Predicting signs and directions of links in online social networks

Chowdhury, Shadman Sakib; Khan, Md. Safayet

dc.contributor.author	Chowdhury, Shadman Sakib
dc.contributor.author	Khan, Md. Safayet
dc.date.accessioned	2021-09-09T08:49:55Z
dc.date.available	2021-09-09T08:49:55Z
dc.date.issued	2013-11-15
dc.identifier.citation	[1] "Data mining Concepts and techniques" by Jiawei Han and MichelineKamber [2] "Computational social network analysis" by Ajith Abraham, Aboul-Ella Hassanien, Vaclav Snasel [3] Teng, Chun-Yuen, Yu-Ru Lin, and Lada A. Adamic. "Recipe recommendation using ingredient networks." Proceedings of the 3rd Annual ACM Web Science Conference. ACM, 2012 [4] L, Linyuan, and Tao Zhou. "Link prediction in complex networks: A survey."Physica A: Statistical [5] Bollen, Johan, et al. "Happiness is assortative in online social net- works."Arti cial life 17.3 (2011): 237-251 [6] Backstrom, Lars, and Jure Leskovec. "Supervised random walks: predicting and recommending links in social networks." Proceedings of the fourth ACM international conference on Web search and data mining. ACM, 2011 [7] Asur, Sitaram, and Bernardo A. Huberman. "Predicting the future with social media." Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on. Vol. 1. IEEE, 2010 [8] Liben?Nowell, David, and Jon Kleinberg. "The link?prediction problem for social networks." Journal of the American society for information science and technology 58.7 (2007): 1019-1031 [9] Gubichev, Andrey, et al. "Fast and accurate estimation of shortest paths in large graphs." Proceedings of the 19th ACM international conference on Information and knowledge management. ACM, 2010 [10] Menon, Aditya Krishna, and Charles Elkan. "Link prediction via matrix factorization." Machine Learning and Knowledge Discovery in Databases. Springer Berlin Heidelberg, 2011. 437-452 39 Bibliography 40 [11] Fortunato, Santo. "Community detection in graphs." Physics Reports 486.3 (2010): 75-174 [12] Leskovec, Jure, Daniel Huttenlocher, and Jon Kleinberg. "Signed networks in social media." Proceedings of the 28th international conference on Human factors in computing systems. ACM, 2010 [13] Leskovec, Jure, Daniel Huttenlocher, and Jon Kleinberg. "Predicting positive and negative links in online social networks." Proceedings of the 19th international conference on World wide web. ACM, 2010	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/926
dc.description	Supervised by Md. Mohiuddin Khan Assistant Professor, And Co-supervised by: Mahmud Hasan, Assistant Professor, Department of Computer Science and Engineering (CSE) Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh.	en_US
dc.description.abstract	Studying online social networks gives us a new way to visualize the network data. The relations between the users in the social networks can be de ned as positive and negative where positive means friendship and negative relations means antag- onism. Signs in the social networks are important because the attitude of one user toward another user can be estimated from evidence provided by their common relationships and also other members surrounded in the speci c social network. We studied how the relationships can be denoted by the signs. For that purpose we need to predict the sign (relationship type) between two users where the users can be represented by the nodes and their relationship can be represented by signed edges. Again implementing triad and a new theme quad has been implemented for better demonstration to predict the signs and directions between actors of social networks.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.title	Predicting signs and directions of links in online social networks	en_US
dc.type	Thesis	en_US