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TitleSelecting, Scraping, and Sampling Big Data Sets from the Internet: Fan Blogs as Exemplar
Creator
Date Issued2015
Source PublicationSAGE Research Methods Cases Part 1
ISBN9781473962996
Publication PlaceLondon
PublisherSAGE Publications, Ltd.
Abstract

This case study uses a study of fan blog commentary to explain how researchers decide precisely what text to gather from the Internet as well as how they identify the locations of that content, decide exactly which website from which to gather data, and how to get the data from the Internet into text files for analysis. If the data set thus gathered is too large for the chosen method of analysis, we offer detailed descriptions of how to employ random sampling to data gathered from multiple websites to ensure representativeness as well as employ random selection in assigning chunks of the sampled data to multiple coders for analysis. Next, we explain how to seamlessly incorporate tests for intercoder reliability into the research design. Finally, we explain one method of analysis, thematic analysis using grounded theory analysis with axial coding.

Language英语English
Keywordblogs fans internet population teams web sites
DOI10.4135/978144627305014558403
URLView source
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeBook chapter
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/9880
CollectionResearch outside affiliated institution
Recommended Citation
GB/T 7714
Webb, Lynne M.,Gibson, Danna M.,Wang, Yuanxinet al. Selecting, Scraping, and Sampling Big Data Sets from the Internet: Fan Blogs as Exemplar. London: SAGE Publications, Ltd., 2015.
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