Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Veronika Solopova"'
Publikováno v:
Journal of Open Humanities Data, Vol 7 (2021)
We provide a new text corpus from the social medium Telegram, which is rich in indirect forms of divisive speech. We scraped all messages from one channel of Donald Trump supporters, covering a large part of his presidency, from late 2016 until Janua
Externí odkaz:
https://doaj.org/article/58541c8d46504e4e8d13e4cc7191b57f
Publikováno v:
Journal of Open Humanities Data, Vol 7 (2021)
Harmful language is frequent in social media, in particular in spaces which are considered anonymous and/or allow free participation. In this paper, we analyze the language in a Telegram channel populated by followers of former US President Donald Tr
Externí odkaz:
https://doaj.org/article/91eb68fb1b884ec3b3db2a9498460bac
Publikováno v:
Datenbank-Spektrum. 23:5-14
The full-scale conflict between the Russian Federation and Ukraine generated an unprecedented amount of news articles and social media data reflecting opposing ideologies and narratives. These polarized campaigns have led to mutual accusations of mis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::632a26eed39f0e4a95b97bd1ae140d8b
https://doi.org/10.1007/s13222-023-00437-2
https://doi.org/10.1007/s13222-023-00437-2
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031148408
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7975fa75fcba3a465244d6a8c0d65808
https://doi.org/10.1007/978-3-031-14841-5_35
https://doi.org/10.1007/978-3-031-14841-5_35
Publikováno v:
Information and Communication Technologies in Education, Research, and Industrial Applications ISBN: 9783031208331
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83e571b39242d4f5d2c6a853d8ffd988
https://doi.org/10.1007/978-3-031-20834-8_5
https://doi.org/10.1007/978-3-031-20834-8_5
Publikováno v:
2021 ISCA Symposium on Security and Privacy in Speech Communication.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c23a2a72cc4beded947c6bfd89b043d
https://doi.org/10.21437/spsc.2021-10
https://doi.org/10.21437/spsc.2021-10
Publikováno v:
EMNLP (Findings)
The performance of standard coreference resolution is known to drop significantly on Twitter texts. We improve the performance of the (Lee et al., 2018) system, which is originally trained on OntoNotes, by retraining on manually-annotated Twitter con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87e078293ab16af9884ad19eb7a86455
https://doi.org/10.18653/v1/2020.findings-emnlp.222
https://doi.org/10.18653/v1/2020.findings-emnlp.222