Proceedings ArticleDOI
Kodak moments and Flickr diamonds: how users shape large-scale media
Radu Andrei Negoescu,Alexander C. Loui,Daniel Gatica-Perez +2 more
- pp 1027-1030
TLDR
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 is presented and a joint probabilistic topic model is proposed to provide further insight into semantic differences between the two communities.Abstract:
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.read more
Citations
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Proceedings ArticleDOI
Why do we converse on social media?: an analysis of intrinsic and extrinsic network factors
TL;DR: The findings indicate that factors that influence participation depend on the media type: YouTube participation is different from a weblog such as Engadget, and an optimal factor combination improves prediction accuracy of observed participation, by ~9--13% and ~8--11% over using just the best hypothesis and all hypotheses respectively.
Book ChapterDOI
Analyzing the dynamics of communication in online social networks
TL;DR: This dissertation deals with the analysis of interpersonal communication dynamics in online social networks and social media, and it is observed that user context is key to characterizing communication between a pair of individuals, and different modes of social engagement lead to evolution of groups that have considerable predictive capability in characterizing external-world temporal occurrences.
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Understanding and leveraging tag-based relations in on-line social networks
TL;DR: It is shown that different types of relationships require different similarity metrics, which could lead to the construction of better user models and in traditional social network analysis problems (e.g., link prediction).
Modeling and understanding communities in online social media using probabilistic methods
TL;DR: In this article, the authors used large-scale data and probabilistic models in a quantitative approach to model and understand emerging online communities that revolve around multimedia content, more specifically photos, using data from two online photo management systems, and examined different aspects of the behavior of users pertaining to the uploading and sharing of photos with other users and online groups.
References
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Journal ArticleDOI
Latent dirichlet allocation
TL;DR: This work proposes a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hofmann's aspect model.
Proceedings Article
Latent Dirichlet Allocation
TL;DR: This paper proposed a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hof-mann's aspect model, also known as probabilistic latent semantic indexing (pLSI).
Journal ArticleDOI
Finding scientific topics
TL;DR: A generative model for documents is described, introduced by Blei, Ng, and Jordan, and a Markov chain Monte Carlo algorithm is presented for inference in this model, which is used to analyze abstracts from PNAS by using Bayesian model selection to establish the number of topics.
Proceedings ArticleDOI
Measurement and analysis of online social networks
TL;DR: This paper examines data gathered from four popular online social networks: Flickr, YouTube, LiveJournal, and Orkut, and reports that the indegree of user nodes tends to match the outdegree; the networks contain a densely connected core of high-degree nodes; and that this core links small groups of strongly clustered, low-degree node at the fringes of the network.
Proceedings ArticleDOI
Why we tag: motivations for annotation in mobile and online media
Morgan G. Ames,Mor Naaman +1 more
TL;DR: The incentives for annotation in Flickr, a popular web-based photo-sharing system, and ZoneTag, a cameraphone photo capture and annotation tool that uploads images to Flickr are investigated to offer a taxonomy of motivations for annotation along two dimensions (sociality and function).