コンピュータ社会科学における説明と予測の統合

Jake M Hofman¹, Duncan J Watts^2,3,4, Susan Athey⁵

¹Microsoft Research, New York, NY, USA. jmh@microsoft.com.

Nature

|July 1, 2021

まとめ

計算社会科学は様々な分野と方法を統合しています. この観点では,より堅固な科学的発見のための説明的および予測的アプローチを組み合わせることを提案しています.

科学分野:

コンピュータ社会科学
分野間の研究
データサイエンス

背景:

コンピューティング社会科学は大規模なデジタルデータセットと先進的な分析技術を含んでいます
異なる方法論を持つ様々な科学分野の収束を表しています.
既存のアプローチはしばしば説明や予測に焦点を当てており,潜在的な断片化につながります.

研究の目的:

計算型社会科学のアプローチの違いを明らかにする.
多様な方法論のための生産的な統合戦略を提案する
研究における説明モデルと予測モデルの組み合わせを提唱する.

主な方法:

研究活動を分析するためのスキーマの開発.
説明 (因果関係) と予測 (結果テスト) の次元に沿って研究を分類する.
予測と説明の両方を組み合わせた"統合的モデリング"の提唱.

主要な成果:

研究の優先順位を評価するための二次元図表 (説明と予測).
説明的および予測的研究目標の互補性を特定する.
統一されたアプローチとして"統合的モデリング"の提案

結論:

コンピューティング社会科学は,多様な学問的視点とコンピューティング方法の統合から利益を得ています.
説明と予測を組み合わせたバランスの取れたアプローチは科学的厳格性を高めます
統合的モデリングは,より包括的で有力な計算社会科学研究への道を開きます.

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