数据挖掘创伤:Reddit上网络受害的人工智能辅助定性研究。

IF 2.3 Q1 HEALTH CARE SCIENCES & SERVICES
JMIR infodemiology Pub Date : 2025-09-03 DOI:10.2196/75493
J'Andra Antisdel, Wendy R Miller, Doyle Groves
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引用次数: 0

摘要

背景:网络受害使个人面临许多风险。发展和心理因素可能使一些使用者没有意识到潜在的危险,增加了他们对心理困扰的易感性。尽管存在这种脆弱性,但在医疗保健环境中识别那些有网络受害风险的人的方法有限,探索他们的网络受害经历的研究也是如此。本研究的目的是分析用户如何使用数据挖掘来描述社交媒体平台Reddit (Reddit, Inc)上的网络受害经历。目的:本研究旨在分析和描述Reddit用户如何使用数据挖掘和非请求数据的计算分析来描述和讨论他们的网络受害经历。方法:本计算定性研究使用数据挖掘、词邻接图(WAG)建模和主题分析来分析Reddit用户围绕网络受害的讨论。纳入标准包括2012年至2023年来自r/cyberbullying和r/bullying子版块的帖子。GPT-4 (OpenAI)是一种先进的人工智能语言模型,用于总结帖子并辅助聚类标注。帖子经过审查,删除了不相关的内容和重复的内容。在整个研究过程中,用户保持匿名。结果:共分析了来自3283个Reddit的13381个帖子,其中约5.1% (n=678)来自2012年至2018年,94.9% (n= 12703)来自2019年至2023年。WAG建模方法确定了38个集群,其中35个被认为与网络受害经历有关。排除了两个包含不相关材料的聚类。六个主要主题出现了:(1)心理影响,(2)应对和治疗,(3)在线保护自己,(4)离线保护自己,(5)各种环境下的受害者,(6)寻求意义和理解。结论:该研究强调了数据挖掘和人工智能在分析大型公共数据集进行定性研究方面的有效性。这些方法可以为未来的互联网风险行为、受害和评估策略的研究提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Data Mining Trauma: AI-Assisted Qualitative Study of Cyber Victimization on Reddit.

Data Mining Trauma: AI-Assisted Qualitative Study of Cyber Victimization on Reddit.

Data Mining Trauma: AI-Assisted Qualitative Study of Cyber Victimization on Reddit.

Data Mining Trauma: AI-Assisted Qualitative Study of Cyber Victimization on Reddit.

Background: Cyber victimization exposes individuals to numerous risks. Developmental and psychological factors may leave some users unaware of the potential dangers, increasing their susceptibility to psychological distress. Despite this vulnerability, methods for identifying those at risk of cyber victimization within health care settings are limited, as is research that explores their experiences of cyber victimization. The purpose of this study was to analyze how users describe experiences of cyber victimization on the social media platform Reddit (Reddit, Inc) using data mining.

Objective: This study aimed to analyze and describe how users on Reddit describe and discuss their experience of cyber victimization using data mining and computational analysis of unsolicited data.

Methods: This computational qualitative study used data mining, Word Adjacency Graph (WAG) modeling, and thematic analysis to analyze discussions of Reddit users surrounding cyber victimization. Inclusion criteria included posts from 2012 to 2023 from subreddits r/cyberbullying and r/bullying. GPT-4 (OpenAI), an advanced artificial intelligence language model, summarized posts and assisted in cluster labeling. Posts were reviewed to remove irrelevant content and duplicates. User anonymity was maintained throughout the study.

Results: A total of 13,381 posts from 3283 Reddit were analyzed, with approximately 5.1% (n=678) originating between 2012 and 2018 and 94.9% (n=12,703) from 2019 to 2023. The WAG modeling approach identified 38 clusters, with 35 deemed to be relevant to cyber victimization experiences. Two clusters containing irrelevant material were excluded. Six overarching themes emerged: (1) psychological impact, (2) coping and healing, (3) protecting yourself online, (4) protecting yourself offline, (5) victimization across various settings, and (6) seeking meaning and understanding.

Conclusions: The study highlights the effectiveness of data mining and AI in analyzing large public datasets for qualitative research. These methods can inform future studies on risky internet behavior, victimization, and assessment strategies in health care settings.

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