Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge

Jia-Zhen Michelle Chan; Florian Kunneman; Roser Morante Vallejo; Lea Lösch; Teun Zuiderent-Jerak

Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge

Jia-Zhen Michelle Chan^*
, Florian Kunneman
, Roser Morante Vallejo
, Lea Lösch
, Teun Zuiderent-Jerak

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

In this paper we present a procedure to extract posts that contain experiential knowledge from Facebook discussions in Dutch, using automated filtering, manual annotations and machine learning. We define guidelines to annotate experiential knowledge and test them on a subset of the data. After several rounds of (re-) annotations, we come to an inter-annotator agreement of K= 0.69, which reflects the difficulty of the task. We subsequently discuss inclusion and exclusion criteria to cope with the diversity of manifestations of experiential knowledge relevant to guideline development.

Original language	English
Title of host publication	Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task
Place of Publication	Gyeongju, Republic of Korea
Publisher	Association for Computational Linguistics, ACL Anthology
Pages	203-208
Number of pages	6
Publication status	Published - Oct 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 4 Quality Education
SDG 10 Reduced Inequalities

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https://aclanthology.org/2022.smm4h-1.51

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Evidence in Actie: Dynamisch standaardiseren van ervaringskennis en waarden in richtlijnen
Zuiderent-Jerak, T. (Principal Investigator), Timen, A. (Principal Investigator), Syurina, E. (Project Researcher), Kunneman, F. (Project Researcher), Lösch, L. (PhD candidate), Bongers, M. (Project Researcher), Stein, M. L. (Principal Investigator) & Lösch, L. (Project Researcher)
1/09/20 → 1/02/24
Project: Research

Cite this

Chan, J.-Z. M., Kunneman, F., Morante Vallejo, R., Lösch, L., & Zuiderent-Jerak, T. (2022). Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task (pp. 203-208). Association for Computational Linguistics, ACL Anthology. https://aclanthology.org/2022.smm4h-1.51

Chan, Jia-Zhen Michelle ; Kunneman, Florian ; Morante Vallejo, Roser et al. / Leveraging Social Media as a Source for Clinical Guidelines : A Demarcation of Experiential Knowledge. Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task. Gyeongju, Republic of Korea : Association for Computational Linguistics, ACL Anthology, 2022. pp. 203-208

@inproceedings{04050e0e36184dc5be7d82e22ddaa525,

title = "Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge",

abstract = "In this paper we present a procedure to extract posts that contain experiential knowledge from Facebook discussions in Dutch, using automated filtering, manual annotations and machine learning. We define guidelines to annotate experiential knowledge and test them on a subset of the data. After several rounds of (re-) annotations, we come to an inter-annotator agreement of K= 0.69, which reflects the difficulty of the task. We subsequently discuss inclusion and exclusion criteria to cope with the diversity of manifestations of experiential knowledge relevant to guideline development.",

author = "Chan, \{Jia-Zhen Michelle\} and Florian Kunneman and \{Morante Vallejo\}, Roser and Lea L{\"o}sch and Teun Zuiderent-Jerak",

year = "2022",

month = oct,

language = "English",

pages = "203--208",

booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop \& Shared Task",

publisher = "Association for Computational Linguistics, ACL Anthology",

}

Chan, J-ZM, Kunneman, F, Morante Vallejo, R, Lösch, L & Zuiderent-Jerak, T 2022, Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge. in Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task. Association for Computational Linguistics, ACL Anthology, Gyeongju, Republic of Korea, pp. 203-208. <https://aclanthology.org/2022.smm4h-1.51>

Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge. / Chan, Jia-Zhen Michelle; Kunneman, Florian; Morante Vallejo, Roser et al.
Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task. Gyeongju, Republic of Korea: Association for Computational Linguistics, ACL Anthology, 2022. p. 203-208.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Leveraging Social Media as a Source for Clinical Guidelines

T2 - A Demarcation of Experiential Knowledge

AU - Chan, Jia-Zhen Michelle

AU - Kunneman, Florian

AU - Morante Vallejo, Roser

AU - Lösch, Lea

AU - Zuiderent-Jerak, Teun

PY - 2022/10

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N2 - In this paper we present a procedure to extract posts that contain experiential knowledge from Facebook discussions in Dutch, using automated filtering, manual annotations and machine learning. We define guidelines to annotate experiential knowledge and test them on a subset of the data. After several rounds of (re-) annotations, we come to an inter-annotator agreement of K= 0.69, which reflects the difficulty of the task. We subsequently discuss inclusion and exclusion criteria to cope with the diversity of manifestations of experiential knowledge relevant to guideline development.

AB - In this paper we present a procedure to extract posts that contain experiential knowledge from Facebook discussions in Dutch, using automated filtering, manual annotations and machine learning. We define guidelines to annotate experiential knowledge and test them on a subset of the data. After several rounds of (re-) annotations, we come to an inter-annotator agreement of K= 0.69, which reflects the difficulty of the task. We subsequently discuss inclusion and exclusion criteria to cope with the diversity of manifestations of experiential knowledge relevant to guideline development.

M3 - Conference contribution

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EP - 208

BT - Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task

PB - Association for Computational Linguistics, ACL Anthology

CY - Gyeongju, Republic of Korea

ER -

Chan JZM, Kunneman F, Morante Vallejo R, Lösch L , Zuiderent-Jerak T. Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task. Gyeongju, Republic of Korea: Association for Computational Linguistics, ACL Anthology. 2022. p. 203-208 Epub 2022 Oct 12.

Leveraging Social Media as a Source for Clinical Guidelines: A Demarcation of Experiential Knowledge

Abstract

UN SDGs

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Evidence in Actie: Dynamisch standaardiseren van ervaringskennis en waarden in richtlijnen

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