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Hits 1 – 15 of 15

1
Cross-media Scientific Research Achievements Query based on Ranking Learning ...
Wang, Benzhi; Liang, Meiyu; Li, Ang. - : arXiv, 2022
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2
Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo
In: J Med Internet Res (2022)
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3
Comparative Anaphora: comparing alternatives
In: Semantics and Linguistic Theory; Proceedings of SALT 31; 484-505 ; 2163-5951 (2022)
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4
Laryngeal Helicobacter pylori Infection and Laryngeal Cancer-Case Series and a Systematic Review
In: Microorganisms ; Volume 9 ; Issue 6 (2021)
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5
Laryngeal Helicobacter pylori Infection and Laryngeal Cancer-Case Series and a Systematic Review
In: Microorganisms (2021)
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6
How fear and collectivism influence public’s preventive intention towards COVID-19 infection: a study based on big data from the social media
In: BMC Public Health (2020)
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7
On the semantic of verbal classifiers
In: CLS 54, 2018 : proceedings of the fifty-fourth annual meeting of the Chicago Linguistic Society (2019), S. 261-269
Leibniz-Zentrum Allgemeine Sprachwissenschaft
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8
A Psycholinguistic Analysis of Responses to Live-Stream Suicides on Social Media
Abstract: Live-stream suicide has become an emerging public health problem in many countries. Regular users are often the first to witness and respond to such suicides, emphasizing their impact on the success of crisis intervention. In order to reduce the likelihood of suicide deaths, this paper aims to use psycholinguistic analysis methods to facilitate automatic detection of negative expressions in responses to live-stream suicides on social media. In this paper, a total of 7212 comments posted on suicide-related messages were collected and analyzed. First, a content analysis was performed to investigate the nature of each comment (negative or not). Second, the simplified Chinese version of the LIWC software was used to extract 75 psycholinguistic features from each comment. Third, based on 19 selected key features, four classification models were established to differentiate between comments with and without negative expressions. Results showed that 19.55% of 7212 comments were recognized as “making negative responses”. Among the four classification models, the highest values of Precision, Recall, F-Measure, and Screening Efficacy reached 69.8%, 85.9%, 72.9%, and 47.1%, respectively. This paper confirms the need for campaigns to reduce negative responses to live-stream suicides and support the use of psycholinguistic analysis methods to improve suicide prevention efforts.
Keyword: Article
URL: https://doi.org/10.3390/ijerph16162848
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719129/
http://www.ncbi.nlm.nih.gov/pubmed/31404975
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9
Data for: Detecting depression stigma on social media: a linguistic analysis ...
Li, Ang. - : Mendeley, 2018
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10
Data for: Detecting depression stigma on social media: a linguistic analysis ...
Li, Ang. - : Mendeley, 2018
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11
Visual Relationship Detection with Internal and External Linguistic Knowledge Distillation ...
Yu, Ruichi; Li, Ang; Morariu, Vlad I.. - : arXiv, 2017
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12
Recognizing Temporal Linguistic Expression Pattern of Individual with Suicide Risk on Social Media ...
Zhang, Aiqi; Li, Ang; Zhu, Tingshao. - : arXiv, 2015
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13
Audiovisual Speech Perception at Various Presentation Levels in Mandarin-Speaking Adults with Cochlear Implants
Liu, Shu-Yu; Yu, Grace; Lee, Li-Ang. - : Public Library of Science, 2014
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14
Environmental Sounds Recognition in Children with Cochlear Implants
Liu, Shu-Yu; Liu, Tien-Chen; Teng, Ya-Ling. - : Public Library of Science, 2013
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15
A Study on the English Translation of Eroticism: The Case of Li Ang’s Sha Fu
In: http://www.inter-disciplinary.net/wp-content/uploads/2009/10/wupaper1.pdf
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