%0 Journal Article %1 Chung2014Generalized %A Chung, Kihong %A Baek, Yongjoo %A Kim, Daniel %A Ha, Meesoon %A Jeong, Hawoong %D 2014 %J Physical Review E %K modular-networks, critical-phenomena epidemic-models tricritical-points %N 5 %R 10.1103/physreve.89.052811 %T Generalized epidemic process on modular networks %U http://dx.doi.org/10.1103/physreve.89.052811 %V 89 %X Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.

@article{Chung2014Generalized, abstract = {{Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.}}, added-at = {2019-06-10T14:53:09.000+0200}, archiveprefix = {arXiv}, author = {Chung, Kihong and Baek, Yongjoo and Kim, Daniel and Ha, Meesoon and Jeong, Hawoong}, biburl = {https://www.bibsonomy.org/bibtex/2accf3f2f82b02ef1b5dd45c067697e89/nonancourt}, citeulike-article-id = {12811238}, citeulike-linkout-0 = {http://arxiv.org/abs/1312.0573}, citeulike-linkout-1 = {http://arxiv.org/pdf/1312.0573}, citeulike-linkout-2 = {http://dx.doi.org/10.1103/physreve.89.052811}, day = 21, doi = {10.1103/physreve.89.052811}, eprint = {1312.0573}, interhash = {648ba73277d34444dc9eacd8eaf5d58b}, intrahash = {accf3f2f82b02ef1b5dd45c067697e89}, issn = {1550-2376}, journal = {Physical Review E}, keywords = {modular-networks, critical-phenomena epidemic-models tricritical-points}, month = may, number = 5, posted-at = {2013-12-11 15:01:29}, priority = {2}, timestamp = {2019-08-01T15:37:28.000+0200}, title = {{Generalized epidemic process on modular networks}}, url = {http://dx.doi.org/10.1103/physreve.89.052811}, volume = 89, year = 2014 }