Medical Discourse and Subjectivity

Grabar, Natalia; Chauveau-Thoumelin, Pierre; Dumonet, Loïc

doi:10.1007/978-3-319-23751-0_3

Cited by 3 publications

(4 citation statements)

References 19 publications

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“…For this reason, MaSanteNet appears to be less suitable for learning classification models that can be used on other forums. Using emotions, uncertainty markers, and medical concepts, Grabar et al 11 obtained F1-measures between 0.91 and 0.95 when classifying forum posts produced by patients and clinical reports produced by medical experts. Our study shows the limits of using these markers in categorizing the patients' discourse and the medical experts' discourse when the text documents are of the same nature (forum posts).…”

Section: Results Interpretationmentioning

confidence: 99%

“…In order to categorize the discourse of medical experts and the discourse of non-experts, the descriptors proposed in Grabar et al 11 have been annotated using the Ogmios platform. 13 This annotation step allows us to include them easily as features in the classification step.…”

Section: Methodsmentioning

confidence: 99%

“…A set of uncertainty words 11 is used to annotate verbs, nouns, adjectives, and even adverbs conveying uncertainty meaning (e.g. to seem, possible, and probably).…”

Section: Methodsmentioning

confidence: 99%

“…They obtained, respectively, the first and the second best results for age and gender on the Spanish partition of PAN 2013 corpus. Grabar et al 11 compared documents written by medical doctors and researchers (clinical reports and scientific literature) with the patient discourse (discussions from health forums). They observed differences in the use of descriptors like uncertainty markers, non-lexical (smileys, repeated punctuations, etc.)…”

Section: Introductionmentioning

confidence: 99%

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Expertise in French health forums

Abdaoui¹,

Azé

Bringay

et al. 2016

Health Informatics J

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More and more health websites hire medical experts (physicians, medical students, experienced volunteers, etc.) and indicate explicitly their medical role in order to notify that they provide high-quality answers. However, medical experts may participate in forum discussions even when their role is not officially indicated. Detecting posts written by medical experts facilitates the quick access to posts that have more chances of being correct and informative. The main objective of this work is to learn classification models that can be used to detect posts written by medical experts in any health forum discussions. Two French health forums have been used to discover the best features and methods for this text categorization task. The obtained results confirm that models learned on appropriate websites may be used efficiently on other websites (more than 98% of F1-measure has been obtained using a Random Forest classifier). A study of misclassified posts highlights the participation of medical experts in forum discussions even if their role is not explicitly indicated.

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Section: Results Interpretationmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…A set of uncertainty words 11 is used to annotate verbs, nouns, adjectives, and even adverbs conveying uncertainty meaning (e.g. to seem, possible, and probably).…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Expertise in French health forums

Abdaoui¹,

Azé

Bringay

et al. 2016

Health Informatics J

Self Cite

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The Lexical Innovations Identification in English-Language Eurointegration Discourse for the Goods Analysis by Comments in E-Commerce Resources

Lytvyn

Danylyk

Bublyk

et al. 2021

2021 IEEE 16th International Conference on Computer Sciences and Information Technologies (CSIT)

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Self-mention and uncertain communication in theBritish Medical Journal(1840–2007): The decrease of subjectivity uncertainty markers

2021

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The communication of a scientific finding as certain or uncertain largely determines whether that information will be translated into practice. In this study, a corpus of 80 articles published in the British Medical Journal for over 167 years (1840–2007) is analysed by focusing on three categories of uncertainty markers, which explicitly reveal a writer’s subjectivity: (1) I/we epistemic verbs; (2) I/we modal verbs; and (3) epistemic non-verbs conveying personal opinions. The quantitative analysis shows their progressive decrease over time, which can be due to several variables, including the evolution of medical knowledge and practice, changes in medical research and within the scientific community, and more stringent guidelines for the scientific writing (regarding types of articles, their structure and rhetorical style).

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Medical Discourse and Subjectivity

Cited by 3 publications

References 19 publications

Expertise in French health forums

Expertise in French health forums

The Lexical Innovations Identification in English-Language Eurointegration Discourse for the Goods Analysis by Comments in E-Commerce Resources

Self-mention and uncertain communication in theBritish Medical Journal(1840–2007): The decrease of subjectivity uncertainty markers

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