Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Antonia Godoy-Lorite"'
Publikováno v:
EPJ Data Science, Vol 7, Iss 1, Pp 1-13 (2018)
Abstract Advancing our understanding of human behavior hinges on the ability of theories to unveil the mechanisms underlying such behaviors. Measuring the ability of theories and models to predict unobserved behaviors provides a principled method to
Externí odkaz:
https://doaj.org/article/9417accafd614e4fb631ad949753f4c9
Publikováno v:
PLoS ONE, Vol 11, Iss 1, p e0146113 (2016)
In social networks, individuals constantly drop ties and replace them by new ones in a highly unpredictable fashion. This highly dynamical nature of social ties has important implications for processes such as the spread of information or of epidemic
Externí odkaz:
https://doaj.org/article/b95c4cb3fb5a47d29af8a7e3d9c461e4
Publikováno v:
Journal of Applied Ecology. 58:777-788
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27689bb4b5e0a217d722615aab745e18
https://doi.org/10.1111/1365-2664.13829
https://doi.org/10.1111/1365-2664.13829
Autor:
Antonia Godoy-Lorite, Nick S. Jones
Publikováno v:
Science Advances
Inference method uncovers homophilic network structures and behavior from only a single snapshot of population behavioral data.
Population behavior, like voting and vaccination, depends on the structure of social networks. This structure can dif
Population behavior, like voting and vaccination, depends on the structure of social networks. This structure can dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94e1dabef8fa842239072d41557b0a27
http://hdl.handle.net/10044/1/89390
http://hdl.handle.net/10044/1/89390
Autor:
Maarten Vanhoof, Antonia Godoy-Lorite, Roberto Murcio, Iacopo Iacopini, Natalia Zdanowska, Juste Raimbault, Richard Milton, Elsa Arcaute, Mike Batty
Publikováno v:
NetMob 2019
NetMob 2019, Jul 2019, Oxford, United Kingdom
HAL
NetMob 2019, Jul 2019, Oxford, United Kingdom
HAL
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::733a067376d298c8aa26f589afdbbf46
https://halshs.archives-ouvertes.fr/halshs-02284843
https://halshs.archives-ouvertes.fr/halshs-02284843
Publikováno v:
Business and Consumer Analytics: New Ideas ISBN: 9783030062217
With the overwhelming online products available in recent years, there is an increasing need to filter and deliver relevant personalized advice for users. Recommender systems solve this problem by modeling and predicting individual preferences for a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69a22e89d6fe7981feda97577ab6f053
https://doi.org/10.1007/978-3-030-06222-4_11
https://doi.org/10.1007/978-3-030-06222-4_11
Publikováno v:
EPJ Data Science, Vol 7, Iss 1, Pp 1-13 (2018)
Advancing our understanding of human behavior hinges on the ability of theories to unveil the mechanisms underlying such behaviors. Measuring the ability of theories and models to predict unobserved behaviors provides a principled method to evaluate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5532a107889074f71c625f1e2cf0fdf
https://doi.org/10.1140/epjds/s13688-018-0175-3
https://doi.org/10.1140/epjds/s13688-018-0175-3
Many real-world complex systems are well represented as multilayer networks; predicting interactions in those systems is one of the most pressing problems in predictive network science. To address this challenge, we introduce two stochastic block mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c418472762896cc0a3343d978a0c5df8
Publikováno v:
PLoS ONE
PLoS ONE, Vol 11, Iss 1, p e0146113 (2016)
PLoS ONE, Vol 11, Iss 1, p e0146113 (2016)
In social networks, individuals constantly drop ties and replace them by new ones in a highly unpredictable fashion. This highly dynamical nature of social ties has important implications for processes such as the spread of information or of epidemic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2da30a6766296edf42086e45fbb5bb4
http://arxiv.org/abs/1506.01516
http://arxiv.org/abs/1506.01516