データマイニングトラウマ:Redditのサイバー被害に関するAI支援の定性研究
J'Andra Antisdel1,2, Wendy R Miller1, Doyle Groves1
1Center for Enhancing Quality of Life in Chronic Illness, School of Nursing, Indiana University Indianapolis, 600 Barnhill Drive, Indianapolis, IN, 46202, United States, 1 574-703-4472.
JMIR infodemiology
|September 3, 2025
まとめ
この研究では Redditのサイバー被害に関する議論を データマイニングで分析し 心理的影響や対処戦略を含む 6つの重要なテーマを明らかにしました 発見はAIを強調する
科学分野:
- コンピュータ社会科学
- サイバー心理学
- デジタル・ヘルス
背景:
- サイバー攻撃は 特にネット上の危険を 認識していない脆弱な個人に 大きなリスクをもたらします
- 医療機関でリスクのある人を特定し サイバー被害の経験を理解するための研究は限られています
- 心理的・発達的な要因が サイバー脅威に対する感受性や その後の苦痛に影響します
研究 の 目的:
- Redditのソーシャル・メディア・プラットフォームで ユーザーによるサイバー被害体験を分析するためです
- サイバー被害の質的な洞察を得るために データマイニングと要求されていないデータの 計算分析を活用する.
主な方法:
- データマイニングとWord Adjacency Graph (WAG) モデリングを用いた計算的定性研究.
- 2012年から2023年にかけてのRedditの13,381件の投稿を分析した.
- 関連性や匿名の厳格な審査で,ポストサマージとクラスターラベルを GPT-4 が支援しています.
主要な成果:
- WAGモデリングによって生成された38の関連クラスタから35を特定しました.
- 心理的影響,対処/癒し,オンライン/オフラインの保護,被害者の様々な状況,理解を求めるという 6つのテーマが挙げられました.
- 2012-2018 (5.1%) と比較すると,2019-2023年の投稿数 (94.9%) が著しく増加していることは,サイバー被害の議論が進化していることを示しています.
結論:
- データマイニングとAIは,大規模な公開データセットを 質的に分析するための効果的なツールです.
- リスクの高いオンライン行動や 被害者の扱いに関する将来の研究に 役立つかもしれません
- 医療環境におけるサイバー被害の評価戦略を 開発するのに役立ちます
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