Characterizing User Behavior in Online Social Networks
Characterizing User Behavior in Online Social Networks Fabrício Benevenutoy Tiago Rodriguesy Meeyoung Cha∗ Virgílio Almeiday yComputer Science Department, Federal University of Minas Gerais, Brazil ∗Max Planck Institute for Software Systems (MPI-SWS), Kaiserslautern/Saarbrücken, Germany ABSTRACT General Terms Understanding how users behave when they connect to social Human Factors, Measurement networking sites creates opportunities for better interface design, richer studies of social interactions, and improved Keywords design of content distribution systems. In this paper, we present a first of a kind analysis of user workloads in on- Online social networks, user behavior, session, clickstream, line social networks. Our study is based on detailed click- social network aggregator, browsing, silent activity stream data, collected over a 12-day period, summarizing HTTP sessions of 37,024 users who accessed four popular 1. INTRODUCTION social networks: Orkut, MySpace, Hi5, and LinkedIn. The Online social networks (OSNs) have become extremely data were collected from a social network aggregator web- popular. According to Nielsen Online's latest research [23], site in Brazil, which enables users to connect to multiple social media have pulled ahead of email as the most popu- social networks with a single authentication. Our analysis lar online activity. More than two-thirds of the global on- of the clickstream data reveals key features of the social net- line population visit and participate in social networks and work workloads, such as how frequently people connect to blogs. In fact, social networking and blogging account for social networks and for how long, as well as the types and nearly 10% of all time spent on the Internet.
[Show full text]