their effects on different forms of information sharing; we show that tenure in the community does affect participation, but that this effect depends on the type of participation activity. Finally, we demonstrate that tenure in the community has a weak moderating effect on a number of motivations with regard to their effect on participation. Directions for future research, as well as implications for theory and practice, are discussed. © 2010 Wiley Periodicals, Inc.

/pdf/analysis-of-participation-in-an-online-photo-sharing-47nks8o49w.pdf

Analysis of participation in an online photo-sharing community: A multidimensional perspective

Photo sharing sites such as Flickr are commonly regarded either as spaces where communal views and experiences evolve as a result of picture exchange, or as visual archives where sharing pictures in the present naturally leads to a collective interpretation of the past. This article proposes regarding Flickr as a social media platform annex database that enables the construction of infinite connections. Platforms such as Flickr are firmly embedded in a culture of connectivity, a culture where the powerful structures of social networking sites are gradually penetrating the core of our daily routines and practices. What is often called ‘collective memory’ or ‘cultural heritage’ in relation to digital photo sharing sites is largely the result of data linked up by means of computer code and institutional protocols.

/pdf/flickr-and-the-culture-of-connectivity-sharing-views-a896kdx297.pdf

Flickr and the culture of connectivity: Sharing views, experiences, memories

In recent years, various Web-based sharing and community services such as Flickr and YouTube have made a vast and rapidly growing amount of multimedia content available online. Uploaded by individual participants, content in these immense pools of content is accompanied by varied types of metadata, such as social network data or descriptive textual information. These collections present, at once, new challenges and exciting opportunities for multimedia research. This article presents an approach for "social multimedia" applications. The approach is based on the experience of building a number of successful applications that are based on mining multimedia content analysis in social multimedia context.

Social multimedia: highlighting opportunities for search and mining of multimedia data in social media applications

Community-based geoportals: The next generation? Concepts and methods for the geospatial Web 2.0

A method of recommending social group(s) for sharing one or more user images, includes using a processor for acquiring the one or more user images and their associated metadata; acquiring one or more group images from the social group(s) and their associated metadata; computing visual features for the user images and the group images; and recommending social group(s) for the one of more user images using both the visual features and the metadata.

Recommending user image to social network groups

There is an explosion of community-generated multimedia content available online. In particular, Flickr constitutes a 200-million photo sharing system where users participate following a variety of social motivations and themes. Flickr groups are increasingly used to facilitate the explicit definition of communities sharing common interests, which translates into large amounts of content (e.g. pictures and associated tags) about specific subjects. However, to our knowledge, an in-depth analysis of user behavior in Flickr groups remains open, as does the existence of effective tools to find relevant groups. Using a sample of about 7 million user-photos and about 51000 Flickr groups, we present a novel statistical group analysis that highlights relevant patterns of photo-to-group sharing practices. Furthermore, we propose a novel topic-based representation model for groups, computed from aggregated group tags. Groups are represented as multinomial distributions over semantically meaningful latent topics learned via unsupervised probabilistic topic modeling. We show this representation to be useful for automatically discovering groups of groups and topic expert-groups, for designing new group-search strategies, and for obtaining new insights of the semantic structure of Flickr groups.

/pdf/analyzing-flickr-groups-3yk8gxuyy2.pdf

Analyzing Flickr groups

With the increased presence of digital imaging devices there also came an explosion in the amount of multimedia content available online. Users have transformed from passive consumers of media into content creators. Flickr.com is such an example of an online community, with over 2 billion photos (and more recently, videos as well), most of which are publicly available. The user interaction with the system also provides a plethora of metadata associated with this content, and in particular tags. One very important aspect in Flickr is the ability of users to organize in self-managed communities called groups. Although users and groups are conceptually different, in practice they can be represented in the same way: a bag-of-tags, which is amenable for probabilistic topic modeling. We present a topic-based approach to represent Flickr users and groups and demonstrate it with a web application, Topickr, that allows similarity based exploration of Flickr entities using their topic-based representation, learned in an unsupervised manner.

/pdf/topickr-flickr-groups-and-users-reloaded-5a916elgnr.pdf

Topickr: flickr groups and users reloaded

In today's age of digital multimedia deluge, a clear understanding of the dynamics of online communities is capital. Users have abandoned their role of passive consumers and are now the driving force behind large-scale media repositories, whose dynamics and shaping factors are not yet fully understood. In this paper we present a novel human-centered analysis of two major photo sharing websites, Flickr and Kodak Gallery. On a combined dataset of over 5 million tagged photos, we investigate fundamental differences and similarities at the level of tag usage and propose a joint probabilistic topic model to provide further insight into semantic differences between the two communities. Our results show that the effects of the users' motivations and needs can be strongly observed in this large-scale data, in the form of what we call Kodak Moments and Flickr Diamonds. They are an indication that system designers should carefully take into account the target audience and its needs.

/pdf/kodak-moments-and-flickr-diamonds-how-users-shape-large-1gvcst6hde.pdf

Radu Andrei Negoescu

Papers

Analyzing Flickr groups

Topickr: flickr groups and users reloaded

Kodak moments and Flickr diamonds: how users shape large-scale media