Back to Search
Start Over
MATI: An efficient algorithm for influence maximization in social networks
- Source :
- PLoS ONE, Vol 13, Iss 11, p e0206318 (2018), PLoS ONE, PLoS ONE, Public Library of Science, 2018, ⟨10.1371/journal.pone.0206318⟩, PLoS ONE, 2018, ⟨10.1371/journal.pone.0206318⟩, PLOS ONE, Complex Networks 2017-6th International Conference on Complex Networks and Their Applications, Complex Networks 2017-6th International Conference on Complex Networks and Their Applications, Nov 2017, Lyon, France. pp.1-3, ⟨10.1371/journal.pone.0206318⟩
- Publication Year :
- 2018
- Publisher :
- Public Library of Science (PLoS), 2018.
-
Abstract
- International audience; Influence maximization has attracted a lot of attention due to its numerous applications, including diffusion of social movements, the spread of news, viral marketing and outbreak of diseases. The objective is to discover a group of users that are able to maximize the spread of influence across a network. The greedy algorithm gives a solution to the Influence Maxi-mization problem while having a good approximation ratio. Nevertheless it does not scale well for large scale datasets. In this paper, we propose Matrix Influence, MATI, an efficient algorithm that can be used under both the Linear Threshold and Independent Cascade diffusion models. MATI is based on the precalculation of the influence by taking advantage of the simple paths in the node's neighborhood. An extensive empirical analysis has been performed on multiple real-world datasets showing that MATI has competitive performance when compared to other well-known algorithms with regards to running time and expected influence spread.
- Subjects :
- Statistical methods
Computer science
Social Sciences
lcsh:Medicine
02 engineering and technology
Social Networking
Sociology
Viral marketing
Medicine and Health Sciences
0202 electrical engineering, electronic engineering, information engineering
Centrality
Social Change
lcsh:Science
Greedy algorithm
ComputingMilieux_MISCELLANEOUS
Marketing
Multidisciplinary
Applied Mathematics
Simulation and Modeling
Statistics
Monte Carlo method
Infectious Diseases
Social Networks
Calibration
Physical Sciences
020201 artificial intelligence & image processing
Algorithms
Network Analysis
Research Article
Behavior Control
Computer and Information Sciences
Mathematical optimization
Infectious Disease Control
[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]
Scale (descriptive set theory)
Research and Analysis Methods
[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
Probability theory
020204 information systems
Humans
[INFO]Computer Science [cs]
Social Behavior
Internet
Social network
Information Dissemination
business.industry
Node (networking)
lcsh:R
Maximization
Models, Theoretical
Probability Theory
Communications
Mathematical and statistical techniques
lcsh:Q
business
Mathematics
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- PLOS ONE
- Accession number :
- edsair.doi.dedup.....a1987a0a1711446f2c5873f0949f40ca