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收集移民在脸书上的帖子:以文本即数据的方法考量伦理措施。

Collecting migrants' Facebook posts: Accounting for ethical measures in a text-as-data approach.

作者信息

Dedecek Gertz Helena

机构信息

Department of Intercultural Education Research, Faculty of Education, Hamburg University, Hamburg, Germany.

出版信息

Front Sociol. 2023 Jan 9;7:932908. doi: 10.3389/fsoc.2022.932908. eCollection 2022.

DOI:10.3389/fsoc.2022.932908
PMID:36698753
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9868646/
Abstract

Based on the heuristics proposed by Helen Nissenbaum to assess ethical issues surrounding research using new technologies, this paper discusses the ethics of the collection and analysis of migrants' digital traces for academic research purposes. Concretely, this paper is grounded on an empirical research that applies a topic modeling approach to a large dataset of migrants' posts written on Facebook groups. After discussing the nine aspects proposed by Nissenbaum, the paper contends that while researchers strive to comply with ethical measures by, for instance, asking adequate questions and protecting the collected data, the lack of transparency of social networking sites is harmful to critical social sciences and can hamper findings that contribute to understanding migratory patterns and decisions.

摘要

基于海伦·尼森鲍姆提出的用于评估围绕使用新技术进行研究的伦理问题的启发法,本文讨论了出于学术研究目的收集和分析移民数字痕迹的伦理问题。具体而言,本文基于一项实证研究,该研究将主题建模方法应用于在脸书群组上撰写的大量移民帖子数据集。在讨论了尼森鲍姆提出的九个方面后,本文认为,虽然研究人员努力通过例如提出适当问题和保护所收集的数据来遵守伦理措施,但社交网站缺乏透明度对批判性社会科学有害,并且可能妨碍有助于理解移民模式和决策的研究结果。

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本文引用的文献

1
Multilingual topic modeling for tracking COVID-19 trends based on Facebook data analysis.基于Facebook数据分析的多语言主题建模用于追踪COVID-19趋势
Appl Intell (Dordr). 2021;51(5):3052-3073. doi: 10.1007/s10489-020-02033-3. Epub 2021 Feb 13.