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On Using Temporal Networks to Analyze User Preferences Dynamics [chapter]

Fabíola S. F. Pereira, Sandra de Amo, João Gama
2016 Lecture Notes in Computer Science  
Then, we use evolving centralities from temporal networks to link with preferences dynamics.  ...  Our results indicate that modeling Twitter as a temporal network is more appropriated for analyzing user preferences dynamics than using just snapshots of static network.  ...  algorithm for detecting changes events in preferences; (3) a centrality change detection algorithm; (4) proposal of a correlation between preferences and centrality measures in temporal networks; (5)  ... 
doi:10.1007/978-3-319-46307-0_26 fatcat:ee5zp67uufbodp3dsjrnq2lmlu

On analyzing user preference dynamics with temporal social networks

Fabíola S. F. Pereira, João Gama, Sandra de Amo, Gina M. B. Oliveira
2018 Machine Learning  
Following this, we use temporal networks concepts to analyze the evolution of social relationships and propose strategies to detect changes in the network structure based on node centrality.  ...  First, we propose a temporal preference model able to detect preference change events of a given user.  ...  In Sect. 4 we propose the use of temporal social networks and define centrality-based metrics to detect changes in nodes position on the network.  ... 
doi:10.1007/s10994-018-5740-2 fatcat:yrjpn7pq6jfyxhqf5czv5ixl3u

Temporal Changes in Connection Patterns of an Email-Based Social Network

Krzysztof Juszczyszyn, Przemyslaw Kazienko, Katarzyna Musial, Bogdan Gabrys
2008 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology  
We have shown that temporal changes in local connection patterns of the social network are indeed correlated with the changes in the clustering coefficient as well as various centrality measures values  ...  At the same time, the analysis of three-node motifs (triads) was used to track the temporal changes in the structure of a large social network derived from e-mail communication between university employees  ...  This network was used for motifs detection in order to check how the motif SP changes when different periods of time are considered.  ... 
doi:10.1109/wiiat.2008.245 dblp:conf/iat/JuszczyszynKMG08 fatcat:hq6d5stxcbgu7l4dvfc5umwumi

Evolving Networks and Social Network Analysis Methods and Techniques [chapter]

Mário Cordeiro, Rui P. Sarmento, Pavel Brazdil, João Gama
2018 Social Media and Journalism - Trends, Connections, Implications  
like network centrality change as a function of time, popularity and influence of individuals grow or fade depending on processes, and events occur in networks during time intervals.  ...  Due to their temporal dimension, rapid growth of users, velocity of changes in networks, and amount of data that these OSNs generate, effective and efficient methods and techniques for small static networks  ...  [51] , despite being a static algorithm, it can be used to calculate centralities in changing networks. This is true by considering full calculations of the centralities for each network snapshot.  ... 
doi:10.5772/intechopen.79041 fatcat:x4m2g5borjfijknqck54ierppq

A statistical framework for streaming graph analysis

James Fairbanks, David Ediger, Rob McColl, David A. Bader, Eric Gilbert
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
We study the temporal nature of betweenness centrality and clustering coefficients while producing multiple visualizations of a social network dataset with 1.2 million edges.  ...  In this paper we propose a new methodology for gaining insight into the temporal aspects of social networks.  ...  This is an embedding of the vertices into a real vector space that captures both topological information and the temporal changes to the network. This embedding can be used for any data mining task.  ... 
doi:10.1145/2492517.2492620 dblp:conf/asunam/FairbanksEMBG13 fatcat:mtuyg5navzhplbqmraak6dbktm

Modelling community structure and temporal spreading on complex networks

Vesa Kuikka
2021 Computational Social Networks  
In this study, classical network connectivity and influence spreading models are used as examples for network models.  ...  Two different temporal spreading distributions demonstrate the methods with three real-world social networks of different sizes.  ...  Also, the network topology may change during the spreading process. Changes in network structure and changes in link and node attribute values are common in many applications.  ... 
doi:10.1186/s40649-021-00094-z fatcat:5hxpakyl3vhxjl4yepuxibivgu

Exploring the use of time-varying graphs for modelling transit networks [article]

Ikechukwu Maduako, Emerson Cavalheri, Monica Wachowicz
2018 arXiv   pre-print
Dynamics in this relationshipalsohave been detected using network metrics such as temporal shortest paths, degree, betweenness and PageRank centralities as well as temporal network diameter and density  ...  The effectiveness of this proposed model has been explored by implementing the model in Neo4j graph database using transit feeds generated by bus transit network of the City of Moncton, New Brunswick,  ...  Mobility patterns have been detected using network metrics such as temporal shortest paths, degree, betweenness and PageRank centralities as well as temporal network diameter and density.  ... 
arXiv:1803.07610v1 fatcat:cendpvzqxvflpabdc4ml5scjn4

The optimal window size for analysing longitudinal networks

Shahadat Uddin, Nazim Choudhury, Sardar M. Farhad, Md. Towfiqur Rahman
2017 Scientific Reports  
In the same way, betweenness centrality values of actors can be used to explore how actors change their capacities to control flows of information between any pair of network actors over time in a longitudinal  ...  Similar differences can be found when other social network measures (e.g., closeness centrality) are used to quantify actors' network positions.  ...  As identified by Fish and Caceres 38 , researchers have defined this problem differently (e.g., change point detection, time scale detection, oversampling correction, temporal resolution inference, aggregation  ... 
doi:10.1038/s41598-017-13640-5 pmid:29042602 pmcid:PMC5645324 fatcat:bucmtrv3ijh5jcha76vxkxrzey

Community-based time segmentation from network snapshots

Thomas Magelinski, Kathleen M. Carley
2019 Applied Network Science  
Community detection has proved to be extremely successful in a variety of domains. However, most of the algorithms used in practice assume networks are unchanging in time.  ...  Lastly, we use our first two case studies to determine optimal parameters for an anomaly-detection-based streaming method.  ...  We would also like to thank MAJ David Beskow, for collecting the Twitter data used in the last case study.  ... 
doi:10.1007/s41109-019-0136-1 fatcat:ckzv4fdcpbas3c2fwcseau7hbm

Sensing spatial and temporal coordination in teams using the smartphone

Sebastian Feese, Michael Joseph Burscher, Klaus Jonas, Gerhard Tröster
2014 Human-Centric Computing and Information Sciences  
In such scenarios, the used technique can only give rough proximity cues. Further, we measured temporal coordination as simultaneous change in activity level.  ...  Further, we propose to summarize the structures of the extracted team networks using density and centralization metrics as used in social network analysis. 3.  ... 
doi:10.1186/s13673-014-0015-9 fatcat:cqb4mmdf3vcjdogycucsrgfdiu

Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory

Foteini Protopapa, Constantinos I. Siettos, Ioannis Evdokimidis, Nikolaos Smyrnis
2014 Frontiers in Computational Neuroscience  
Change detection-memory trial types resulted in a three-peak temporal pattern of the total degree with higher degree nodes emerging mainly at central, right frontal, and occipital areas.  ...  We employed spectral Granger causality analysis on a full set of 56 electroencephalographic recordings acquired during the execution of either a 2D movement pointing or a perceptual (yes/no) change detection  ...  FUNCTIONAL CONNECTIVITY NETWORK FOR THE CHANGE DETECTION TASK Memorizing a target location for the performance of a change detection task also resulted in the emergence of a robust pattern characterized  ... 
doi:10.3389/fncom.2014.00146 pmid:25431557 pmcid:PMC4230052 fatcat:i2q6dwxelba6depfuow6aovj3e

Resting Connectivity in Non-lesional Temporal Lobe Epilepsy

Mohamad Koubeissi
2017 Epilepsy Currents  
Using the detected clusters as seed regions revealed decreased connectivity from the sclerotic hippocampus to both the contralateral temporal lobe and regions of the default mode network.  ...  No functional abnormality was detected within mesial temporal structures.  ...  Using the detected clusters as seed regions revealed decreased connectivity from the sclerotic hippocampus to both the contralateral temporal lobe and regions of the default mode network.  ... 
doi:10.5698/1535-7597.17.4.219 pmid:29225523 pmcid:PMC5716112 fatcat:uwsatqkcbnem3hntqqalmtlqsy

Objective measures for sentinel surveillance in network epidemiology

Petter Holme
2018 Physical review. E  
As a basis for the comparison, we use the susceptible-infectious-recovered model on static and temporal networks of human contacts.  ...  As opposed to other problems in network epidemiology, we draw similar conclusions from the static and temporal networks.  ...  Static networks We use the time to detection and extinction as our baseline and compare the other two objective measures with that.  ... 
doi:10.1103/physreve.98.022313 pmid:30253620 pmcid:PMC7217546 fatcat:2n74rp7dljguhkywyvsnfharza

Spatiotemporal data analysis with chronological networks

Leonardo N. Ferreira, Didier A. Vega-Oliveros, Moshé Cotacallapa, Manoel F. Cardoso, Marcos G. Quiles, Liang Zhao, Elbert E. N. Macau
2020 Nature Communications  
Using artificial and real data sets, we show how chronnets can capture data properties beyond simple statistics, like frequent patterns, spatial changes, outliers, and spatiotemporal clusters.  ...  Here, we propose a network-based model, called Chronnet, for spatiotemporal data analysis.  ...  This result shows that the proposed can successfully find temporal clusters. Spatial changes can also be detected using the community structure in chronnet.  ... 
doi:10.1038/s41467-020-17634-2 pmid:32788573 fatcat:qyca3kk32rhtjnknic32u3xs5q

Dynamic network centrality summarizes learning in the human brain

A. V. Mantzaris, D. S. Bassett, N. F. Wymbs, E. Estrada, M. A. Porter, P. J. Mucha, S. T. Grafton, D. J. Higham
2013 Journal of Complex Networks  
We thereby provide a proof of principle for the use of recently proposed dynamic centrality measures on temporal network data in neuroscience.  ...  Using network centrality measures that respect the arrow of time, we express the data in an extremely compact form that characterizes the aggregate activity of each brain region in each experiment using  ...  In a previous examination of these data, we used time-dependent community detection [20] to identify statistically significant temporal evolution of network organization over time [5] .  ... 
doi:10.1093/comnet/cnt001 fatcat:3qec5hxhunaqzlu75owaixdnvu
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