23,088 research outputs found

    Online Popularity and Topical Interests through the Lens of Instagram

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    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 gathering hundred millions users. Instagram exhibits a mixture of features including social structure, social tagging and media sharing. The network of social interactions among users models various dynamics including follower/followee relations and users' communication by means of posts/comments. Users can upload and tag media such as photos and pictures, and they can "like" and comment each piece of information on the platform. In this work we investigate three major aspects on our Instagram dataset: (i) the structural characteristics of its network of heterogeneous interactions, to unveil the emergence of self organization and topically-induced community structure; (ii) the dynamics of content production and consumption, to understand how global trends and popular users emerge; (iii) the behavior of users labeling media with tags, to determine how they devote their attention and to explore the variety of their topical interests. Our analysis provides clues to understand human behavior dynamics on socio-technical systems, specifically users and content popularity, the mechanisms of users' interactions in online environments and how collective trends emerge from individuals' topical interests.Comment: 11 pages, 11 figures, Proceedings of ACM Hypertext 201

    The Metabolism and Growth of Web Forums

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    We view web forums as virtual living organisms feeding on user's attention and investigate how these organisms grow at the expense of collective attention. We find that the "body mass" (PVPV) and "energy consumption" (UVUV) of the studied forums exhibits the allometric growth property, i.e., PVtUVtθPV_t \sim UV_t ^ \theta. This implies that within a forum, the network transporting attention flow between threads has a structure invariant of time, despite of the continuously changing of the nodes (threads) and edges (clickstreams). The observed time-invariant topology allows us to explain the dynamics of networks by the behavior of threads. In particular, we describe the clickstream dissipation on threads using the function DiTiγD_i \sim T_i ^ \gamma, in which TiT_i is the clickstreams to node ii and DiD_i is the clickstream dissipated from ii. It turns out that γ\gamma, an indicator for dissipation efficiency, is negatively correlated with θ\theta and 1/γ1/\gamma sets the lower boundary for θ\theta. Our findings have practical consequences. For example, θ\theta can be used as a measure of the "stickiness" of forums, because it quantifies the stable ability of forums to convert UVUV into PVPV, i.e., to remain users "lock-in" the forum. Meanwhile, the correlation between γ\gamma and θ\theta provides a convenient method to evaluate the `stickiness" of forums. Finally, we discuss an optimized "body mass" of forums at around 10510^5 that minimizes γ\gamma and maximizes θ\theta.Comment: 6 figure

    The role of social networks in students’ learning experiences

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    The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly relevant in recent years. This research focuses on analyzing the role that social networks play in students’ learning experiences. The construction of students’ social networks, the evolution of these networks, and their effects on the students’ learning experience in a university environment are examined

    Reason Maintenance - Conceptual Framework

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    This paper describes the conceptual framework for reason maintenance developed as part of WP2

    Evaluating tag-based information access in image collections

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    The availability of social tags has greatly enhanced access to information. Tag clouds have emerged as a new "social" way to find and visualize information, providing both one-click access to information and a snapshot of the "aboutness" of a tagged collection. A range of research projects explored and compared different tag artifacts for information access ranging from regular tag clouds to tag hierarchies. At the same time, there is a lack of user studies that compare the effectiveness of different types of tag-based browsing interfaces from the users point of view. This paper contributes to the research on tag-based information access by presenting a controlled user study that compared three types of tag-based interfaces on two recognized types of search tasks - lookup and exploratory search. Our results demonstrate that tag-based browsing interfaces significantly outperform traditional search interfaces in both performance and user satisfaction. At the same time, the differences between the two types of tag-based browsing interfaces explored in our study are not as clear. Copyright 2012 ACM
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