scholarly journals From calls to communities: a model for time-varying social networks

2015 ◽  
Vol 88 (11) ◽  
Author(s):  
Guillaume Laurent ◽  
Jari Saramäki ◽  
Márton Karsai
Keyword(s):  
Social Networks ◽  
Time Varying

scholarly journals Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks

2021 ◽  
Vol 13 (3) ◽  
pp. 76
Author(s):  
Quintino Francesco Lotito ◽  
Davide Zanella ◽  
Paolo Casari
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Simulation Models ◽  
Epidemic Models ◽  
Time Varying ◽  
Fake News ◽  
Network Access ◽  
Spreading Process ◽  
Network Topologies ◽  
Access Patterns

The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading.

scholarly journals Opinion formation in time-varying social networks: The case of the naming game

2012 ◽  
Vol 86 (3) ◽  
Author(s):  
Suman Kalyan Maity ◽  
T. Venkat Manoj ◽  
Animesh Mukherjee
Keyword(s):  
Social Networks ◽  
Time Varying ◽  
Opinion Formation ◽  
Naming Game

scholarly journals A Social Interaction Activity based Time-Varying User Vectorization Method for Online Social Networks

2018 ◽  
Author(s):  
Tianyi Hao ◽  
Longbo Huang
Keyword(s):  
Social Networks ◽  
Social Interaction ◽  
Online Social Networks ◽  
User Modeling ◽  
State Of The Art ◽  
Time Varying ◽  
Self Similarity ◽  
Pairwise Interactions ◽  
User Data ◽  
Model Training

In this paper, we consider the problem of user modeling in online social networks, and propose a social interaction activity based user vectorization framework, called the time-varying user vectorization (Tuv), to infer and make use of important user features. Tuv is designed based on a novel combination of word2vec, negative sampling and a smoothing technique for model training. It jointly handles multi-format user data and computes user representing vectors, by taking into consideration user feature variation, self-similarity and pairwise interactions among users. The framework enables us to extract hidden user properties and to produce user vectors. We conduct extensive experiments based on a real-world dataset, which show that Tuv significantly outperforms several state-of-the-art user vectorization methods.

scholarly journals Exploiting Temporal and Spatial Regularities for Content Dissemination in Opportunistic Social Network

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Zhiyuan Li ◽  
Junlei Bi ◽  
Carlos Borrego
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Success Rate ◽  
State Of The Art ◽  
Time Varying ◽  
Hop Count ◽  
Content Dissemination ◽  
System Overhead ◽  
Temporal And Spatial ◽  
Query Latency

Recently, content dissemination has become more and more important for opportunistic social networks. The challenges of opportunistic content dissemination result from random movement of nodes and uncertain positions of a destination, which seriously affect the efficiency of content dissemination. In this paper, we firstly construct time-varying interest communities based on the temporal and spatial regularities of users. Next, we design a content dissemination algorithm on the basis of time-varying interest communities. Our proposed content dissemination algorithm can run in O(nlog⁡n) time. Finally, the comparisons between the proposed content dissemination algorithm and state-of-the-art content dissemination algorithms show that our proposed content dissemination algorithm can (a) keep high query success rate, (b) reduce the average query latency, (c) reduce the hop count of a query, and (d) maintain low system overhead.

Rumor Source Identification in Social Networks with Time-Varying Topology

2018 ◽  
Vol 15 (1) ◽  
pp. 166-179 ◽  
Author(s):  
Jiaojiao Jiang ◽  
Sheng Wen ◽  
Shui Yu ◽  
Yang Xiang ◽  
Wanlei Zhou
Keyword(s):  
Social Networks ◽  
Source Identification ◽  
Time Varying
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