Topic Detection and Tracking: Event-Based Information Organization
Topic Detection and Tracking: Event-Based Information Organization
Reductions in streaming algorithms, with an application to counting triangles in graphs
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
ThemeRiver: Visualizing Theme Changes over Time
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
prefuse: a toolkit for interactive information visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Counting triangles in data streams
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
SybilGuard: defending against sybil attacks via social networks
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Maximizing influence in a competitive social network: a follower's perspective
Proceedings of the ninth international conference on Electronic commerce
Introduction to Information Retrieval
Introduction to Information Retrieval
Efficient semi-streaming algorithms for local triangle counting in massive graphs
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Fast Counting of Triangles in Large Real Networks without Counting: Algorithms and Laws
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
DOULION: counting triangles in massive graphs with a coin
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Finding the frequent items in streams of data
Communications of the ACM - A View of Parallel Computing
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Randomization tests for distinguishing social influence and homophily effects
Proceedings of the 19th international conference on World wide web
Measurement-calibrated graph models for social network experiments
Proceedings of the 19th international conference on World wide web
Competitive influence maximization in social networks
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
An analysis of social network-based Sybil defenses
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
Limiting the spread of misinformation in social networks
Proceedings of the 20th international conference on World wide web
Proceedings of the 20th international conference on World wide web
Where the blogs tip: connectors, mavens, salesmen and translators of the blogosphere
Proceedings of the First Workshop on Social Media Analytics
New streaming algorithms for counting triangles in graphs
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Data-driven modeling and analysis of online social networks
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Information diffusion in social networks: observing and affecting what society cares about
Proceedings of the 20th ACM international conference on Information and knowledge management
See what's enBlogue: real-time emergent topic identification in social media
Proceedings of the 15th International Conference on Extending Database Technology
Identifying event-related bursts via social media activities
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Towards Topic Trend Prediction on a Topic Evolution Model with Social Connection
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Partitioning and ranking tagged data sources
Proceedings of the VLDB Endowment
Predicting trends in social networks via dynamic activeness model
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Traveling trends: social butterflies or frequent fliers?
Proceedings of the first ACM conference on Online social networks
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The identification of popular and important topics discussed in social networks is crucial for a better understanding of societal concerns. It is also useful for users to stay on top of trends without having to sift through vast amounts of shared information. Trend detection methods introduced so far have not used the network topology and has thus not been able to distinguish viral topics from topics that are diffused mostly through the news media. To address this gap, we propose two novel structural trend definitions we call coordinated and uncoordinated trends that use friendship information to identify topics that are discussed among clustered and distributed users respectively. Our analyses and experiments show that structural trends are significantly different from traditional trends and provide new insights into the way people share information online. We also propose a sampling technique for structural trend detection and prove that the solution yields in a gain in efficiency and is within an acceptable error bound. Experiments performed on a Twitter data set of 41.7 million nodes and 417 million posts show that even with a sampling rate of 0.005, the average precision is 0.93 for coordinated trends and 1 for uncoordinated trends.