計算社会科学入門(電子書籍版)

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計算社会科学とは、人間の相互関係によって成り立つ社会をデータに基づいて解明していく学問である。この学問分野はコンピュータサイエンスや社会科学など様々な分野の研究者により進められている学際分野であり、研究を行うための基礎学問も多岐にわたり、すべてに精通することは難しい。そこで本書は、計算社会科学を俯瞰的に捉え、主に技術的な側面から「計算社会科学とは何か」を紹介すべく企画された。

目次

  • 表紙
  • まえがき
  • 執筆者一覧
  • 目次
  • 第1章 計算社会科学とは
  • 1.1 はじめに
  • 1.2 計算社会科学の誕生
  • 1.3 計算社会科学の方法論
  • 1.4 ビッグデータ分析
  • 1.5 デジタル調査と実験
  • 1.6 計算モデルとシミュレーション
  • 1.7 おわりに
  • 参考文献
  • 第2章 Web調査
  • 2.1 本章の概要
  • 2.2 調査 : そのメリットとデメリット
  • 2.3 Web調査 : そのメリットとデメリット
  • 2.4 調査における倫理
  • 2.5 Web調査のメリットを生かせる発展的な調査手法
  • 2.6 調査で得られるデータに関する留意点
  • 2.7 計算社会科学研究におけるWeb調査の活用事例
  • 2.8 発展的情報収集のための参考文献
  • 参考文献
  • 第3章 デジタル実験
  • 3.1 実験の利点と限界
  • 3.2 デジタル実験の特長
  • 3.3 デジタル実験の実際
  • 3.4 ブラウザアドオンを使ったデジタル実験
  • 3.5 スマートフォンアプリ使ったデジタル実験
  • 3.6 ソーシャルメディアを用いたフィールド実験
  • 3.7 デジタル実験の注意点
  • 3.8 今後の展望
  • 参考文献
  • 第4章 データ収集・公開データセット
  • 4.1 はじめに
  • 4.2 研究データとは
  • 4.3 公開データの探索と紹介
  • 4.4 データの収集
  • 4.5 データの公開
  • 4.6 データの収集・活用・公開の実例
  • 4.7 データの倫理
  • 4.8 おわりに
  • 参考文献
  • 第5章 ネットワーク
  • 5.1 ネットワーク分析概要
  • 5.2 ネットワークデータの基礎知識
  • 5.3 ネットワークの特徴分析
  • 5.4 ノードの特徴分析
  • 5.5 コミュニティ抽出
  • 5.6 情報の伝播
  • 参考文献
  • 第6章 テキスト分析 : データとしてのテキスト
  • 6.1 はじめに
  • 6.2 データとしてのテキストの例
  • 6.3 量的テキスト分析の特徴
  • 6.4 テキストの前処理
  • 6.5 テキスト分析の方法 : 概観
  • 6.6 テキスト分析の研究例
  • 6.7 おわりに
  • 参考文献
  • 第7章 ソーシャルデータ分析のための教師あり機械学習
  • 7.1 計算社会科学と機械学習
  • 7.2 代表的な教師あり機械学習
  • 7.3 教師データの前処理
  • 7.4 予測精度の評価
  • 7.5 機械学習を用いた個人の属性推定の実例
  • 7.6 まとめと留意点
  • 参考文献
  • 第8章 社会シミュレーション
  • 8.1 社会シミュレーションの概要
  • 8.2 社会シミュレーションの歴史
  • 8.3 代表的な研究の紹介
  • 8.4 社会シミュレーションモデルの表現と実装
  • 8.5 社会シミュレーションの事例
  • 8.6 批判
  • 参考文献
  • 第9章 統計モデリング
  • 9.1 はじめに
  • 9.2 統計モデル
  • 9.3 行動ビッグデータの性質
  • 9.4 統計モデリングの例
  • 9.5 行動ビッグデータを用いた統計モデリングの研究事例
  • 9.6 おわりに
  • 参考文献
  • 第10章 社会物理
  • 10.1 社会物理学とは
  • 10.2 磁性物理学と社会 : イジングモデル
  • 10.3 意見の運動方程式 : オピニオンダイナミクス
  • 10.4 社会のシミュレーション
  • 10.5 ヒット現象の解析
  • 10.6 まとめ
  • 参考文献
  • 第11章 計算社会科学における倫理
  • 11.1 はじめに
  • 11.2 科学研究で要請される倫理
  • 11.3 計算社会科学の何が特有か
  • 11.4 研究を倫理的に評価する
  • 11.5 データ倫理:ビッグデータの誘惑と懸念
  • 11.6 データをめぐる懸念にどう対処するか
  • 11.7 計算社会科学における倫理
  • 参考文献
  • 第12章 計算社会科学の今後の展望と課題
  • 12.1 はじめに
  • 12.2 計算社会科学の定義
  • 12.3 計算社会科学の課題
  • 12.4 おわりに
  • 参考文献
  • 索引
  • 奥付

この書籍の参考文献

参考文献のリンクは、リンク先の都合等により正しく表示されない場合がありますので、あらかじめご了承下さい。

本参考文献は電子書籍掲載内容を元にしております。

第1章 計算社会科学とは

P.24 掲載の参考文献
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第2章 Web調査

P.49 掲載の参考文献
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第3章 デジタル実験

P.74 掲載の参考文献
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第4章 データ収集・公開データセット

P.102 掲載の参考文献
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[10] 佐藤翔, 吉田光男「日本の学協会誌掲載論文のオルトメトリクス付与状況」, 『情報知識学会誌』, 27 (1), 2017, 23-42.
 
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第5章 ネットワーク

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第6章 テキスト分析 : データとしてのテキスト

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第7章 ソーシャルデータ分析のための教師あり機械学習

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第8章 社会シミュレーション

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第9章 統計モデリング

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第10章 社会物理

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第11章 計算社会科学における倫理

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[13] Greene, T., G. Shmueli, S. Ray, J. Fell, "Adjusting to the GDPR : The Impact on Data Scientists and Behavioral Researchers", Big Data, 7 (3), 2019, 140-162. DOI : 10.1089/big.2018.0176
 
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[15] Harris, R., Rigor Mortis : How Sloppy Science Creates Worthless Cures, Crushed Hope, and Wastes Billions, Basic Books, 2017. (寺町朋子訳『生命科学クライシス : 新薬開発の危ない現場』, 白揚社, 2019.)
 
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[22] Ritchie, S., Science Fictions : Exposing Fraud, Bias, Negligence and Hype in Science, Bodley Head, 2020.
 
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第12章 計算社会科学の今後の展望と課題

P.296 掲載の参考文献
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