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返信態度の分類に基づくツイート間論述関係の分析
http://hdl.handle.net/2261/54196
1b77b8b3-a2a3-46ae-a611-2dca079825cc
名前 / ファイル | ライセンス | アクション | |
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Item type | 学位論文 / Thesis or Dissertation(1) | |||||
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公開日 | 2013-05-07 | |||||
タイトル | ||||||
タイトル | 返信態度の分類に基づくツイート間論述関係の分析 | |||||
言語 | ||||||
言語 | jpn | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_46ec | |||||
タイプ | thesis | |||||
その他のタイトル | ||||||
その他のタイトル | Analyzing Statement Relations between Tweets from Users'Communications | |||||
著者 |
大和田, 裕亮
× 大和田, 裕亮 |
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著者別名 | ||||||
識別子 | ||||||
識別子 | 10542 | |||||
識別子Scheme | WEKO | |||||
姓名 | ||||||
姓名 | Owada, Yusuke | |||||
著者所属 | ||||||
著者所属 | 東京大学大学院情報理工学系研究科電子情報学専攻 | |||||
著者所属 | ||||||
著者所属 | Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo | |||||
Abstract | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | 東日本大震災では安否確認や被災者支援のためにTwitter が活躍したが,一方で多種多様な情報が流通し,混乱を招いた.我々は,情報の信憑性や重要性を評価するには,ツイート空間の論述的な構造を解析・可視化し,情報の「裏」を取ることが大切だと考えている.本稿では,ツイートの返信および非公式RT(以下,返信・引用と略す)に着目し,ツイート間の論述的な関係を認識する手法を提案する.具体的には,返信・引用ツイートによって,投稿者の「同意」「反論」「疑問」などの態度が表明されると考え,これらの態度を推定する分類器を教師有り学習で構築する.評価実験では,返信・引用ツイートで表明される態度の推定性能を報告する.さらに,本手法が直接的に返信・引用関係のないツイート間の論述的な関係の推定にも応用できることを示し,ツイート間の含意関係認識に基づくアプローチとの比較を行う. | |||||
書誌情報 | 発行日 2013-03-25 | |||||
学位名 | ||||||
学位名 | 修士(情報理工学) | |||||
学位 | ||||||
値 | master | |||||
研究科・専攻 | ||||||
情報理工学系研究科・電子情報学専攻 | ||||||
学位授与年月日 | ||||||
学位授与年月日 | 2013-03-25 |