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Titlebook: Big Data Factories; Collaborative Approa Sorin Adam Matei,Nicolas Jullien,Sean P. Goggins Book 2017 Springer International Publishing AG 20

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31#
發(fā)表于 2025-3-26 23:03:21 | 只看該作者
Democratizing Data Science: The Community Data Science Workshops and Classesists with the skills necessary to extract business value from burgeoning datasets created by online communities like Facebook, Twitter, and LinkedIn. This model of data science—professional data scientists mining online communities for the benefit of their employers—is only one possible vision for t
32#
發(fā)表于 2025-3-27 04:07:30 | 只看該作者
33#
發(fā)表于 2025-3-27 05:20:33 | 只看該作者
34#
發(fā)表于 2025-3-27 09:31:40 | 只看該作者
Henrik Christensen,Lisbeth E. de Vriesucted piecemeal, one Internet address at a time, often without social or scholarly impact beyond the site’s own stakeholders. Scientists lack the tools, methods, and practices to combine, compare, contrast, and communicate about online behavior across Internet addresses or over time. In response, we
35#
發(fā)表于 2025-3-27 16:24:14 | 只看該作者
Henrik Christensen,John Elmerdahl Olsenan activity. The volume of data available offers great potential to advance social and behavioural science research. However, the data are of a very different kind than more conventional social and behavioural science data, posing challenges to use. This paper adopts a data framework from Earth obse
36#
發(fā)表于 2025-3-27 20:50:33 | 只看該作者
37#
發(fā)表于 2025-3-27 23:54:36 | 只看該作者
https://doi.org/10.1007/978-3-319-98428-5duce content that has immediate impact. Intellectual, analytic, or symbolic collaboration in academia, business, or even government is now almost inconceivable without online support. Work on text and narratives has been entirely transformed by Internet-based sites. Of these, wiki sites are the most
38#
發(fā)表于 2025-3-28 03:08:21 | 只看該作者
Introduction to Biomedical Engineeringee/libre open source software (FLOSS) is made. Embodying some of the same FLOSS ethos, this team created a public-facing repository for their own data and analyses and encouraged other researchers to use it and contribute to it. This chapter tells the story of how the FLOSSmole project began, where
39#
發(fā)表于 2025-3-28 09:19:20 | 只看該作者
40#
發(fā)表于 2025-3-28 11:02:24 | 只看該作者
https://doi.org/10.1007/978-3-031-01638-7ists with the skills necessary to extract business value from burgeoning datasets created by online communities like Facebook, Twitter, and LinkedIn. This model of data science—professional data scientists mining online communities for the benefit of their employers—is only one possible vision for t
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