منابع مشابه
Overlapping Community Detection in Social Networks Based on Stochastic Simulation
Community detection is a task of fundamental importance in social network analysis. Community structures enable us to discover the hidden interactions among the network entities and summarize the network information that can be applied in many applied domains such as bioinformatics, finance, e-commerce and forensic science. There exist a variety of methods for community detection based on diffe...
متن کاملoverlapping community detection in social networks based on stochastic simulation
community detection is a task of fundamental importance in social network analysis. community structures enable us to discover the hidden interactions among the network entities and summarize the network information that can be applied in many applied domains such as bioinformatics, finance, e-commerce and forensic science. there exist a variety of methods for community detection based on diffe...
متن کاملEvent Detection in Social Networks
Micro-blog services such as Twitter generate a large amount of messages carrying event information and users’ opinions over a wide range of topics. The events discussed on social networks can be associated with topics, locations, and time periods. The events can be a variety, such as celebrities or political affairs, local social events, accidents, protests, or natural disasters. Messages are p...
متن کاملAn Optimized Firefly Algorithm based on Cellular Learning Automata for Community Detection in Social Networks
The structure of the community is one of the important features of social networks. A community is a sub graph which nodes have a lot of connections to nodes of inside the community and have very few connections to nodes of outside the community. The objective of community detection is to separate groups or communities that are linked more closely. In fact, community detection is the clustering...
متن کاملDetection of Fake Accounts in Social Networks Based on One Class Classification
Detection of fake accounts on social networks is a challenging process. The previous methods in identification of fake accounts have not considered the strength of the users’ communications, hence reducing their efficiency. In this work, we are going to present a detection method based on the users’ similarities considering the network communications of the users. In the first step, similarity ...
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ژورنال
عنوان ژورنال: IEEE Transactions on Computational Social Systems
سال: 2016
ISSN: 2329-924X
DOI: 10.1109/tcss.2016.2627811