Social networks have become an increasingly common abstraction to capture the interactions of individual users in a number everyday activities and applications. As result, analysis such has attracted lots attention literature. Among topics interest, key problem relates identifying so-called influential for applications, which need spread messages. Several approaches been proposed estimate users' influence identify sets social networks. A basis these is consider links between users, that is,...

Abstract Social network analysis has recently attracted lots of attention among researchers due to its wide applicability in capturing social interactions. Link prediction, related the likelihood having a link between two nodes that are not connected, is key problem analysis. Many methods have been proposed solve problem. Among these methods, similarity-based exhibit good efficiency by considering structure and using as fundamental criterion number common neighbours establish structural...

Centrality measures have been widely used to capture the properties of different nodes in a social network, particularly when edges are fully deterministic. Various models also proposed calculate nodes' centrality graphs where there might be some uncertainty relation edges. Their common characteristic is that graph essentially embedded into calculation compute single crisp value. However, as degree may vary, values vary. In this paper, making use fuzzy set theory, we assume network modelled...

Influence maximization is a fundamental problem in social network analysis. This refers to the identification of set influential users as initial spreaders maximize spread message network. When such spread, some may be influenced by it. A common assumption existing work that impact essentially binary: user either (activated) or not (non-activated). However, how strongly play an important role this user’s attempt influence subsequent and further; methods fail model accurately spreading...

Classifying the stance of individuals on controversial topics and uncovering their concerns is crucial for social scientists policymakers. Data from Online Social Networks (OSNs), which serve as a proxy to representative sample society, offers an opportunity classify these stances, discover society's regarding topics, track evolution over time. Consequently, classification in OSNs has garnered significant attention researchers. However, most existing methods this task often rely labelled...

The spread of rumours in social networks has become a significant challenge recent years. Blocking so-called critical edges, that is, edges have role the spreading process, attracted lots attention as means to minimize rumours. Although detection sources rumour may help identify this an overhead source-ignorant approaches are trying eliminate. Several edge blocking methods been proposed which mostly determine on basis centrality. Taking into account additional features (beyond centrality)...

Abstract The emergence of a new virus in community may cause significant overload on health services and spread out to other communities quickly. Social distancing help reduce the infection rate within prevent communities. However, social comes at cost; how strike good balance between reduction cost be challenging problem. In this paper, problem is formulated as bi-objective optimization Assuming that community-based society interaction links have different capacities, determine link...

Individuals may have a range of opinions on controversial topics. However, the ease making friendships in online social networks tends to create groups like-minded individuals, who propagate messages that reinforce existing and ignore expressing opposite opinions. This creates situation where there is decrease diversity which users are exposed ( exposure ). means do not easily get chance be containing alternative viewpoints; it even more unlikely they forward such their friends. Increasing...

In recent years, the problem of identifying spreading ability and ranking social network users according to their influence has attracted a lot attention; different approaches have been proposed for this purpose. Most these rely on topological location nodes neighbours in graph provide measure that estimates users. One most well-known measures is k-shell; additional based it. However, as same k-shell index may be assigned with degrees, suffers from low accuracy. This paper trying improve by...

Social networks have become an increasingly common abstraction to capture the interactions of individual users in a number everyday activities and applications. As result, analysis such has attracted lots attention literature. Among topics interest, key problem relates identifying so-called influential for applications, which need spread messages. Several approaches been proposed estimate users' influence identify sets social networks. A basis these is consider links between users, that is,...