ACM Computing Surveys (CSUR)
X-means: Extending K-means with Efficient Estimation of the Number of Clusters
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Modeling the Clickstream: Implications for Web-Based Advertising Efforts
Marketing Science
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
The dynamics of viral marketing
ACM Transactions on the Web (TWEB)
Analysis of topological characteristics of huge online social networking services
Proceedings of the 16th international conference on World Wide Web
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Looking at, looking up or keeping up with people?: motives and use of facebook
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
International ethnographic observation of social networking sites
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Comparison of online social relations in volume vs interaction: a case study of cyworld
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
Predicting tie strength with social media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Feed me: motivating newcomer contribution in social network sites
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User interactions in social networks and their implications
Proceedings of the 4th ACM European conference on Computer systems
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
Analyzing patterns of user content generation in online social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting spammers and content promoters in online video social networks
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Beyond friendship graphs: a study of user interactions in Flickr
Proceedings of the 2nd ACM workshop on Online social networks
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
Video interactions in online video social networks
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Understanding online social network usage from a network perspective
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Characterizing user behavior in online social networks
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
The SocialTrust framework for trusted social information management: Architecture and algorithms
Information Sciences: an International Journal
A measure of online social networks
COMSNETS'09 Proceedings of the First international conference on COMmunication Systems And NETworks
Social network activity and social well-being
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
The little engine(s) that could: scaling online social networks
Proceedings of the ACM SIGCOMM 2010 conference
@spam: the underground on 140 characters or less
Proceedings of the 17th ACM conference on Computer and communications security
Detecting and characterizing social spam campaigns
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Understanding latent interactions in online social networks
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Exploiting locality of interest in online social networks
Proceedings of the 6th International COnference
Proceedings of the 20th international conference on World wide web
On word-of-mouth based discovery of the web
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Tips, dones and todos: uncovering user profiles in foursquare
Proceedings of the fifth ACM international conference on Web search and data mining
Discovering influencers for marketing in the blogosphere
Information Sciences: an International Journal
A workload characterization study of the 1998 World Cup Web site
IEEE Network: The Magazine of Global Internetworking
A significance-driven framework for characterizing and finding evolving patterns of news networks
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
International Journal of Organizational and Collective Intelligence
Computers in Human Behavior
Discovering content-based behavioral roles in social networks
Decision Support Systems
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Understanding how users navigate and interact when they connect to social networking sites creates opportunities for better interface design, richer studies of social interactions, and improved design of content distribution systems. In this paper, we present an in-depth analysis of user workloads in online social networks. This study is based on detailed clickstream data, collected over a 12-day period, summarizing HTTP sessions of 37,024 users who accessed four popular social networks: Orkut, MySpace, Hi5, and LinkedIn. The data were collected from a social network aggregator website in Brazil, which enables users to connect to multiple social networks with a single authentication. Our analysis of the clickstream data reveals key features of the social network workloads, such as how frequently people connect to social networks and for how long, as well as the types and sequences of activities that users conduct on these sites. Additionally, we gather the social network topology of Orkut, so that we could analyze user interaction data in light of the social graph. Our data analysis suggests insights into how users interact with friends in Orkut, such as how frequently users visit their friends' and non-immediate friends' pages. Results show that browsing, which cannot be inferred from crawling publicly available data, accounts for 92% of all user activities. Consequently, compared to using only crawled data, silent interactions like browsing friends' pages increase the measured level of interaction among users. Additionally, we find that friends requesting content are often within close geographical proximity of the uploader. We also discuss a series of implications of our findings for efficient system and interface design as well as for advertisement placement in online social networks.