Quantifying Reciprocity in Social Networks Export

@inproceedings{zhang:reciprocity, abstract = {In this paper we propose a new reciprocity index for quantifying social relationships based on mobile phone call detail records and Twitter blogs. We use this reciprocity index to measure the level of reciprocity between users. This work is useful for detecting unwanted calls (e.g., spam) and product marketing. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months and Twitter blogs of 460 users collected by the Network Security team at UNT for a period of 12 months. The experimental results show that our model achieves results with high accuracy.}, address = {Los Alamitos, CA, USA}, author = {Zhang, Huiqi and Dantu, Ram and Cangussu, Joao}, booktitle = {2009 International Conference on Computational Science and Engineering (CSE)}, citeulike-article-id = {6111160}, citeulike-linkout-0 = {http://doi.ieeecomputersociety.org/10.1109/CSE.2009.399}, citeulike-linkout-1 = {http://dx.doi.org/10.1109/CSE.2009.399}, doi = {10.1109/CSE.2009.399}, isbn = {978-1-4244-5334-4}, journal = {Computational Science and Engineering, IEEE International Conference on}, keywords = {mit\_reality, reciprocity, social-network-analysis, social-networks, twitter}, location = {Vancouver, BC, Canada}, month = {August}, pages = {1031--1035}, posted-at = {2009-11-13 22:33:36}, priority = {2}, publisher = {IEEE}, title = {Quantifying Reciprocity in Social Networks}, url = {http://dx.doi.org/10.1109/CSE.2009.399}, volume = {4}, year = {2009} }

TY - CONF ID - zhang:reciprocity L3 - citeulike-article-id:6111160 N2 - In this paper we propose a new reciprocity index for quantifying social relationships based on mobile phone call detail records and Twitter blogs. We use this reciprocity index to measure the level of reciprocity between users. This work is useful for detecting unwanted calls (e.g., spam) and product marketing. For validation of our results, we used actual call logs of 100 users collected at MIT by the Reality Mining Project group for a period of 8 months and Twitter blogs of 460 users collected by the Network Security team at UNT for a period of 12 months. The experimental results show that our model achieves results with high accuracy. CY - Vancouver, BC, Canada JF - Computational Science and Engineering, IEEE International Conference on SN - 978-1-4244-5334-4 AD - Los Alamitos, CA, USA EP - 1035 TI - Quantifying Reciprocity in Social Networks PB - IEEE VL - 4 T2 - 2009 International Conference on Computational Science and Engineering (CSE) SP - 1031 KW - mit_reality KW - reciprocity KW - social-network-analysis KW - social-networks KW - twitter AU - Zhang, Huiqi AU - Dantu, Ram AU - Cangussu, Joao PY - 2009/08// UR - http://dx.doi.org/10.1109/CSE.2009.399 ER -