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03633nam a22005055i 4500 |
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978-3-319-19003-7 |
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150528s2015 gw | s |||| 0|eng d |
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|a 9783319190037
|9 978-3-319-19003-7
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|a 10.1007/978-3-319-19003-7
|2 doi
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|a QA76.9.D343
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|a UNF
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|a COM021030
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|a 006.312
|2 23
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|a Applications of Social Media and Social Network Analysis
|h [electronic resource] /
|c edited by Przemysław Kazienko, Nitesh Chawla.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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|a XIII, 240 p. 123 illus., 37 illus. in color.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
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|a Lecture Notes in Social Networks,
|x 2190-5428
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|a A Node-Centric Reputation Computation Algorithm on Online Social Networks -- Measuring Centralities for Transportation Networks Beyond Structures -- Indifferent Attachment: The Role of Degree in Ranking Friends -- Analyzing the Social Networks of Contributors in Open Source Software Community -- Precise Modeling Rumor Propagation and Control Strategy on Social Networks -- Studying Graph Dynamics Through Intrinsic Time Based Diffusion Analysis -- A Learning Based Approach for Real-time Emotion Classification of Tweets -- A New Linguistic Approach to Assess the Opinion of Users in Social Network Environments -- Visual Analysis of Topical Evolution in Unstructured Text: Design and Evaluation of TopicFlow -- Explaining Scientic and Technical Emergence Forecasting -- Combining Social, Audiovisual and Experiment Content for Enhanced Cultural Experiences -- Social Network Analysis for Biometric Template Protection.
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|a This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to communities of open source software developers, biometric template generation as well as analysis of user behavior within heterogeneous environments of cultural educational centers. Addressing these challenging applications is what makes this edited volume of interest to researchers and students focused on social media and social network analysis.
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|a Computer science.
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|a Data mining.
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|a Application software.
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|a Physics.
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|a Computer Science.
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|a Data Mining and Knowledge Discovery.
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|a Complex Networks.
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|a Computer Appl. in Social and Behavioral Sciences.
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|a Kazienko, Przemysław.
|e editor.
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|a Chawla, Nitesh.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783319190020
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|a Lecture Notes in Social Networks,
|x 2190-5428
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856 |
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|u http://dx.doi.org/10.1007/978-3-319-19003-7
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-SCS
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950 |
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|a Computer Science (Springer-11645)
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