Twitter as Data:
The rise of the internet and mobile telecommunications has created the possibility of using large datasets to understand behavior at unprecedented levels of temporal and geographic resolution. Online social networks attract the most users, though users of these new technologies provide their data th...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2018
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| Schriftenreihe: | Elements in Quantitative and Computational Methods for the Social Sciences
Cambridge Elements |
| Schlagworte: | |
| Online-Zugang: | DE-12 DE-473 DE-29 Volltext |
| Zusammenfassung: | The rise of the internet and mobile telecommunications has created the possibility of using large datasets to understand behavior at unprecedented levels of temporal and geographic resolution. Online social networks attract the most users, though users of these new technologies provide their data through multiple sources, e.g. call detail records, blog posts, web forums, and content aggregation sites. These data allow scholars to adjudicate between competing theories as well as develop new ones, much as the microscope facilitated the development of the germ theory of disease. Of those networks, Twitter presents an ideal combination of size, international reach, and data accessibility that make it the preferred platform in academic studies. Acquiring, cleaning, and analyzing these data, however, require new tools and processes. This Element introduces these methods to social scientists and provides scripts and examples for downloading, processing, and analyzing Twitter data |
| Beschreibung: | 1 Online-Ressource Illustrationen, Diagramme |
| ISBN: | 9781108529327 |
| DOI: | 10.1017/9781108529327 |
Internformat
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Datensatz im Suchindex
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| author_facet | Steinert-Threlkeld, Zachary C. |
| author_role | aut |
| author_sort | Steinert-Threlkeld, Zachary C. |
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| illustrated | Illustrated |
| indexdate | 2024-12-05T17:00:53Z |
| institution | BVB |
| isbn | 9781108529327 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030248124 |
| oclc_num | 1028535894 |
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| series2 | Elements in Quantitative and Computational Methods for the Social Sciences Cambridge Elements |
| spelling | Steinert-Threlkeld, Zachary C. Verfasser (DE-588)1138716537 aut Twitter as Data Zachary C. Steinert-Threkeld Cambridge Cambridge University Press 2018 1 Online-Ressource Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Elements in Quantitative and Computational Methods for the Social Sciences Cambridge Elements The rise of the internet and mobile telecommunications has created the possibility of using large datasets to understand behavior at unprecedented levels of temporal and geographic resolution. Online social networks attract the most users, though users of these new technologies provide their data through multiple sources, e.g. call detail records, blog posts, web forums, and content aggregation sites. These data allow scholars to adjudicate between competing theories as well as develop new ones, much as the microscope facilitated the development of the germ theory of disease. Of those networks, Twitter presents an ideal combination of size, international reach, and data accessibility that make it the preferred platform in academic studies. Acquiring, cleaning, and analyzing these data, however, require new tools and processes. This Element introduces these methods to social scientists and provides scripts and examples for downloading, processing, and analyzing Twitter data Soziale Software (DE-588)7550143-0 gnd rswk-swf Soziales Netzwerk (DE-588)4055762-5 gnd rswk-swf Big Data (DE-588)4802620-7 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Datenerhebung (DE-588)4155272-6 gnd rswk-swf Twitter Softwareplattform (DE-588)7660487-1 gnd rswk-swf Twitter Softwareplattform (DE-588)7660487-1 s Big Data (DE-588)4802620-7 s Datenerhebung (DE-588)4155272-6 s Data Mining (DE-588)4428654-5 s Soziales Netzwerk (DE-588)4055762-5 s Soziale Software (DE-588)7550143-0 s 1\p DE-604 Erscheint auch als Druck-Ausgabe 9781108438339 Erscheint auch als Druck-Ausgabe, paperback https://doi.org/10.1017/9781108529327 Verlag kostenfrei Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Steinert-Threlkeld, Zachary C. Twitter as Data Soziale Software (DE-588)7550143-0 gnd Soziales Netzwerk (DE-588)4055762-5 gnd Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Datenerhebung (DE-588)4155272-6 gnd Twitter Softwareplattform (DE-588)7660487-1 gnd |
| subject_GND | (DE-588)7550143-0 (DE-588)4055762-5 (DE-588)4802620-7 (DE-588)4428654-5 (DE-588)4155272-6 (DE-588)7660487-1 |
| title | Twitter as Data |
| title_auth | Twitter as Data |
| title_exact_search | Twitter as Data |
| title_full | Twitter as Data Zachary C. Steinert-Threkeld |
| title_fullStr | Twitter as Data Zachary C. Steinert-Threkeld |
| title_full_unstemmed | Twitter as Data Zachary C. Steinert-Threkeld |
| title_short | Twitter as Data |
| title_sort | twitter as data |
| topic | Soziale Software (DE-588)7550143-0 gnd Soziales Netzwerk (DE-588)4055762-5 gnd Big Data (DE-588)4802620-7 gnd Data Mining (DE-588)4428654-5 gnd Datenerhebung (DE-588)4155272-6 gnd Twitter Softwareplattform (DE-588)7660487-1 gnd |
| topic_facet | Soziale Software Soziales Netzwerk Big Data Data Mining Datenerhebung Twitter Softwareplattform |
| url | https://doi.org/10.1017/9781108529327 |
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