Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Richard F. Sear"'
Autor:
Nicholas J. Restrepo, Lucia Illari, Rhys Leahy, Richard F. Sear, Yonatan Lupu, Neil F. Johnson
Publikováno v:
IEEE Access, Vol 10, Pp 2330-2344 (2022)
We reveal hidden social media machinery that has allowed misinformation to thrive among mainstream users, but which is missing from current policy discussions. Specifically, we show how mainstream parenting communities on Facebook have been subject t
Externí odkaz:
https://doaj.org/article/1ae966b73ab346298c834c338c1ba437
Autor:
Richard F. Sear, Nicolas Velasquez, Rhys Leahy, Nicholas Johnson Restrepo, Sara El Oud, Nicholas Gabriel, Yonatan Lupu, Neil F. Johnson
Publikováno v:
IEEE Access, Vol 8, Pp 91886-91893 (2020)
A huge amount of potentially dangerous COVID-19 misinformation is appearing online. Here we use machine learning to quantify COVID-19 content among online opponents of establishment health guidance, in particular vaccinations (“anti-vax”). We fin
Externí odkaz:
https://doaj.org/article/909c5288fd67457a91b853a8d64fab25
Publikováno v:
Advances in Artificial Intelligence and Machine Learning. :257-272
Not only can online hate content spread easily between social media platforms, but its focus can also evolve over time. Machine learning and other artificial intelligence (AI) tools could play a key role in helping human moderators understand how suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2bfe2da2daeb1568f6b501d1043af81f
https://doi.org/10.54364/aaiml.2022.1117
https://doi.org/10.54364/aaiml.2022.1117
Publikováno v:
Advances in Artificial Intelligence and Machine Learning. :191-202
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4b9771e7151e3378ca5afa200cbbd98
https://doi.org/10.54364/aaiml.2021.1112
https://doi.org/10.54364/aaiml.2021.1112
Autor:
Nicholas Gabriel, Yonatan Lupu, Sara El Oud, Nicolas Velasquez, Neil F. Johnson, Richard F. Sear, R. Leahy, Nicholas Johnson Restrepo
Publikováno v:
Ieee Access
IEEE Access
IEEE Access, Vol 8, Pp 91886-91893 (2020)
IEEE Access
IEEE Access, Vol 8, Pp 91886-91893 (2020)
A huge amount of potentially dangerous COVID-19 misinformation is appearing online. Here we use machine learning to quantify COVID-19 content among online opponents of establishment health guidance, in particular vaccinations (“anti-vax”). We fin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::306df02e9cae348f136d8a5177b58a4e
http://europepmc.org/articles/PMC8043493
http://europepmc.org/articles/PMC8043493
Autor:
Nicolas Velasquez, Nicholas Johnson Restrepo, R. Leahy, H. Larson, Neil F. Johnson, Nicholas Gabriel, Richard F. Sear, Yonatan Lupu
Parents - particularly moms - increasingly consult social media for support when taking decisions about their young children, and likely also when advising other family members such as elderly relatives. Minimizing malignant online influences is ther
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77e7679b583df47f8800aa7d33e52e62
Autor:
Nicolas Velasquez, Richard F. Sear, Pedro D. Manrique, N. Johnson Restrepo, L. Illari, Yonatan Lupu, R. Leahy, Neil F. Johnson
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Disrupting the emergence and evolution of potentially violent online extremist movements is a crucial challenge. Extremism research has analyzed such movements in detail, focusing on individual- and movement-level characteristics. But are there syste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71534e264d57b36ed059401d89e58e1c
https://pubmed.ncbi.nlm.nih.gov/34011970
https://pubmed.ncbi.nlm.nih.gov/34011970
Autor:
R. Leahy, Nicholas Gabriel, B. Goldberg, O. K. Jha, Nicolas Velasquez, Yonatan Lupu, Richard F. Sear, N. Johnson Restrepo, Neil F. Johnson
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
We show that malicious COVID-19 content, including racism, disinformation, and misinformation, exploits the multiverse of online hate to spread quickly beyond the control of any individual social media platform. We provide a first mapping of the onli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a213d92d0e4bf85468b1084089fb4b4
https://pubmed.ncbi.nlm.nih.gov/34131158
https://pubmed.ncbi.nlm.nih.gov/34131158