Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Jacob G. Foster"'
Publikováno v:
RSF: The Russell Sage Foundation Journal of the Social Sciences, Vol 10, Iss 5, Pp 165-187 (2024)
We develop a novel application of machine learning and apply it to the interview transcripts from the American Voices Project (N = 1,396), using discourse atom topic modeling to explore social class variation in the centrality of family in adults’
Externí odkaz:
https://doaj.org/article/5bb552f76f704acfb6141c38ec67e252
Publikováno v:
Frontiers in Research Metrics and Analytics, Vol 7 (2022)
This paper proposes a text-mining framework to systematically identify vanishing or newly formed topics in highly interdisciplinary and diverse fields like cognitive science. We apply topic modeling via non-negative matrix factorization to cognitive
Externí odkaz:
https://doaj.org/article/ecc61e3f5b2c4c6d81424bde1f916ead
Autor:
Daril A. Vilhena, Jacob G. Foster, Martin Rosvall, Jevin D. West, James Evans, Carl T. Bergstrom
Publikováno v:
Sociological Science, Vol 1, Iss 15, Pp 221-238 (2014)
Divergent interests, expertise, and language form cultural barriers to communication. No formalism has been available to characterize these “cultural holes.” Here we use information theory to measure cultural holes and demonstrate our formalism i
Externí odkaz:
https://doaj.org/article/a5b2a795b0694955a3d042922d40a126
Publikováno v:
CrimRxiv.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e31fbf87d141aeb8ad48d3faf25a94a
https://doi.org/10.21428/cb6ab371.66b7b893
https://doi.org/10.21428/cb6ab371.66b7b893
Publikováno v:
Annual Review of Anthropology
Annual Review of Anthropology, 2022, 51 (1), pp.419-436. ⟨10.1146/annurev-anthro-012121-012127⟩
Annual Review of Anthropology, 2022, 51 (1), pp.419-436. ⟨10.1146/annurev-anthro-012121-012127⟩
Although anthropology was the first academic discipline to investigate cultural change, many other disciplines have made noteworthy contributions to understanding what influences the adoption of new behaviors. Drawing on a broad, interdisciplinary li
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a8d8cf9cdf72d96c080b7dba89357f8
https://publications.ut-capitole.fr/id/eprint/46333/
https://publications.ut-capitole.fr/id/eprint/46333/
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40fbb424edd8f93dde75fd6aa9217428
https://doi.org/10.1109/bigdata52589.2021.9672040
https://doi.org/10.1109/bigdata52589.2021.9672040
This review systematizes the emerging literature for causal inference using deep neural networks under the potential outcomes framework. It provides an intuitive introduction on how deep learning can be used to estimate/predict heterogeneous treatmen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a53cd398d1a8e2ee5f399e5607aa8ed
https://osf.io/preprints/socarxiv/aeszf
https://osf.io/preprints/socarxiv/aeszf
Autor:
Susan Perry, Marco Smolla, Susan D. Healy, Alecia J. Carter, Erol Akçay, Sabine Nöbel, Jacob G. Foster
Publikováno v:
Philosophical Transactions of the Royal Society B: Biological Sciences
Philosophical Transactions of the Royal Society B: Biological Sciences, Royal Society, The, 2021, vol.376 (n°1828), ⟨10.31235/osf.io/x2acu⟩
Philosophical transactions of the Royal Society of London. Series B, Biological sciences, vol 376, iss 1828
Philosophical Transactions of the Royal Society B: Biological Sciences, Royal Society, The, 2021, vol.376 (n°1828), ⟨10.31235/osf.io/x2acu⟩
Philosophical transactions of the Royal Society of London. Series B, Biological sciences, vol 376, iss 1828
We are grateful to the Templeton World Charity Foundation, Inc. for funding this work and to the Diverse Intelligences research community for valuable conversations around these themes. S. Nöbel acknowledges IAST funding from the French National Res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5782eeee354eced890d975196f13feb7
https://hdl.handle.net/10023/23352
https://hdl.handle.net/10023/23352
Publikováno v:
Am J Public Health
Objectives. To investigate racial/ethnic differences in legal intervention‒related deaths using state-of-the-art topic modeling of law enforcement and coroner text summaries drawn from the 2003–2017 US National Violent Death Reporting System (NVD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af0fdaf9a164db6c242efc35b3086b0b
https://pubmed.ncbi.nlm.nih.gov/33984244
https://pubmed.ncbi.nlm.nih.gov/33984244
Autor:
Alina Arseniev-Koehler, Jacob G. Foster, Ankith Uppunda, Susan D. Cochran, Vickie M. Mays, Kai-Wei Chang
Publikováno v:
NAACL-HLT
Coreference resolution is an important component in analyzing narrative text from administrative data (e.g., clinical or police sources). However, existing coreference models trained on general language corpora suffer from poor transferability due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e92b67b7201104da4490516eeabbf585
http://arxiv.org/abs/2104.14703
http://arxiv.org/abs/2104.14703