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|a QA76.9.D343
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| 100 |
1 |
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|a Russell, Matthew A.
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| 245 |
0 |
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|a Unleashing Twitter data for fun and insight
|c Matthew A. Russell
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| 260 |
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|a [United States?]
|b O'Reilly Media
|c 2011
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| 300 |
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|a 1 streaming video file (48 min., 3 sec.)
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| 653 |
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|a Data mining / fast / (OCoLC)fst00887946
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| 653 |
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|a Online social networks / fast / (OCoLC)fst01741311
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| 653 |
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|a Data mining / http://id.loc.gov/authorities/subjects/sh97002073
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| 653 |
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|a Online social networks / http://id.loc.gov/authorities/subjects/sh2006006990
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| 653 |
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|a Réseaux sociaux (Internet)
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| 653 |
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|a Twitter / http://id.loc.gov/authorities/names/n2009031956
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| 653 |
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|a Exploration de données (Informatique)
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| 653 |
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|a Twitter / fast / (OCoLC)fst01794911
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| 041 |
0 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 500 |
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|a Recorded at O'Reilly strata making data work conference: Feb. 1-3, 2011, Santa Clara, CA.
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|u https://learning.oreilly.com/videos/~/9781449306106/?ar
|x Verlag
|3 Volltext
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|a 331
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|a 006.754
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|a 302.231
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| 520 |
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|a "This talk demonstrates how an eclectic blend of storage, analysis, and visualization techniques can be used to gain a lot of serious insight from Twitter data, but also to answer fun questions such as "What does Justin Bieber and the Tea Party have (and not have) in common?"--Resource description page
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