Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Aleksander Wawer"'
Autor:
Justyna Sarzyńska-Wawer, Krzysztof Hanusz, Aleksandra Pawlak, Julia Szymanowska, Aleksander Wawer
Publikováno v:
Journal of Intelligence, Vol 11, Iss 4, p 69 (2023)
Lying is essential to social communication. Despite years of research, its detection still poses many challenges. This is partly because some individuals are perceived as truthful and reliable, even when lying. However, relatively little is known abo
Externí odkaz:
https://doaj.org/article/77ef110b987547e0aaf50ea940145aab
Publikováno v:
Applied Sciences, Vol 12, Iss 12, p 5878 (2022)
Lying is an integral part of everyday communication in both written and oral forms. Detecting lies is therefore essential and has many possible applications. Our study aims to investigate the performance of automated lie detection methods, namely the
Externí odkaz:
https://doaj.org/article/2dbc93a9289e46faa8a23cee6e3339c0
Autor:
Izabela Chojnicka, Aleksander Wawer
Publikováno v:
PLoS ONE, Vol 15, Iss 3, p e0229985 (2020)
Individuals with autism spectrum disorder (ASD) demonstrate impairments with pragmatic (social) language, including narrative skills and conversational abilities. We aimed to quantitatively characterize narrative performance in ASD using natural lang
Externí odkaz:
https://doaj.org/article/994cb02a62414840a08a583b791ae8a6
Publikováno v:
Natural Language Engineering. :1-39
Fake news detection is an emerging topic that has attracted a lot of attention among researchers and in the industry. This paper focuses on fake news detection as a text classification problem: on the basis of five publicly available corpora with doc
Autor:
Aleksander Wawer, Izabela Chojnicka
Publikováno v:
International Journal of Language & Communication Disorders. 57:948-962
Deficits in the ability to use language in social contexts, including storytelling skills, are observed across the autism spectrum. Development in machine-learning approaches may contribute to clinical psychology and psychiatry, given its potential t
Autor:
Justyna Sarzynska-Wawer, Aleksandra Pawlak, Julia Szymanowska, Krzysztof Hanusz, Aleksander Wawer
Publikováno v:
PLOS ONE. 18:e0281179
Lying appears in everyday oral and written communication. As a consequence, detecting it on the basis of linguistic analysis is particularly important. Our study aimed to verify whether the differences between true and false statements in terms of co
Publikováno v:
Cognitive Computation. 14:461-473
Detection of mental disorders from textual input is an emerging field for applied machine and deep learning methods. Here, we explore the limits of automated detection of autism spectrum disorder (ASD) and schizophrenia (SCZ). We compared the perform
Publikováno v:
Human Language Technology. Challenges for Computer Science and Linguistics ISBN: 9783031053276
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a488508833a1f2f05c482bb15ee6447
https://doi.org/10.1007/978-3-031-05328-3_18
https://doi.org/10.1007/978-3-031-05328-3_18
Publikováno v:
Current Psychology. 41:4368-4378
Information on personality development (and its linguistic predictors) in the aftermath of a critical life event among depressive patients is relatively limited. The study’s aim was to verify two hypotheses: (1) Participants with depression will us
Autor:
Michał Marcińczuk, Aleksander Wawer
Publikováno v:
Poznan Studies in Contemporary Linguistics. 55:239-269
In this article we discuss the current state-of-the-art for named entity recognition for Polish. We present publicly available resources and open-source tools for named entity recognition. The overview includes various kind of resources, i.e. guideli