Abstract
This paper investigates the edge sign prediction problem in signed social networks, in which edges have either positive and negative sign. The main goal of this research is to effectively predict the sign of the edges using a newly proposed metric and with an emphasis on reducing the computational cost. In this study a new metric is introduced based on both neighbourhood and distance based link prediction measures. The sign of a connection between two users is subjected to the context of their relations. In the absence of these information, we can utilize topological and structural information of the network. The proposed metric has two components: (i) the importance of a node which is measured by node degree and (ii) the distance between two nodes which is penalizing the first component can be estimated by any shortest path algorithms. The new metric outperforms other sign prediction methods and also is computationally more affordable.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Agrawal, P., Garg, V.K., Narayanam, R.: Link label prediction in signed social networks. In: IJCAI (2013)
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)
Chiang, K.Y., Hsieh, C.J., Natarajan, N., Dhillon, I.S., Tewari, A.: Prediction and clustering in signed networks: a local to global perspective. J. Mach. Learn. Res. 15(1), 1177–1213 (2014)
Chiang, K.Y., Natarajan, N., Tewari, A., Dhillon, I.S.: Exploiting longer cycles for link prediction in signed networks. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, pp. 1157–1162. ACM (2011)
Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: Proceedings of the 13th International Conference on World Wide Web, pp. 403–412. ACM (2004)
Heider, F.: Attitudes and cognitive organization. J. Psychol. 21(1), 107–112 (1946)
Hsieh, C.J., Chiang, K.Y., Dhillon, I.S.: Low rank modeling of signed networks. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 507–515. ACM (2012)
Katz, L.: A new status index derived from sociometric analysis. Psychometrika 18(1), 39–43 (1953)
Kumar, S., Spezzano, F., Subrahmanian, V., Faloutsos, C.: Edge weight prediction in weighted signed networks. In: 2016 IEEE 16th International Conference on Data Mining (ICDM), pp. 221–230. IEEE (2016)
Kunegis, J., Lommatzsch, A., Bauckhage, C.: The slashdot zoo: mining a social network with negative edges. In: Proceedings of the 18th International Conference on World Wide Web, pp. 741–750. ACM (2009)
Kunegis, J., Preusse, J., Schwagereit, F.: What is the added value of negative links in online social networks? In: Proceedings of the 22nd International Conference on World Wide Web, pp. 727–736. ACM (2013)
Leskovec, J., Huttenlocher, D., Kleinberg, J.: Predicting positive and negative links in online social networks. In: Proceedings of the 19th International Conference on World Wide Web, pp. 641–650. ACM (2010)
Leskovec, J., Huttenlocher, D., Kleinberg, J.: Signed networks in social media. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1361–1370. ACM (2010)
Liben-Nowell, D., Kleinberg, J.: The link-prediction problem for social networks. J. Am. Soc. Inf. Sci. Technol. 58(7), 1019–1031 (2007)
Papaoikonomou, A., Kardara, M., Tserpes, K., Varvarigou, T.A.: Predicting edge signs in social networks using frequent subgraph discovery. IEEE Internet Comput. 18(5), 36–43 (2014)
Shahriari, M., Jalili, M.: Ranking nodes in signed social networks. Soc. Netw. Anal. Min. 4(1), 172 (2014)
Shahriary, S.R., Shahriari, M., Noor, R.: A community-based approach for link prediction in signed social networks. Sci. Program. 2015, 5 (2015)
Xu, X., Yuruk, N., Feng, Z., Schweiger, T.A.: Scan: a structural clustering algorithm for networks. In: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 824–833. ACM (2007)
Yang, S.H., Smola, A.J., Long, B., Zha, H., Chang, Y.: Friend or frenemy?: predicting signed ties in social networks. In: Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 555–564. ACM (2012)
Ye, J., Cheng, H., Zhu, Z., Chen, M.: Predicting positive and negative links in signed social networks by transfer learning. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 1477–1488. ACM (2013)
Zhang, T., Jiang, H., Bao, Z., Zhang, Y.: Characterization and edge sign prediction in signed networks. J. Ind. Intell. Inf. 1(1) (2013)
Zhao, J., Lui, J.C., Towsley, D., Guan, X., Zhou, Y.: Empirical analysis of the evolution of follower network: a case study on Douban. In: 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 924–929. IEEE (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Ahmadalinezhad, M., Makrehchi, M. (2018). Sign Prediction in Signed Social Networks Using Inverse Squared Metric. In: Thomson, R., Dancy, C., Hyder, A., Bisgin, H. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2018. Lecture Notes in Computer Science(), vol 10899. Springer, Cham. https://doi.org/10.1007/978-3-319-93372-6_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-93372-6_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-93371-9
Online ISBN: 978-3-319-93372-6
eBook Packages: Computer ScienceComputer Science (R0)