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A dissemination model based on psychological theories in complex social networks
2021
IEEE Transactions on Cognitive and Developmental Systems
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Information spread on social media has been extensively studied through both model-driven theoretical research and data-driven case studies. ...
To capture the complex patterns of the information dissemination mechanism, we propose a resistant linear threshold (RLT) dissemination model based on psychological theories and empirical findings. ...
[33] considered the time delay of propagation and proposed the continuous-time delay linear threshold (CTLT). Yang et al. ...
doi:10.1109/tcds.2021.3052824
fatcat:arj7gnosbraxlbqp4rpoj3pjey
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation
[article]
2020
arXiv
pre-print
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Based on the analysis, we model the diffusion as a mixture of Independent Cascade models (MIC) with parameters θ_T, θ_F over the social network graph; and derive unsupervised inference techniques for parameter ...
Moreover, information sharing on social media facilitates diffusion of viral information cascades. ...
In Fig 8, we evaluate cascade separability based on clustering accuracy and f1 with estimated diffusion mixture model (MIC); varied over # of cascades at different mixture distributions. ...
arXiv:2008.03450v1
fatcat:sw4mj4tyxfhm3kxdl5weei7rn4
Identifying Topic-sensitive Influential Spreaders in Social Networks
2015
International Journal of Hybrid Information Technology
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In this paper, we propose to harness historical propagation data to learn the information diffusion probabilities on topic-level, based on which we use a greedy algorithm to iteratively select a set of ...
Given observed propagation data, we first use Latent Dirichlet Allocation (LDA) model to learn a topic mixture for each propagation message. ...
fashion, so propagation actions with different time delays Figure 2 shows an example of information propagation graph. ...
doi:10.14257/ijhit.2015.8.2.38
fatcat:splmymtka5d2tf6dwbo53yl7pa
Analyzing the Dynamics of Communication in Online Social Networks
[chapter]
2010
Handbook of Social Network Technologies and Applications
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This dissertation deals with the analysis of interpersonal communication dynamics in online social networks and social media. ...
My central hypothesis is that communication dynamics between individuals manifest themselves via three key aspects: the information that is the content of communication, the social engagement i.e. the ...
Social Diffusion Analysis The analysis of social information diffusion has been of interest to researchers from various domains ranging from social sciences, epidemiology, disease propagation, physics ...
doi:10.1007/978-1-4419-7142-5_4
fatcat:d2mn6rm64zg2bdgo4kdoysyi64
Literature Survey on Interplay of Topics, Information Diffusion and Connections on Social Networks
[article]
2017
arXiv
pre-print
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Researchers have attempted to model information diffusion and topic trends and lifecycle on online social networks. ...
The current article presents a survey of representative models that perform topic analysis, capture information diffusion, and explore the properties of social connections in the context of online social ...
Trend and topic propagation is one of the key factors that are associated with information diffusion on online social networks. ...
arXiv:1706.00921v1
fatcat:doqorr3v2zhq5oiemm5zhlmc3u
Influence analysis: A survey of the state-of-the-art
2018
Mathematical Foundations of Computing
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First, we review the development process of influence analysis in social networks based on several basic conceptions and features in a social aspect. Then the online social networks are discussed. ...
After describing the classical models which simulate the influence spreading progress, we give a bird's eye view of the up-to-date literatures on influence diffusion models and influence maximization approaches ...
The phenomena of time-delay in information diffusion has been explored in statistics. Observation by Moro et al. ...
doi:10.3934/mfc.2018010
fatcat:n2vnokuivbbdjjuptgyzurhceu
Deep Agent: Studying the Dynamics of Information Spread and Evolution in Social Networks
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2003.11611v1 fatcat:m2gc6v57rrcudakbbk24ym5ivu
We focused on modeling three information domains: cryptocurrencies, cyber threats, and software vulnerabilities for the three interrelated social environments: GitHub, Reddit, and Twitter. ...
This paper explains the design of a social network analysis framework, developed under DARPA's SocialSim program, with novel architecture that models human emotional, cognitive and social factors. ...
Agent-Based Models The agent-based models in this paper are generative rule-driven models, designed based on the social theory on Diffusion of Information (DoI) and the user actions in OSNs. ...
arXiv:2003.11611v2
fatcat:jplfsweeyrfj3fftlaa2ejjtgy
MIDMod-OSN: A Microscopic-level Information Diffusion Model for Online Social Networks
[article]
2020
arXiv
pre-print
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We build a model based on Bayesian Logistic Regression for learning and prediction and Random Forests for feature selection. ...
As online social networks continue to be commonly used for the dissemination of information to the public, understanding the phenomena that govern information diffusion is crucial for many security and ...
CONCLUSION AND FUTURE WORK Predicting information diffusion will continue to be an active research area due to the fast growing importance of online social networks. ...
arXiv:2002.10522v2
fatcat:vwrzg3cy4zgovfnuserxr4tj5a
Information diffusion in online social networks
2013
SIGMOD record
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The objective is to provide a comprehensive analysis and guide of existing efforts around information diffusion in social networks. ...
Online social networks play a major role in the spread of information at very large scale. ...
counterparts plus a time-delay parameter on each edge of the graph. ...
doi:10.1145/2503792.2503797
fatcat:hdusatji55atrpxiatsetizijq
Data Driven Modeling of Continuous Time Information Diffusion in Social Networks
2017
2017 IEEE Second International Conference on Data Science in Cyberspace (DSC)
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In this dissertation proposal, we proposed a new information diffusion model, namely, sustaining cascading (SC) model to study the influence maximization problem and based on the SC model, we further plan ...
One specific problem is influence maximization problem in online social networks, which maximize the result of information diffusion process. ...
An information diffusion model can help people understand how information spread in online social networks. ...
doi:10.1109/dsc.2017.103
dblp:conf/dsc/LiuCQHQ17
fatcat:i2xrapht2fblxbhu3rwt4g2b2y
A survey of Big Data dimensions vs Social Networks analysis
2020
Journal of Intelligent Information Systems
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The pervasive diffusion of Social Networks (SN) produced an unprecedented amount of heterogeneous data. ...
More in detail, the analysis of user generated data by popular social networks (i.e Facebook (https://www.facebook.com/), Twitter (https://www.twitter.com/), Instagram (https://www.instagram.com/), LinkedIn ...
Both approaches had a great impact on the analysis of new communication models that came out after social network pervasive diffusion as they try to provide answers both to company and societal needs. ...
doi:10.1007/s10844-020-00629-2
pmid:33191981
pmcid:PMC7649712
fatcat:3hvd5sshwzd67lxi4qlo2sgnwe
Survival Factorization on Diffusion Networks
[chapter]
2017
Lecture Notes in Computer Science
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By exploiting the cumulative properties of the survival function and of the likelihood of the model on a given adoption log, which records the observed activation times of users and side-information for ...
In this paper we propose a survival factorization framework that models information cascades by tying together social influence patterns, topical structure and temporal dynamics. ...
Twitter The following analysis is based on a sample of real-world propagation cascades crawled from the public timeline of Twitter and studied in [2] . ...
doi:10.1007/978-3-319-71249-9_41
fatcat:pymyr6i67bgjzjjkh2igavmuni
Propagation From Deceptive News Sources Who Shares, How Much, How Evenly, and How Quickly?
2018
IEEE Transactions on Computational Social Systems
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2018 pre-print arXiv:1812.03533v1 fatcat:4pjwp5sybvcrzgh6x5immwhb44
These include high inequity in the diffusion rate based on the source of disinformation, with a small group of highly active users responsible for the majority of disinformation spread overall and within ...
As people rely on social media as their primary sources of news, the spread of misinformation has become a significant concern. ...
Twitter data used for the analysis in this paper was acquired from a vendor and analyzed over the period of 01/2016 -01/2017. ...
doi:10.1109/tcss.2018.2881071
fatcat:3hchhi3w6rcnpawfsmh7jep2k4
Influence learning for cascade diffusion models: focus on partial orders of infections
2016
Social Network Analysis and Mining
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Probabilistic cascade models consider information diffusion as an iterative process in which information transits between users of a network. ...
The problem of diffusion modeling then comes down to learning transmission probability distributions, depending on hidden influence relationships between users, in order to discover the main diffusion ...
Furthermore, as the nature of the propagated information may have a great impact on its spread of diffusion, we are also currently considering mixtures of delay-agnostic IC models that depend on the diffused ...
doi:10.1007/s13278-016-0406-1
fatcat:biu235wh2zbkpdwriqamhugbba
Online Social Deception and Its Countermeasures for Trustworthy Cyberspace: A Survey
[article]
2020
arXiv
pre-print
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Based on this survey, we provide insights into the effectiveness of countermeasures and the lessons from existing literature. ...
We are living in an era when online communication over social network services (SNSs) have become an indispensable part of people's everyday lives. ...
information diffusion.
5.3.2 Credibility-based Models. ...
arXiv:2004.07678v1
fatcat:k4a6siywefb6lhkmyn67lmoqwe
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