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Reciprocal versus Parasocial Relationships in Online Social Networks [article]

Neil Zhenqiang Gong, Wenchang Xu
2014 arXiv   pre-print
However, the impacts of reciprocal edges linking ordinary and popular users on the network structures increase slowly as the social networks evolve.  ...  Many online social networks are fundamentally directed, i.e., they consist of both reciprocal edges (i.e., edges that have already been linked back) and parasocial edges (i.e., edges that haven't been  ...  For instance, linking-back probability of parasocial edges with age 0 is around 100 times higher than that of the parasocial edges with age 20 in Flickr.  ... 
arXiv:1302.6309v4 fatcat:vmp2yhpsbvatja537xzmksbdgi

Reciprocal versus parasocial relationships in online social networks

Neil Zhenqiang Gong, Wenchang Xu
2014 Social Network Analysis and Mining  
However, the impacts of reciprocal edges linking ordinary and popular users on the network structures increase slowly as the social networks evolve.  ...  Many online social networks are fundamentally directed, i.e., they consist of both reciprocal edges (i.e., edges that have already been linked back) and parasocial edges (i.e., edges that haven't been  ...  For instance, linking-back probability of parasocial edges with age 0 is around 100 times higher than that of the parasocial edges with age 20 in Flickr.  ... 
doi:10.1007/s13278-014-0184-6 fatcat:3lpwlvlvdzhwrhhyixfjg3lhp4

Centrality Robustness and Link Prediction in Complex Social Networks [chapter]

Søren Atmakuri Davidsen, Daniel Ortiz-Arroyo
2012 Computational Social Networks  
Secondly, we present a method to predict edges in dynamic social networks.  ...  the accuracy achieved on edge prediction.  ...  Centrality Robustness and Link Prediction in Complex Social Networks Centrality Robustness and Link Prediction in Complex Social Networks Centrality Robustness and Link Prediction in Complex  ... 
doi:10.1007/978-1-4471-4048-1_8 fatcat:fdhemyqvmndltaiumvkhjvhwqe

Data Fusion-Link Prediction for Evolutionary Network with Deep Reinforcement Learning

Marcus Lim, NZ Jhanjhi, Azween Abdullah
2020 International Journal of Advanced Computer Science and Applications  
learning (DRL) can contribute towards higher precision in predicting links.  ...  The design of tools to predict links between members mainly rely on Social Network Analysis (SNA) models and machine learning (ML) techniques to improve the precision of the model.  ...  Proposed MCNA-DRL Model The problem of predicting the formation or disappearance of edges in a network is treated as a binary classification task in ML modelling process.The data fusion DRL link prediction  ... 
doi:10.14569/ijacsa.2020.0110644 fatcat:652xpzvr2zaelmpwu34ew3w6bi

Status and friendship

Christina Brandt, Jure Leskovec
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
We study the differences and similarities in edge creation mechanisms in these social networks. We find large differences in edge reciprocation rates and overall structure of the underlying networks.  ...  Lastly, we show how a user's future popularity, her indegree, can be predicted based on her initial edge creation behavior.  ...  Here we tackle this question by examining mechanisms of link creation in five different social networks with the goal of understanding the roles that different social mechanisms play in the formation of  ... 
doi:10.1145/2567948.2577327 dblp:conf/www/BrandtL14 fatcat:4c4xrzcmdjdc5lwada4wt3sgam

The predictive value of young and old links in a social network

Hung-Hsuan Chen, David J. Miller, C. Lee Giles
2013 Proceedings of the ACM SIGMOD Workshop on Databases and Social Networks - DBSocial '13  
In this paper, we apply a supervised learning approach to study age as a factor for link formation.  ...  Several previously observed network properties and network evolution phenomena, such as "the number of edges grows super-linearly in the number of nodes" and "the diameter is decreasing as the network  ...  In this work, we analyze two networks with age values on edges: a coauthorship network among computer scientists and a costarring network among actors.  ... 
doi:10.1145/2484702.2484711 dblp:conf/dbsocial/ChenMG13 fatcat:frqebc4zhnaqxhw5ms34tckjdy

Applying Answer Set Programming for Knowledge-Based Link Prediction on Social Interaction Networks

Çiçek Güven, Martin Atzmueller
2019 Frontiers in Big Data  
Link prediction targets the prediction of possible future links in a social network, i. e., we aim to predict the next most likely links of the network given the current state.  ...  In particular, we investigate link prediction via ASP based on node proximity and its enhancement with background knowledge, in order to test intuitions that common features, e. g., a common educational  ...  knowledge to predict future links) in a social interaction network.  ... 
doi:10.3389/fdata.2019.00015 pmid:33693338 pmcid:PMC7931864 fatcat:bbxfiwnrdfhkfaohwbjambq55e

AN INFLUENTIAL NODE METRICS APPROACH FOR QUANTIFYING LINK ANALYSIS IN SOCIAL NETWORK

Rohini A
2020 JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES  
A weight-based centrality of links is proposed to determine the strong ties in the pair of nodes. The connectivity of link values is used to predict the binding of ties in the network.  ...  The social network analysis graph theory concept consists of Vertices, (who may be persons or organization) and Edges (relationship of vertices) one to one or one to many relationships between them.  ...  The experiments on the weight value of the links given satisfactory results. The extension of this work is preprocessing the Social Network Analysis and quantifies the accuracy of links.  ... 
doi:10.26782/jmcms.2020.03.00012 fatcat:kn2op5f5knfzrfk2vjw4dhxy7u

Comparison Analysis of Link Prediction Algorithms in Social Network

Sahil Gupta, Shalini Pandey, K.K.Shukla K.K.Shukla
2015 International Journal of Computer Applications  
Given a social network graph in which a node represents a user and an edge represents the relationship between the users, link prediction algorithm predicts the possible new relationships that can be created  ...  Social Network depicts the relationship like friendship, common interests etc. among various individuals. Social Network Analysis deals with analysis of these social relationships.  ...  Link prediction is not only used in the field of social network but can also be used to find persons for a certain job profile.  ... 
doi:10.5120/19624-1502 fatcat:enhyqk66szecfbs3s74hkbkw3q

Newton's Gravitational Law for Link Prediction in Social Networks [chapter]

Akanda Wahid -Ul- Ashraf, Marcin Budka, Katarzyna Musial-Gabrys
2017 Studies in Computational Intelligence  
Link prediction is an important research area in network science due to a wide range of real-world application. There are a number of link prediction methods.  ...  Although this law deals with physical bodies, based on our intuition and empirical results we found that this could also work in networks, and especially in social networks.  ...  In social networks, age, location, preferences etc. could be used as basis on which people make friends [40] . 4.  ... 
doi:10.1007/978-3-319-72150-7_8 fatcat:xfgnlhwvk5h4dodmbprl6ub2lm

Research on the Link Prediction Model of Dynamic Multiplex Social Network Based on Improved Graph Representation Learning (December 2020)

Tianyu Xia, Yijun Gu, Dechun Yin
2020 IEEE Access  
This article studied the dynamic graph representation learning so as to put forward an improved link prediction model in dynamic social network.  ...  In the natural and social systems of the real world, various network can be seen everywhere. The world where people live can be seen as a combination of network with different dimensions.  ...  ACKNOWLEDGMENT The authors would like to thank the reviewers for their suggestions which helped in improving the quality of the article.  ... 
doi:10.1109/access.2020.3046526 fatcat:truu6tm2lbhp7p55wnuohg7wla

Behavioral Link Analytics on Heterogeneous Human Interaction Networks

Martin Atzmueller
2020 International Journal of Transdisciplinary Artificial Intelligence  
The analysis is performed on a real-world dataset capturing networks of proximity interactions coupled with self-report questionnaires about preferences and perception of those interactions.  ...  This paper investigates face-to-face as well as socio-spatial interaction networks for modeling user interactions from three perspectives: We analyze preferences and perceptions of human social interactions  ...  In that way, we can estimate the predictability between source and target networks with respect to the contained sets of edges, which directly reflect the respective interactions.  ... 
doi:10.35708/tai1869-126248 fatcat:adukg5ip2vazbahzbutw4ulfim

Jointly Predicting Links and Inferring Attributes using a Social-Attribute Network (SAN) [article]

Neil Zhenqiang Gong, Ameet Talwalkar, Lester Mackey, Ling Huang, Eui Chul Richard Shin, Emil Stefanov, Elaine Shi, Dawn Song
2012 arXiv   pre-print
In this paper, we extend the SAN framework with several leading supervised and unsupervised link prediction algorithms and demonstrate performance improvement for each algorithm on both link prediction  ...  Recently, Yin et al. proposed Social-Attribute Network (SAN), an attribute-augmented social network, to integrate network structure and node attributes to perform both link prediction and attribute inference  ...  ., the logistic function) to map a given set of attributes for each edge (e.g., edge age) into the real-valued edge weights of the SAN model.  ... 
arXiv:1112.3265v9 fatcat:fh2lf5njtveapf7bzim5pky6ke

Improving individual predictions using social networks assortativity

Dounia Mulders, Cyril de Bodt, Johannes Bjelland, Alex Sandy Pentland, Michel Verleysen, Yves-Alexandre de Montjoye
2017 2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM)  
Social networks are known to be assortative with respect to many attributes, such as age, weight, wealth, level of education, ethnicity and gender.  ...  In this case, individual predictions with 75% accuracy are improved by up to 3%.  ...  . link) in the social network.  ... 
doi:10.1109/wsom.2017.8020023 dblp:conf/wsom/MuldersBBPVM17 fatcat:sb2u6lxvonbczncmsz4cbfhm6e

Supervised Random Walks: Predicting and Recommending Links in Social Networks [article]

L. Backstrom, J. Leskovec
2010 arXiv   pre-print
Predicting the occurrence of links is a fundamental problem in networks.  ...  In the link prediction problem we are given a snapshot of a network and would like to infer which interactions among existing members are likely to occur in the near future or which existing interactions  ...  Research was in-part supported by NSF CNS-1010921, NSF IIS-1016909, AFRL FA8650-10-C-7058, Albert Yu & Mary Bechmann Foundation, IBM, Lightspeed, Microsoft and Yahoo.  ... 
arXiv:1011.4071v1 fatcat:e3rkkcrhirgxvcixmhscxmxpxe
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