| 書目名稱 | Temporal Patterns of Communication in Social Networks | | 編輯 | Giovanna Miritello | | 視頻video | http://file.papertrans.cn/903/902973/902973.mp4 | | 概述 | Nominated by Universidad Carlos III de Madrid as an outstanding Ph.D. thesis.Reveals new and unexpected features of how complex social networks develop over time.Based on data mining of massive record | | 叢書名稱 | Springer Theses | | 圖書封面 |  | | 描述 | The main interest of this research has been in understanding and characterizing large networks of human interactions as continuously changing objects. In fact, although many real social networks are dynamic networks whose elements and properties continuously change over time, traditional approaches to social network analysis are essentially static, thus neglecting all temporal aspects. Specifically, we have investigated the role that temporal patterns of human interaction play in three main fields of social network analysis and data mining: characterization of time (or attention) allocation in social networks, prediction of link decay/persistence, and information spreading. In order to address this we analyzed large anonymized data sets of phone call communication traces over long periods of time. Access to these observations was granted by Telefonica Research, Spain. The findings that emerge from our research indicate that the observed heterogeneities and correlations of human temporal patterns of interaction significantly affect the traditional view of social networks, shifting from a very steady to a highly complex entity. Since structure and dynamics are tightly coupled, they c | | 出版日期 | Book 2013 | | 關(guān)鍵詞 | Analysis of Social Networks; Handling and Mining Massive Datasets; Human Communication Patterns; Mathem | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-00110-4 | | isbn_softcover | 978-3-319-03341-9 | | isbn_ebook | 978-3-319-00110-4Series ISSN 2190-5053 Series E-ISSN 2190-5061 | | issn_series | 2190-5053 | | copyright | Springer International Publishing Switzerland 2013 |
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