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Using network motifs to characterize temporal network evolution leading to diffusion inhibition
[article]
2019
arXiv
pre-print
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In this paper, we use motif patterns to characterize the information diffusion process in social networks. ...
We test features of motif patterns by using regression models for both individual patterns and their combination and we find that motifs as features are better predictors of the future network organization ...
Numerous methods have been highlighted in [48] surrounding diffusion models for social networks. ...
arXiv:1903.00862v1
fatcat:r6vlgw6oljbsjewsna3nq75pmq
Leveraging Motifs to Model the Temporal Dynamics of Diffusion Networks
[article]
2020
arXiv
pre-print
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Information diffusion mechanisms based on social influence models are mainly studied using likelihood of adoption when active neighbors expose a user to a message. ...
In doing so, we accommodate the effect of exposures from active neighbors of a node through a network pruning technique that leverages network motifs to identify potential infectors responsible for exposures ...
algorithm based on the learned model Note that some of the patterns contain parallel nodes -one of them denoting a social / historical di usion link apart from the cascade di usion link. ese motifs have ...
arXiv:1902.10366v3
fatcat:6nzyz3ahxfeb5g7qlq55rlktau
Subgraphs of Interest Social Networks for Diffusion Dynamics Prediction
2021
Entropy
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dynamical properties, so as to be appropriate for diffusion prediction for the whole graph on the base of its small subgraph. ...
The extracted subgraphs are different for the considered interest networks, and provide interesting material for the global dynamics exploration on the mesoscale base. ...
[5] explore diffusion at individual and population scales in relation to motif structure and try to infer the diffusion network with the motif profile. Finally, diffusion networks are considered. ...
doi:10.3390/e23040492
pmid:33924216
pmcid:PMC8074582
fatcat:jbegiouohfd2jmtrf5vw2ef2gm
Socio-technical Computation
2015
Proceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing - CSCW'15 Companion
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the "infectee" and the identifier of the diffusing information; evidence for an infection is inferred based on features of the subnetwork. ...
In many cases explicit social networks built around Web-based systems condition this socio-technical interplay. ...
doi:10.1145/2685553.2698991
dblp:conf/cscw/Luczak-RoschTOS15
fatcat:aqlfdg6varbe5gokoqpmpxrvze
Spatial localisation meets biomolecular networks
2021
Nature Communications
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(iv) As an engineering tool for rewiring networks and network/circuit design. ...
, and an enabler of new network capabilities (ii) As a potent new regulator of pattern formation and self-organisation (iii) As an often hidden factor impacting inference of temporal networks from data ...
Network inference. Reverse engineering of networks is commonplace in biology, involving developing network models based on data, often neglecting spatial aspects. ...
doi:10.1038/s41467-021-24760-y
pmid:34504069
fatcat:tj6zcqgxd5gd3hn7dd6gu55ssq
Predictive Analysis for Social Diffusion: The Role of Network Communities
[article]
2009
arXiv
pre-print
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Of particular interest is the possibility to develop predictive capabilities for social diffusion, for instance enabling early identification of diffusion processes which are likely to become "viral" and ...
These empirical studies demonstrate that network community-based diffusion metrics do indeed possess predictive power, and in fact can be more useful than standard measures. ...
In [3] we a present a theoretical analysis of social diffusion on networks with realistic topologies, including community structure. The analysis leverages S-HDS models for network dynamics. ...
arXiv:0912.5242v1
fatcat:2x7feuk5jrecvgse5egxkar2fq
Detecting causality in policy diffusion processes
2016
Chaos
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In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. ...
A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. ...
Sachit Butail for his constructive feedback and invaluable help during the preparation of the revised version of this work based on the very constructive comments of two anonymous reviewers. ...
doi:10.1063/1.4961067
pmid:27586609
pmcid:PMC4991992
fatcat:6izxkfnapjcnnhv4iig7cw2eze
Network deconvolution as a general method to distinguish direct dependencies in networks
2013
Nature Biotechnology
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a n a ly s i s Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous ...
for protein structure prediction from sequence alignments; and distinguishing strong collaborations in co-authorship social networks using connectivity information alone. ...
Consistent with previous studies 5 , we found that network inference methods tend to perform better on one or the other network motif, based on their approach for dealing with indirect information (Fig ...
doi:10.1038/nbt.2635
pmid:23851448
pmcid:PMC3773370
fatcat:eq6vz6yc4vbl7kvwjlkvza2asy
Selected Ph.D. Thesis Abstracts
2017
The IEEE intelligent informatics bulletin
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to infer the diffusion models as well as the underlying diffusion mechanisms based on information cascades observed in real social networks. ...
The inferred activation motifs can be interpreted as the underlying diffusion mechanisms characterizing the diffusion happening in the social network. ...
dblp:journals/cib/Li17
fatcat:3rekqnvlozdwjcyt4hs3uyipom
Table of Contents
2020
IEEE Transactions on Network Science and Engineering
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Swami 1453 A Self-Learning Information Diffusion Model for Smart Social Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
Dai 1710 Link Prediction in Signed Social Networks: From Status Theory to Motif Families . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...
doi:10.1109/tnse.2020.3003537
fatcat:mujbc3zvzrcsxivq4pqb4v5bd4
SIGN: Scalable Inception Graph Neural Networks
[article]
2020
arXiv
pre-print
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The popularity of graph neural networks has sparked interest, both in academia and in industry, in developing methods that scale to very large graphs such as Facebook or Twitter social networks. ...
Our architecture allows using different local graph operators (e.g. motif-induced adjacency matrices or Personalized Page Rank diffusion matrix) to best suit the task at hand. ...
Studying the effect of operators induced by more complex network motifs is left for future research. ...
arXiv:2004.11198v3
fatcat:g5iyj6adujgxzb2hler65yzoum
The Cultural Evolution of National Constitutions
[article]
2017
arXiv
pre-print
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Using these topics we derive a diffusion network for borrowing from ancestral constitutions back to the US Constitution of 1789 and reveal that constitutions are complex cultural recombinants. ...
Legal "Ideas" are encoded as "topics" - words statistically linked in documents - derived from topic modeling the corpus of constitutions. ...
In order to set τ , we varied τ between 0 to 0.8, and inferred the diffusion network for each of the values. ...
arXiv:1711.06899v1
fatcat:dy7q44zbtzfrtbt3rb2soefk2y
Motif-Preserving Temporal Network Embedding
2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
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Specifically, we propose MTNE, a novel embedding model for temporal networks. ...
In light of this, we concentrate on a particular motif --- triad --- and its temporal dynamics, to study the temporal network embedding. ...
According to Eq. (1), we model the triad evolution process by modeling the base rate and past influence, respectively. Base rate. ...
doi:10.24963/ijcai.2020/172
dblp:conf/ijcai/HuangFWM020
fatcat:rnsz5yjwhvfq3jdts3nxw6cvzu
Protein Interaction Networks: Protein Domain Interaction and Protein Function Prediction
[chapter]
2011
Handbook of Statistical Bioinformatics
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These inferences are based on the premise that the function of a protein may be discovered by studying its interaction with one or more proteins of known functions. ...
The second part of this chapter reviews recent computational approaches to predict protein functions from PPI networks. ...
Local model: Each of the above approaches builds a global model to predict new edges over the network based on the partial knowledge of the network to be inferred ( Figure 8(b) ). ...
doi:10.1007/978-3-642-16345-6_21
fatcat:whl2kgd3rbfcjm3ljkd56tj7vq
Pairwise structural role mining for user categorization in information cascades
2015
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15
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We propose a new method named SR-Diffuse to simultaneously identify structural roles in a network and to model the role membership matrix of users. ...
The tendency of users to connect with peers of similar interests and social demography (homophily) is one of the sources of information for user behavior modeling and classification. ...
This algorithm, iteratively infers the social roles of users based on structural similarities in the network and by propagating roles through connections. • We show how information cascade modeling can ...
doi:10.1145/2808797.2808909
dblp:conf/asunam/ChoobdarRS15
fatcat:q2rptkeahvdmtfrfgxvpt6xq6m
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