Applied Network Science: 2021, vol: 6, issue:
- 1)- Asma Azizi, Zhuolin Qu, Bryan Lewis, James Mac Hyman. Generating a heterosexual bipartite network embedded in social network. Applied network science. 2021, 6 (1): 30
Cited : 0Read More - 2)- Erik Braun, Tamás Sebestyén, Tibor Kiss. The strength of domestic production networks: an economic application of the Finn cycling index. Applied network science. 2021, 6 (1): 69Cited : 3Read More
- 3)- Yohei Shida, Hideki Takayasu, Shlomo Havlin, Misako Takayasu. Universal scaling of human flow remain unchanged during the COVID-19 pandemic. Applied network science. 2021, 6 (1): 75Cited : 6Read More
- 4)- Simon Krukowski, Tobias Hecking. Global and local community memberships for estimating spreading capability of nodes in social networks. Applied network science. 2021, 6 (1): 84Cited : 1Read More
- 5)- Alex Stivala, Alessandro Lomi. Testing biological network motif significance with exponential random graph models. Applied network science. 2021, 6 (1): 91Cited : 6Read More
- 6)- Issa Moussa Diop, Chantal Cherifi, Cherif Diallo, Hocine Cherifi. Revealing the component structure of the world air transportation network. Applied network science. 2021, 6 (1): 92Cited : 16Read More
- 7)- Alex Zhao, Kavin Kumaravel, Emanuele Massaro, Marta Gonzalez. A network-based group testing strategy for colleges. Applied network science. 2021, 6 (1): 93Cited : 0Read More
- 8)- Robert Harper, Philip Tee. Balancing capacity and epidemic spread in the global airline network. Applied network science. 2021, 6 (1): 94Cited : 0Read More
- 9)- Satyaki Roy, Preetam Ghosh. Scalable and distributed strategies for socially distanced human mobility. Applied network science. 2021, 6 (1): 95Cited : 3Read More
- 10)- Bojan Evkoski, Nikola Ljubešić, Andraž Pelicon, Igor Mozetič, Petra Kralj Novak. Evolution of topics and hate speech in retweet network communities. Applied network science. 2021, 6 (1): 96Cited : 7Read More
- 11)- Matthew D Nemesure, Thomas M Schwedhelm, Sofia Sacerdote, A James O'Malley, Luke R Rozema, Erika L Moen. A measure of local uniqueness to identify linchpins in a social network with node attributes. Applied network science. 2021, 6: Cited : 13Read More
