@inproceedings{5b714bc4cfcb48989e1e843475037328,
title = "Analysis of link formation, persistence and dissolution in NetSense data",
abstract = "We study a unique behavioral network data set (based on periodic surveys and on electronic logs of dyadic contact via smartphones) collected at the University of Notre Dame. The participants are a sample of members of the entering class of freshmen in the fall of 2011 whose opinions on a wide variety of political and social issues and activities on campus were regularly recorded - at the beginning and end of each semester - for the first three years of their residence on campus. We create a communication activity network implied by call and text data, and a friendship network based on surveys. Both networks are limited to students participating in the NetSense surveys. We aim at finding student traits and activities on which agreements correlate well with formation and persistence of links while disagreements is highly correlated with non-existence or dissolution of links in the two social networks that we created. Using statistical analysis and machine learning, we observe several traits and activities displaying such correlations, thus being of potential use to predict social network evolution.",
keywords = "NetSense, evolving networks, link persistence, link prediction, social networks",
author = "Ashwin Bahulkar and Szymanski, {Boleslaw K.} and Omar Lizardo and Yuxiao Dong and Yang Yang and Chawla, {Nitesh V.}",
note = "Funding Information: We thank Prof. G. Korniss for beneficial discussions. This work was supported in part by the Army Research Laboratory under Cooperative Agreement Number W911NF-09-2-0053 (the Network Science CTA), by the Office of Naval Research (ONR) grant no. N00014-15-1-2640, by the European Commission under the 7th Framework Programme, Agreement Number 316097, and by the Polish National Science Centre, the decision no. DEC-2013/09/B/ST6/02317. The views and conclusions contained in this document are those of the authors Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 ; Conference date: 18-08-2016 Through 21-08-2016",
year = "2016",
month = nov,
day = "21",
doi = "10.1109/ASONAM.2016.7752391",
language = "English (US)",
series = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1197--1204",
editor = "Ravi Kumar and James Caverlee and Hanghang Tong",
booktitle = "Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016",
address = "United States",
}