scispace - formally typeset
Proceedings ArticleDOI

Finding Subgroups in a Flickr Group

Reads0
Chats0
TLDR
The proposed probabilistic model employs a more flexible prior distribution to model topic-topic correlations and utilizes both tag and image information for discovering subgroups in a given Flickr Group by discovering latent subgroups.
Abstract
Information management systems today face a tremendous challenge considering the growing popularity of social media repositories involving images and video. Considering the growing volume of multimedia content in such online media-sharing communities there is an increasing need for novel ways of organizing content. In this paper we consider the problem of organizing images in a given Flickr Group by discovering latent subgroups. A Flickr Group can be visualized as a collection of such subgroups where each subgroup represents a distinct theme. We model the task of discovering subgroups as that of finding highly correlated topics from a dataset containing images and associated tags. The proposed probabilistic model employs a more flexible prior distribution to model topic-topic correlations and utilizes both tag and image information for discovering such subgroups. Our experiments on Flickr Group data demonstrate that the model is able to successfully discover subgroups without any supervision.

read more

Citations
More filters
Journal ArticleDOI

Characterization of online groups along space, time, and social dimensions

TL;DR: Results support the intuition that a more nuanced description of groups could improve not only the understanding of the activity of the user base but also the interpretation of other phenomena occurring on social graphs.
Book ChapterDOI

Group Types in Social Media

TL;DR: In this article, the authors survey some techniques that have been used to get a multi-faceted description of group types and show that different types of groups impact on orthogonal interaction processes on the social graph such as the diffusion of information along social ties.

Nature of Social Structures.

TL;DR: Pragmatics is needed to reach a deeper and more reasonable understanding of human language and, in turn, to grasp the fundamental rules governing social interactions.
References
More filters
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).
Proceedings ArticleDOI

A Combined Corner and Edge Detector

TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
Proceedings ArticleDOI

Modeling annotated data

TL;DR: Three hierarchical probabilistic mixture models which aim to describe annotated data with multiple types, culminating in correspondence latent Dirichlet allocation, a latent variable model that is effective at modeling the joint distribution of both types and the conditional distribution of the annotation given the primary type.
Proceedings ArticleDOI

Flickr tag recommendation based on collective knowledge

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.
Related Papers (5)