Proceedings Article•
Social Browsing on Flickr
07 Dec 2006-
TL;DR: Through an extensive analysis of Flickr data, it is shown that social browsing through the contacts' photo streams is one of the primary methods by which users find new images on Flickr.
Abstract: The new social media sites—blogs, wikis, del.icio.us and Flickr, among others—underscore the transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. The photo-sharing site Flickr, for example, allows users to upload photographs, view photos created by others, comment on those photos, etc. As is common to other social media sites, Flickr allows users to designate others as "contacts" and to track their activ- ities in real time. The contacts (or friends) lists form the social network backbone of social media sites. These social networks facilitate new ways of interacting with information, e.g., through what we call social browsing. The contacts inter- face on Flickr enables users to see latest images submitted by their friends. Through an extensive analysis of Flickr data, we show that social browsing through the contacts' photo streams is one of the primary methods by which users find new images on Flickr. This finding has implications for creat- ing personalized recommendation systems based on the user's declared contacts lists.
Citations
More filters
21 Apr 2008
TL;DR: This paper analyzes a representative snapshot of Flickr and presents and evaluates tag recommendation strategies to support the user in the photo annotation task by recommending a set of tags that can be added to the photo.
Abstract: Online photo services such as Flickr and Zooomr allow users to share their photos with family, friends, and the online community at large. An important facet of these services is that users manually annotate their photos using so called tags, which describe the contents of the photo or provide additional contextual and semantical information. In this paper we investigate how we can assist users in the tagging phase. The contribution of our research is twofold. We analyse a representative snapshot of Flickr and present the results by means of a tag characterisation focussing on how users tags photos and what information is contained in the tagging. Based on this analysis, we present and evaluate tag recommendation strategies to support the user in the photo annotation task by recommending a set of tags that can be added to the photo. The results of the empirical evaluation show that we can effectively recommend relevant tags for a variety of photos with different levels of exhaustiveness of original tagging.
1,048 citations
Cites background from "Social Browsing on Flickr"
...There it is concluded that users are highly driven by social incentives....
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20 Apr 2009
TL;DR: This work uses the spatial distribution of where people take photos to define a relational structure between the photos that are taken at popular places, and finds that visual and temporal features improve the ability to estimate the location of a photo, compared to using just textual features.
Abstract: We investigate how to organize a large collection of geotagged photos, working with a dataset of about 35 million images collected from Flickr. Our approach combines content analysis based on text tags and image data with structural analysis based on geospatial data. We use the spatial distribution of where people take photos to define a relational structure between the photos that are taken at popular places. We then study the interplay between this structure and the content, using classification methods for predicting such locations from visual, textual and temporal features of the photos. We find that visual and temporal features improve the ability to estimate the location of a photo, compared to using just textual features. We illustrate using these techniques to organize a large photo collection, while also revealing various interesting properties about popular cities and landmarks at a global scale.
861 citations
Cites background from "Social Browsing on Flickr"
..., [7, 12, 14, 15, 24]), or on content, such as studies of image tagging (e....
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20 Apr 2009
TL;DR: Analysis of large-scale traces of information dissemination in the Flickr social network finds that even popular photos do not spread widely throughout the network, and the role of word-of-mouth exchanges between friends in the overall propagation of information in the network is questioned.
Abstract: Online social networking sites like MySpace, Facebook, and Flickr have become a popular way to share and disseminate content. Their massive popularity has led to viral marketing techniques that attempt to spread content, products, and ideas on these sites. However, there is little data publicly available on viral propagation in the real world and few studies have characterized how information spreads over current online social networks.In this paper, we collect and analyze large-scale traces of information dissemination in the Flickr social network. Our analysis, based on crawls of the favorite markings of 2.5 million users on 11 million photos, aims at answering three key questions: (a) how widely does information propagate in the social network? (b) how quickly does information propagate? and (c) what is the role of word-of-mouth exchanges between friends in the overall propagation of information in the network? Contrary to viral marketing ``intuition,'' we find that (a) even popular photos do not spread widely throughout the network, (b) even popular photos spread slowly through the network, and (c) information exchanged between friends is likely to account for over 50 of all favorite-markings, but with a significant delay at each hop.
842 citations
Cites result from "Social Browsing on Flickr"
...[14] K. Lerman and L. Jones....
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...The most similar to our work is by Lerman and Jones [14]....
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...The most similar to our work is by Lerman and Jones [14]....
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18 Aug 2008
TL;DR: It is found that links tend to be created by users who already have many links, that users tend to respond to incoming links by creating links back to the source, and that users link to other users who are already close in the network.
Abstract: Online social networking sites like MySpace, Orkut, and Flickr are among the most popular sites on the Web and continue to experience dramatic growth in their user population. The popularity of these sites offers a unique opportunity to study the dynamics of social networks at scale. Having a proper understanding of how online social networks grow can provide insights into the network structure, allow predictions of future growth, and enable simulation of systems on networks of arbitrary size. However, to date, most empirical studies have focused on static network snapshots rather than growth dynamics.In this paper, we collect and examine detailed growth data from the Flickr online social network, focusing on the ways in which new links are formed. Our study makes two contributions. First, we collect detailed data covering three months of growth, encompassing 950,143 new users and over 9.7 million new links, and we make this data available to the research community. Second, we use a first-principles approach to investigate the link formation process. In short, we find that links tend to be created by users who already have many links, that users tend to respond to incoming links by creating links back to the source, and that users link to other users who are already close in the network.
439 citations
Cites methods from "Social Browsing on Flickr"
...[11] K. Lerman and L. A. Jones....
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...For example, Lerman and Jones [11] used a small data sample from Flickr and found that the social network is used to locate new content in the site....
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...For example,Lerman andJones[11]used a small data sample from Flickr and found that the social network is used to locate new content in the site....
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TL;DR: This analysis suggests that users with similar interests are more likely to be friends, and therefore topical similarity measures among users based solely on their annotation metadata should be predictive of social links.
Abstract: Social media have attracted considerable attention because their open-ended nature allows users to create lightweight semantic scaffolding to organize and share content. To date, the interplay of the social and topical components of social media has been only partially explored. Here, we study the presence of homophily in three systems that combine tagging social media with online social networks. We find a substantial level of topical similarity among users who are close to each other in the social network. We introduce a null model that preserves user activity while removing local correlations, allowing us to disentangle the actual local similarity between users from statistical effects due to the assortative mixing of user activity and centrality in the social network. This analysis suggests that users with similar interests are more likely to be friends, and therefore topical similarity measures among users based solely on their annotation metadata should be predictive of social links. We test this hypothesis on several datasets, confirming that social networks constructed from topical similarity capture actual friendship accurately. When combined with topological features, topical similarity achieves a link prediction accuracy of about 92p.
390 citations
References
More filters
TL;DR: The combination of high volume and personal taste made Usenet news a promising candidate for collaborative filtering and the potential predictive utility for Usenets news was very high.
Abstract: newsgroups carry a wide enough spread of messages to make most individuals consider Usenet news to be a high noise information resource. Furthermore, each user values a different set of messages. Both taste and prior knowledge are major factors in evaluating news articles. For example, readers of the rec.humor newsgroup, a group designed for jokes and other humorous postings, value articles based on whether they perceive them to be funny. Readers of technical groups, such as comp.lang.c11 value articles based on interest and usefulness to them—introductory questions and answers may be uninteresting to an expert C11 programmer just as debates over subtle and advanced language features may be useless to the novice. The combination of high volume and personal taste made Usenet news a promising candidate for collaborative filtering. More formally, we determined the potential predictive utility for Usenet news was very high. The GroupLens project started in 1992 and completed a pilot study at two sites to establish the feasibility of using collaborative filtering for Usenet news [8]. Several critical design decisions were made as part of that pilot study, including:
2,657 citations
"Social Browsing on Flickr" refers background in this paper
...Collaborative ltering [3] used by many popular commercial recommendation systems attempts to nd users with sim-...
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Posted Content•
TL;DR: A dynamical model of collaborative tagging is presented that predicts regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url.
Abstract: Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge
997 citations
"Social Browsing on Flickr" refers background in this paper
...The emergent social tagging structures on these sites have already attracted the interest of researchers [2, 5]....
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01 Sep 2004
TL;DR: It is posited that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data.
Abstract: Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from such a perspective. This viewpoint is under-emphasized in the recommender systems literature. We therefore take a connection-oriented perspective toward recommender systems research. We posit that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data. Thus, recommender systems are characterized by how they model users to bring people together: explicitly or implicitly. Finally, user modeling and the connection-centric viewpoint raise broadening and social issues—such as evaluation, targeting, and privacy and trust—which we also briefly address.
193 citations
"Social Browsing on Flickr" refers background in this paper
...Researchers have recognized [6] that social networks present in the user base of the recommender systems can be induced from the explicit and implicit declarations of user interest, and that these social...
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Proceedings Article•
07 Dec 2006TL;DR: Digg is a social news aggregator which allows users to submit links to, vote on and discuss news stories as discussed by the authors. And each day Digg selects a handful of stories to feature on its front page.
Abstract: The new social media sites — blogs, wikis, Flickr and Digg, among others — underscore the transformation of the Web to a participatory medium in which users are actively creating, evaluating and distributing information. Digg is a social news aggregator which allows users to submit links to, vote on and discuss news stories. Each day Digg selects a handful of stories to feature on its front page. Rather than rely on the opinion of a few editors, Digg aggregates opinions of thousands of its users to decide which stories to promote to the front page. Digg users can designate other users as “friends” and easily track friends’ activities: what new stories they submitted, commented on or read. The friends interface acts as a social filtering system, recommending to user stories his or her friends liked or found interesting. By tracking the votes received by newly submitted stories over time, we showed that social filtering is an effective information filtering approach. Specifically, we showed that (a) users tend to like stories submitted by friends and (b) users tend to like stories their friends read and liked. Social filtering is a promising new technology that can be used to personalize and tailor information to individual users: for example, through personal front pages.
107 citations