Research Article
Behavior of Users Illustrated using Heavy-Tailed Distribution
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 182 - Issue 39 |
| Published: Feb 2019 |
| Authors: Nripesh Trivedi |
10.5120/ijca2019918444
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Nripesh Trivedi . Behavior of Users Illustrated using Heavy-Tailed Distribution. International Journal of Computer Applications. 182, 39 (Feb 2019), 1-2. DOI=10.5120/ijca2019918444
@article{ 10.5120/ijca2019918444,
author = { Nripesh Trivedi },
title = { Behavior of Users Illustrated using Heavy-Tailed Distribution },
journal = { International Journal of Computer Applications },
year = { 2019 },
volume = { 182 },
number = { 39 },
pages = { 1-2 },
doi = { 10.5120/ijca2019918444 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2019
%A Nripesh Trivedi
%T Behavior of Users Illustrated using Heavy-Tailed Distribution%T
%J International Journal of Computer Applications
%V 182
%N 39
%P 1-2
%R 10.5120/ijca2019918444
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Behavior of users on online social services is characterized using heavy-tailed distribution. The assumption in heavy-tailed distribution is that few users are responsible for most of the variation. In this paper, users characterized using heavy-tailed distribution are further characterized according to their activity on the online social service. Further, this characterization of behavior is shown to have similar properties as a trigonometric function,
References
- Trivedi, N., Asamoah, D. A., & Doran, D. (2018). Keep the conversations going: engagement-based customer segmentation on online social service platforms. Information Systems Frontiers, 20(2), 239-257.
- Viswanath, B., Mislove, A., Cha, M., & Gummadi, K. P. (2009). On the Evolution of User Interaction in Facebook. Proceedings of the 2nd ACM Workshop on Online Social Networks - WOSN ’09, 37.
- Anderson, A., Huttenlocher, D., & Kleinberg, J. (2012). Discovering Value from Community Activity on Focused Question Answering Sites : A Case Study of Stack Overflow. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Dscovery and Data Mining, 850–858.
- Kwak, H., Lee, C., Park, H., & Moon, S. (2010). What is Twitter , Social Network or a News Media? The International World Wide Web Conference Committee (IW3C2), 1–10.
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