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Modeling Information Diffusion over Social Networks for Temporal Dynamic Prediction
2017
IEEE Transactions on Knowledge and Data Engineering
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Micro-models hold the ability to predict diffusion processes, unfortunately, most of these models ignore the important fact that information diffusion fundamentally is a temporal dynamic process. ...
By introducing time series into the payoff calculation, the proposed model has the capability to predict the temporal dynamics of the information diffusion process. ...
doi:10.1109/tkde.2017.2702162
fatcat:onrofzlsabdrnmteddaenfgnzm
Modeling information diffusion over social networks for temporal dynamic prediction
2013
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13
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Micro-models hold the ability to predict diffusion processes, unfortunately, most of these models ignore the important fact that information diffusion fundamentally is a temporal dynamic process. ...
By introducing time series into the payoff calculation, the proposed model has the capability to predict the temporal dynamics of the information diffusion process. ...
doi:10.1145/2505515.2507823
dblp:conf/cikm/LiXLLGSLHC13
fatcat:o6nzipz45je2bovgbdexrm3rky
Diffusive Logistic Model Towards Predicting Information Diffusion in Online Social Networks
2012
2012 32nd International Conference on Distributed Computing Systems Workshops
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Our experiment results show that the DL model is able to characterize and predict the process of information propagation in online social networks. ...
Most of prior work either carried out empirical studies or focus on the information diffusion modeling in temporal dimension, little attempt has been given on understanding information diffusion over both ...
ACKNOWLEDGMENT We would like to thank Kristina Lerman for making the Digg 2009 data set available to our research project. ...
doi:10.1109/icdcsw.2012.16
dblp:conf/icdcsw/WangWX12
fatcat:mcjezn53pbcazno2tckkp53mnm
Diffusive Logistic Model Towards Predicting Information Diffusion in Online Social Networks
[article]
2011
arXiv
pre-print
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For example, for the most popular news with 24,099 votes in Digg, the average prediction accuracy of DL model over all distances during the first 6 hours is 92.08%. ...
Many prior work have carried out empirical studies and proposed diffusion models to understand the information diffusion process in online social networks. ...
temporal and spatial patterns of information diffusion over online social networks. ...
arXiv:1108.0442v1
fatcat:a6fbfgomfzb6lf67zkgsxwu5he
Characterizing Information Diffusion in Online Social Networks with Linear Diffusive Model
2013
2013 IEEE 33rd International Conference on Distributed Computing Systems
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Mathematical modeling is an important approach to study information diffusion in online social networks. Prior studies have focused on the modeling of the temporal aspect of information diffusion. ...
A recent effort introduced the spatiotemporal diffusion problem and addressed the problem with a theoretical framework built on the similarity between information propagation in online social networks ...
This supports the predictability of spatio-temporal information diffusion dynamics. ...
doi:10.1109/icdcs.2013.14
dblp:conf/icdcs/WangWXWJ13
fatcat:oahjigipircb5nnjtli3wpo5fe
Advancement from Topic based to Information based Model: A Survey
2015
International Journal of Computer Applications
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topic detection to information diffusion modeling, containing prominent diffuser's identification. ...
The aim of this paper is to provide an extensive analysis of prevailing efforts around information diffusion in social networks is the aim of the paper. ...
The temporal dynamic is the number of nodes that accepts the part of information over time called as diffusion rate. ...
doi:10.5120/21578-4643
fatcat:lxdkdiibt5e6xfzvrtzmogotv4
Social network user influence sense-making and dynamics prediction
2014
Expert systems with applications
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We propose a dynamic information propagation model based on Continuous-Time Markov Process to predict the influence dynamics of social network users, where the nodes in the propagation sequences are the ...
In addition, most of the developed algorithms and tools are mainly dependent on the static network structure instead of the dynamic diffusion process over the network, and are thus essentially based on ...
To address the second limitation, we propose a dynamic information diffusion model based on the Continuous-Time Markov Process (CTMP) to predict the influence dynamics of social network users. ...
doi:10.1016/j.eswa.2014.02.038
fatcat:iickiw6g3ngsdfjynuxsr72kja
Social Network User Influence Dynamics Prediction
[chapter]
2013
Lecture Notes in Computer Science
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In this paper, we propose a dynamic information propagation model based on Continuous-Time Markov Process to predict the influence dynamics of social network users, where the nodes in the propagation sequences ...
Most of the developed algorithms and tools are mainly dependent on the static network structure instead of the dynamic diffusion process over the network, and are thus essentially based on descriptive ...
In particular, To address the limitation, we propose a dynamic information diffusion model based on Continuous-Time Markov Process (CTMP) to predict the influence dynamics of social network users. ...
doi:10.1007/978-3-642-37401-2_32
fatcat:ar3wqqpyvngkbe37vzsmiyxjle
Predicting the Temporal Dynamics of Information Diffusion in Social Networks
[article]
2013
arXiv
pre-print
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In this paper we address the issue of predicting the temporal dynamics of the information diffusion process. ...
observed in online social networks. ...
predict the degree of adoption of such information in the provided social network for a given period of time, i.e. the temporal patterns of the dynamics? ...
arXiv:1302.5235v2
fatcat:5saoviqrxjendldd4gjejab6vu
Information diffusion in online social networks
2013
Proceedings of the 2013 Sigmod/PODS Ph.D. symposium on PhD symposium - SIGMOD'13 PhD Symposium
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So far, our contributions are the following: (i) a survey of developments in the field; (ii) T-BaSIC, a graph-based model for information diffusion prediction; (iii) SONDY, an open source platform that ...
Online social networks play a major role in the spread of information at very large scale and it becomes essential to provide means to analyze this phenomenon. ...
In section 3, we introduce T-BaSIC, a predictive model for information diffusion. Section 4 describes SONDY, an open source platform for social dynamics mining and analysis. ...
doi:10.1145/2483574.2483575
dblp:conf/sigmod/Guille13
fatcat:htlwhtlifbci3gvdgagbe3lpf4
Information Diffusion Temporal Dynamic Prediction in Microblog System Based On User Influence Learning
2016
International Journal of Hybrid Information Technology
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In this research, a novel graphbased cascades construct algorithm is proposed, with which we build a prediction model for future information diffusion dynamics. ...
Information diffusion in online social network especially in microblog system, can largely affect the public opinion and even the development of events, so the prediction of the future dynamics of diffusion ...
Acknowledgements The work was sponsored by "The Fundamental Research Funds for the Central ...
doi:10.14257/ijhit.2016.9.6.29
fatcat:x7vcicrmlffabifrwxswtoviua
Who is next: rising star prediction via diffusion of user interest in social networks
[article]
2022
arXiv
pre-print
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To address above challenges, in this paper, we observe that the presence of rising stars is closely correlated with the early diffusion of user interest in social networks, which is validated in the case ...
Thus, we propose a novel framework, RiseNet, to incorporate the user interest diffusion process with the item dynamic features to effectively predict rising stars. ...
However, most of these works analyse user interest information by exacting several features from their social media content and ignore the dynamic information in user social network. ...
arXiv:2203.14807v2
fatcat:ah4i5bdct5hxfdzqvjazh5ce2u
Community Level Diffusion Extraction
2015
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data - SIGMOD '15
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Our method guarantees high scalability with increasing data size. 1 Weak social ties are responsible for the majority of the information spreading through human networks. ...
., COmmunity Level Diffusion (COLD), to uncover and explore temporal diffusion. We model topics and communities in a unified latent framework, and extract inter-community influence dynamics. ...
DIFFUSION PREDICTION & ANALYSIS Modeling information diffusion at community level can provide insights into social dynamics at a brand new granularity. ...
doi:10.1145/2723372.2723737
dblp:conf/sigmod/HuYCX15
fatcat:e73jxvicovdz5ecmgl3et44tei
Predicting Information Diffusion Initiated from Multiple Sources in Online Social Networks
2013
2013 Sixth International Symposium on Computational Intelligence and Design
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A number of prior studies apply mathematical approaches to characterize and model the complex dynamics of information dissemination, also called information diffusion over online social networks. ...
In recent years, online social networks such as Twitter and Facebook have become a major channel for information dissemination and communication. ...
diffusion over online social networks. ...
doi:10.1109/iscid.2013.138
fatcat:fxfh43pkh5e5jb3wpvh4wvi7f4
Dynamical Modeling, Analysis, and Control of Information Diffusion over Social Networks
2021
Discrete Dynamics in Nature and Society
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Acknowledgments e editors are very grateful to all of the authors for their outstanding contributions in this field and the reviewers for their valuable comments on the evaluation of the papers during ...
over social networks. ...
Although lots of dynamical models describing the behaviors of information diffusion have been proposed, it is still a challenging interdisciplinary task to explain and predict the dynamics of the diffusion ...
doi:10.1155/2021/9815653
doaj:8cb6466decf742979e6ce71666e056bf
fatcat:awn7withnvcx7bojpve2qhzbqe
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