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  <titleInfo>
    <title>Computational social science</title>
    <subTitle>proceedings of the 1st International Conference on New Computational Social Science (ICNCSS 2020), September 25-27, 2020, Guangzhou, China</subTitle>
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    <namePart>International Conference on New Computational Social Science 2020 : Guangzhou, China),</namePart>
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    <namePart>Luo, Wei</namePart>
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  <name type="personal">
    <namePart>Ciurea, Maria</namePart>
    <role>
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  <name type="personal">
    <namePart>Kumar, Santosh</namePart>
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    <dateIssued encoding="marc">2021</dateIssued>
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    <edition>First edition.</edition>
    <issuance>monographic</issuance>
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  <abstract>Selected papers from the International Conference on New Computational Social Science, focusing on the following five aspects: Big data acquisition and analysis, Integration of qualitative research and quantitative research, Sociological Internet experiment research, Application of ABM simulation method in Sociology Research, Research and development of new social computing tools. With the rapid development of information technology, especially sweeping progress in the Internet of things, cloud computing, social networks, social media and big data, social computing, as a data-intensive science, is an emerging field that leverages the capacity to collect and analyze data with an unprecedented breadth, depth and scale. It represents a new computing paradigm and an interdisciplinary field of research and application. A broad comprehension of major topics involved in social computing is important for both scholars and practitioners. This proceedings presents and discusses key concepts and analyzes the state-of-the-art of the field. The conference not only gave insights on social computing, but also affords conduit for future research in the field. Social computing has two distinct trends: One is on the social science issues, such as computational social science, computational sociology, social network analysis, etc; The other is on the use of computational techniques. Finally some new challenges ahead are summarized, including interdisciplinary cooperation and training, big data sharing for scientific data mashups, and privacy protect.</abstract>
  <tableOfContents>1. Big data acquisition and analysis; 2. Integration of qualitative research and quantitative research; 3. Cultural Studies and Humanities; 4. Law and Education; 5.Management and Economics.</tableOfContents>
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  <note type="statement of responsibility">editors: Wei Luo, Maria Ciurea, Santosh Kumar.</note>
  <subject authority="lcsh">
    <topic>Social sciences</topic>
    <topic>Data processing</topic>
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    <topic>Social sciences</topic>
    <topic>Mathematical models</topic>
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    <topic>Social sciences</topic>
    <topic>Methodology</topic>
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  <subject authority="bisacsh">
    <topic>SOCIAL SCIENCE / General</topic>
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  <subject authority="bisacsh">
    <topic>TECHNOLOGY / Engineering / Civil</topic>
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  <classification authority="lcc">H61.3</classification>
  <classification authority="ddc" edition="23">300.285</classification>
  <identifier type="isbn">9781003144977</identifier>
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