The Mathematics of Infectious Diseases
SIAM Review
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Tracking Information Epidemics in Blogspace
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Influence and correlation in social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and 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
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
Proceedings of the 20th international conference on World wide web
Structure and dynamics of information pathways in online media
Proceedings of the sixth ACM international conference on Web search and data mining
Fast structure learning in generalized stochastic processes with latent factors
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting social events for learning better information diffusion models
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering latent influence in online social activities via shared cascade poisson processes
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Cascading outbreak prediction in networks: a data-driven approach
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Social influence based clustering of heterogeneous information networks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining structural hole spanners through information diffusion in social networks
Proceedings of the 22nd international conference on World Wide Web
Detecting epidemics using highly noisy data
Proceedings of the fourteenth ACM international symposium on Mobile ad hoc networking and computing
Finding contexts of social influence in online social networks
Proceedings of the 7th Workshop on Social Network Mining and Analysis
Modeling direct and indirect influence across heterogeneous social networks
Proceedings of the 7th Workshop on Social Network Mining and Analysis
Information diffusion in online social networks: a survey
ACM SIGMOD Record
On popularity prediction of videos shared in online social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Personalized influence maximization on social networks
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Diffusion-aware personalized social update recommendation
Proceedings of the 7th ACM conference on Recommender systems
Are there cultural differences in event driven information propagation over social media?
Proceedings of the 2nd international workshop on Socially-aware multimedia
Buddy2GuessWho: a smartphone application in on-line social network platform
Proceedings of the 2013 Research in Adaptive and Convergent Systems
Characterizing the life cycle of online news stories using social media reactions
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Online egocentric models for citation networks
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Social influence locality for modeling retweeting behaviors
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Modelling growth of urban crowd-sourced information
Proceedings of the 7th ACM international conference on Web search and data mining
Inferring the impacts of social media on crowdfunding
Proceedings of the 7th ACM international conference on Web search and data mining
Modeling opinion dynamics in social networks
Proceedings of the 7th ACM international conference on Web search and data mining
Understanding spatial homophily: the case of peer influence and social selection
Proceedings of the 23rd international conference on World wide web
Proceedings of the 23rd international conference on World wide web
The bursty dynamics of the Twitter information network
Proceedings of the 23rd international conference on World wide web
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Social networks play a fundamental role in the diffusion of information. However, there are two different ways of how information reaches a person in a network. Information reaches us through connections in our social networks, as well as through the influence external out-of-network sources, like the mainstream media. While most present models of information adoption in networks assume information only passes from a node to node via the edges of the underlying network, the recent availability of massive online social media data allows us to study this process in more detail. We present a model in which information can reach a node via the links of the social network or through the influence of external sources. We then develop an efficient model parameter fitting technique and apply the model to the emergence of URL mentions in the Twitter network. Using a complete one month trace of Twitter we study how information reaches the nodes of the network. We quantify the external influences over time and describe how these influences affect the information adoption. We discover that the information tends to "jump" across the network, which can only be explained as an effect of an unobservable external influence on the network. We find that only about 71% of the information volume in Twitter can be attributed to network diffusion, and the remaining 29% is due to external events and factors outside the network.