Zobrazeno 1 - 10 of 224 pro vyhledávání: '"Steven Bethard"'
1
Engagement with partisan Russian troll tweets during the 2016 U.S. presidential election: a social identity perspective
Autor: Stephen A Rains, Jake Harwood, Yotam Shmargad, Kate Kenski, Kevin Coe, Steven Bethard
Publikováno v: Journal of Communication. 73:38-48
Operatives working for the Russian Internet Research Agency (IRA) infiltrated social media with the goal of disrupting the 2016 U.S. presidential election. We investigate how these operatives or “trolls” leveraged partisan political identities in
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c3413504f5c8d2cda608ded3c090cb94
https://doi.org/10.1093/joc/jqac037
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2
Assessing the Russian Troll Efforts to Sow Discord on Twitter during the 2016 U.S. Election
Autor: Kevin Coe, Kate Kenski, Stephen A. Rains, Steven Bethard, Yotam Shmargad
Publikováno v: Human Communication Research. 47:477-486
Although experts agree that the Russian Internet Research Agency deployed trolls on Twitter to disrupt the 2016 U.S. presidential election, questions remain about the nuances of their efforts. We examined almost 350,000 original tweets made during th
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bfa0589953c2584ffc93280f39f40c2e
https://doi.org/10.1093/hcr/hqab009
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3
Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking for concept normalization
Autor: Kris Brown, Jiacheng Zhang, Steven Bethard, Edmon Begoli, Dongfang Xu, Manoj Gopale
Publikováno v: Journal of the American Medical Informatics Association : JAMIA
Objective Concept normalization, the task of linking phrases in text to concepts in an ontology, is useful for many downstream tasks including relation extraction, information retrieval, etc. We present a generate-and-rank concept normalization syste
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5424a9588722629a5d16b9ed9478cfe8
http://europepmc.org/articles/PMC7566510
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4
Rethinking domain adaptation for machine learning over clinical language
Autor: Egoitz Laparra, Steven Bethard, Timothy A. Miller
Publikováno v: JAMIA Open
Building clinical natural language processing (NLP) systems that work on widely varying data is an absolute necessity because of the expense of obtaining new training data. While domain adaptation research can have a positive impact on this problem,
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70ebafa41816f810a133b1711bcc1e1e
https://doi.org/10.1093/jamiaopen/ooaa010
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8
TEAM-Atreides at SemEval-2022 Task 11: On leveraging data augmentation and ensemble to recognize complex Named Entities in Bangla
Autor: Nazia Tasnim, Md. Istiak Shihab, Asif Shahriyar Sushmit, Steven Bethard, Farig Sadeque
Publikováno v: Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022).
Many areas, such as the biological and healthcare domain, artistic works, and organization names, have nested, overlapping, discontinuous entity mentions that may even be syntactically or semantically ambiguous in practice. Traditional sequence taggi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf8047e856d09fd63f40d06c3da7f8dc
https://doi.org/10.18653/v1/2022.semeval-1.209
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