Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

1-2016

Abstract

We investigate the differences between how some of the fundamental principles of network formation apply among offline friends and how they apply among online friends on Twitter. We consider three fundamental principles of network formation proposed by Schaefer et al.: reciprocity, popularity, and triadic closure. Overall, we discover that these principles mainly apply to offline friends on Twitter. Based on how these principles apply to offline versus online friends, we formulate rules to predict offline friendship on Twitter. We compare our algorithm with popular machine learning algorithms and Xiewei’s random walk algorithm. Our algorithm beats the machine learning algorithms on average by 15 % in terms of f-score. Although our algorithm loses 6 % to Xiewei’s random walk algorithm in terms of f-score, it still performs well (f-score above 70 %), and it reduces prediction time complexity from O(n2)to O(n).

Keywords

Network formation, Offline friends, Online friends, Twitter Social network, Offline friends prediction, Machine learning, Offline online

Discipline

Databases and Information Systems | Social Media

Research Areas

Data Science and Engineering

Publication

Advances in Network Science: 12th International Conference and School, NetSci-X 2016, Wroclaw, Poland, January 11-13, 2016, Proceedings

Volume

9564

First Page

169

Last Page

177

ISBN

9783319283609

Identifier

10.1007/978-3-319-28361-6_14

Publisher

Springer

City or Country

Cham

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1007/978-3-319-28361-6_14

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