外国人は歓迎されますか? 隠された意味論分析 (LSA) を用いて,ドイツのマスメディアの議論の変化を分類する
Arianna Haviv Zehner1, Marco Fölsch1, Natalja Menold1
1Institute for Sociology, Dresden University of Technology, Dresden, Germany.
PloS one
|February 13, 2026
まとめ
隠された意味論分析 (LSA) は,ドイツにおける外国人統合に関するメディアの議論の進化を明らかにしています. 社会的統合に関する言及は増加したが,感情分析はポジティブな枠組ではなく中立的な枠組を示し,他のトピックは否定的なバイアスを反映している.
科学分野:
- コンピューティング社会科学
- メディア研究 メディア研究
- コンピュータ言語学 コンピュータ言語学
背景:
- 用語流行度やバイアス検出などの伝統的なメディア分析方法には,限界があります.
- 新しいコンピューティングアプローチは,メディア・ディスカースの洞察を深めることを可能にします.
- ドイツの総合社会調査 (GGSS) は,メディア分析のための貴重なデータセットを提供します.
研究 の 目的:
- ドイツのメディアにおける外国人移民と統合に関する議論を分類し,比較する.
- 競合する言説の物語の進化を時間とともに分析する.
- メディア分析における潜在的意味論分析 (LSA) の応用を探求する.
主な方法:
- LSA (Latent Semantic Analysis) を利用し,2006年から2021年にかけてのドイツのメディア記事1万件以上を調査した.
- "Ausländerproblem"や"Ausländerintegration"などの"外国人" (アウスランダー) に関連する複合用語に焦点を当てました.
- 用語は,行政と政策,社会統合,外国人嫌悪,移民制限の4つのディスカースカテゴリーにグループ化されています. 感情分析を行いました.
主要な成果:
- "社会統合"に関する議論は,時を経て,ドイツのメディアでますます一般的になった.
- センチメント分析によると",社会統合"の議論は主に中立だった.
- "外国人嫌悪"や"移民の制限"を含む他のディスカースカテゴリーは,ネガティブなバイアスを示した.
結論:
- 隠された意味論分析 (Latent Semantic Analysis,LSA) は,複雑なメディアの議論を分析するための強力な方法を提供します.
- "社会統合"の議論が増加する中立的な感情は,さらなる調査を正当化します.
- コンピューティング・メソッドはメディアの分析を向上させることができますが,調査データとの文脈化は依然として重要です.
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