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Using early view patterns to predict the popularity of youtube videos
TLDR
Predicting Web content popularity is an important task for supporting the design and evaluation of a wide range of systems, from targeted advertising to effective search and recommendation services. Expand
The tube over time: characterizing popularity growth of youtube videos
TLDR
We characterize the growth patterns of video popularity on the currently most popular video sharing application, namely YouTube, and analyze how the popularity of individual videos evolves since the video's upload time. Expand
Detecting Spammers and Content Promoters in Online Video Social Networks
TLDR
A number of online video social networks, out of which YouTube is the most popular, provides features that allow users to post a video as response to a discussion topic. Expand
Identifying user behavior in online social networks
TLDR
We propose a methodology for characterizing and identifying user behaviors in online social networks. Expand
Analyzing client interactivity in streaming media
TLDR
This paper provides an extensive analysis of pre-stored streaming media workloads, focusing on the client interactive behavior. Expand
We know where you live: privacy characterization of foursquare behavior
TLDR
In the last few years, the increasing interest in location-based services (LBS) has favored the introduction of geo-referenced information in various Web 2.0 applications. Expand
Resource Management in the Autonomic Service-Oriented Architecture
TLDR
In service oriented systems, Quality of Service (QoS) is a service selection driver. Expand
Characterizing a spam traffic
TLDR
The rapid increase in the volume of unsolicited commercial e-mails, also known as spam, is beginning to take its toll in system administrators, business corporations and end-users. Expand
Beware of What You Share: Inferring Home Location in Social Networks
TLDR
In this paper, we perform a large-scale inference study in three of the currently most popular social networks: Foursquare, Google+ and Twitter. Expand
Identifying video spammers in online social networks
TLDR
We use machine learning to provide a heuristic for classifying an arbitrary video as either legitimate or spam. Expand
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