弱い絆の強さの因果的なテスト
Karthik Rajkumar1, Guillaume Saint-Jacques1, Iavor Bojinov2
1LinkedIn Corporation, 700 E Middlefield Rd, Mountain View, CA 94043, USA.
まとめ
LinkedInの弱い結びつきは 雇用の流動性を高めますが その効果は非線形であり 結びつきの強さを測る方法や 業界によって異なります 適度な弱い絆はしばしば最高の結果をもたらします.
科学分野:
- ソーシャルネットワークの分析
- 労働経済学
- 社会学
背景:
- "弱い絆の強さ"理論は 弱い社会的つながりが 新しい機会へのアクセスを促進することを示唆しています
- LinkedInのようなプロフェッショナルネットワークにおける 弱い結びつきの役割を理解することは キャリアの流動性にとって極めて重要です
- 過去の研究は主に観察データに 基づいており,因果的な証拠は欠けていた.
研究 の 目的:
- LinkedInのプロフェッショナルネットワーク内の仕事の移動性に対する弱い結びつきの因果関係を実験的に調査する.
- 大規模なデジタル環境で 弱い結びつきの理論の強さを検証する
- 絆の強さと仕事の移動性の関係を緩和する要因を特定する.
主な方法:
- 大規模なランダム化実験を分析し 5年間に2000万人以上のLinkedInユーザーを対象にしました
- ユーザーネットワーク内の弱いリンクの流行の操作.
- 新しいタイの形成と仕事の移行を追跡します.
主要な成果:
- 実験的な証拠は 弱い結びつきが 雇用の流動性を高めることを確認し 弱い結びつきの理論の強さを裏付けています
- 弱い結びつきは,仕事の移動性を一定程度まで高め,その後の収益は減少する.
- 弱い結びつきの影響は様々で,中程度に弱い結びつき (相互のつながりによって) と最も弱い結びつき (相互作用の強さによって) が,雇用の移動性に最も大きな影響を及ぼした.
- デジタル産業では弱い結びつきがより効果的であり, 強い結びつきはデジタル化が進まない産業ではより有益であった.
結論:
- 弱い結びつきの強さは線形ではなく,限界利益の減少を示しています.
- 結びつきの強さの定義と測定 (相互作用の強さ vs 相互のつながり) は,仕事の移動性の結果に大きな影響を与えます.
- 雇用の流動性を促進する際の 弱い関係と強い関係の効果は文脈に依存し,産業のデジタル化によって異なる.
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