Related papers: Collaborative Tagging and Semiotic Dynamics
Online socio-technical systems can be studied as proxy of the real world to investigate human behavior and social interactions at scale. Here we focus on Instagram, a media-sharing online platform whose popularity has been rising up to…
Social bookmarking and tagging has emerged a new era in user collaboration. Collaborative Tagging allows users to annotate content of their liking, which via the appropriate algorithms can render useful for the provision of product…
In this work we present an in-depth analysis of the user behaviors on different Social Sharing systems. We consider three popular platforms, Flickr, Delicious and StumbleUpon, and, by combining techniques from social network analysis with…
Tagging facilitates information retrieval in social media and other online communities by allowing users to organize and describe online content. Researchers found that the efficiency of tagging systems steadily decreases over time, because…
A main characteristic of social media is that its diverse content, copiously generated by both standard outlets and general users, constantly competes for the scarce attention of large audiences. Out of this flood of information some topics…
We describe a general stochastic processes-based approach to modeling user-contributory web sites, where users create, rate and share content. These models describe aggregate measures of activity and how they arise from simple models of…
Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through…
Collaborative recommendation is an information-filtering technique that attempts to present information items that are likely of interest to an Internet user. Traditionally, collaborative systems deal with situations with two types of…
Large-scale data resulting from users online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms…
Online communications, and in particular social media, are a key component of how society interacts with and promotes content online. Collective attention on such content can vary wildly. The majority of breaking topics quickly fade into…
One potential disadvantage of social tagging systems is that due to the lack of a centralized vocabulary, a crowd of users may never manage to reach a consensus on the description of resources (e.g., books, users or songs) on the Web. Yet,…
Recently, collaborative tagging systems have attracted more and more attention and have been widely applied in web systems. Tags provide highly abstracted information about personal preferences and item content, and are therefore potential…
Automatically understanding the contents of an image is a highly relevant problem in practice. In e-commerce and social media settings, for example, a common problem is to automatically categorize user-provided pictures. Nowadays, a…
Social tagging systems have recently developed as a popular method of data organisation on the Internet. These systems allow users to organise their content in a way that makes sense to them, rather than forcing them to use a pre-determined…
Online social media provide multiple ways to find interesting content. One important method is highlighting content recommended by user's friends. We examine this process on one such site, the news aggregator Digg. With a stochastic model…
Modern social platforms are characterized by the presence of rich user-behavior data associated with the publication, sharing and consumption of textual content. Users interact with content and with each other in a complex and dynamic…
Recommendation systems and content filtering approaches based on annotations and ratings, essentially rely on users expressing their preferences and interests through their actions, in order to provide personalised content. This activity,…
In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify…
We propose a stochastic model of web user behaviors in online social systems, and study the influence of attraction kernel on statistical property of user or item occurrence. Combining the different growth patterns of new entities and…
Most tagging systems support the user in the tag selection process by providing tag suggestions, or recommendations, based on a popularity measurement of tags other users provided when tagging the same resource. In this paper we investigate…