Measuring scholarly impact : methods and practice
著者
書誌事項
Measuring scholarly impact : methods and practice
Springer, c2014
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book is an authoritative handbook of current topics, technologies and methodological approaches that may be used for the study of scholarly impact. The included methods cover a range of fields such as statistical sciences, scientific visualization, network analysis, text mining, and information retrieval. The techniques and tools enable researchers to investigate metric phenomena and to assess scholarly impact in new ways. Each chapter offers an introduction to the selected topic and outlines how the topic, technology or methodological approach may be applied to metrics-related research. Comprehensive and up-to-date, Measuring Scholarly Impact: Methods and Practice is designed for researchers and scholars interested in informetrics, scientometrics, and text mining. The hands-on perspective is also beneficial to advanced-level students in fields from computer science and statistics to information science.
目次
Community detection and visualization of networks with the map equation framework.- Link Prediction.- Network analysis and indicators.- PageRank-related methods for analyzing citation networks.- Systems Life Cycle and its relation with the Triple Helix.- Spatial scientometrics and scholarly impact: A review of recent studies, tools and methods.- Researchers' publication patterns and their use for author disambiguation.- Knowledge integration and diffusion: Measures and mapping of diversity and coherence.- Limited dependent variables models and probabilistic prediction in informetrics.- Text mining with the Stanford CoreNLP.- Topic modeling: Measuring scholarly impact using a topical lens.- The substantive and practical significance of citation impact differences between institutions: Guidelines for the analysis of percentiles using effect sizes and confidence intervals.- Visualizing bibliometric networks.- Replicable science of science studies.
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