News Posting by Strategic Users in a Social Network

Authors:
Mangesh Gupte;Mohammadtaghi Hajiaghayi;Lu Han;Liviu Iftode;Pravin Shankar;Raluca M. Ursu
Affiliations:
Department of Computer Science, Rutgers University, Piscataway 08854;AT&T Labs --- Research, Florham Park 07932;Department of Computer Science, Rutgers University, Piscataway 08854;Department of Computer Science, Rutgers University, Piscataway 08854;Department of Computer Science, Rutgers University, Piscataway 08854;Mount Holyoke College, South Hadley 01075
Venue:
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Year:
2009

Citing 9
Cited 1

Mining the network value of customers

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Mining knowledge-sharing sites for viral marketing

Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network

Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Graphs over time: densification laws, shrinking diameters and possible explanations

Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Scalable modeling of real graphs using Kronecker multiplication

Proceedings of the 24th international conference on Machine learning
Meme-tracking and the dynamics of the news cycle

Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Stochastic Kronecker graphs

WAW'07 Proceedings of the 5th international conference on Algorithms and models for the web-graph
A critical point for random graphs with a given degree sequence

Random Structures & Algorithms
Patterns of influence in a recommendation network

PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining

All the news that's fit to read: finding and recommending news online

INTERACT'11 Proceedings of the 13th IFIP TC 13 international conference on Human-computer interaction - Volume Part III

Quantified Score

Hi-index	0.00

Visualization

Abstract

We argue that users in social networks are strategic in how they post and propagate information. We propose two models -- greedy and courteous -- and study information propagation both analytically and through simulations. For a suitable random graph model of a social network, we prove that news propagation follows a threshold phenomenon, hence, "high-quality" information provably spreads throughout the network assuming users are "greedy". Starting from a sample of the Twitter graph, we show through simulations that the threshold phenomenon is exhibited by both the greedy and courteous user models.