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  • 标题:Evaluating Sampling Methods for Content Analysis of Twitter Data:
  • 本地全文:下载
  • 作者:Hwalbin Kim ; S. Mo Jang ; Sei-Hill Kim
  • 期刊名称:Social Media + Society
  • 电子版ISSN:2056-3051
  • 出版年度:2018
  • 卷号:4
  • 期号:2
  • DOI:10.1177/2056305118772836
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:Despite the existing evaluation of the sampling options for periodical media content, only a few empirical studies have examined whether probability sampling methods can be applicable to social media content other than simple random sampling. This article tests the efficiency of simple random sampling and constructed week sampling, by varying the sample size of Twitter content related to the 2014 South Carolina gubernatorial election. We examine how many weeks were needed to adequately represent 5 months of tweets. Our findings show that a simple random sampling is more efficient than a constructed week sampling in terms of obtaining a more efficient and representative sample of Twitter data. This study also suggests that it is necessary to produce a sufficient sample size when analyzing social media content.
  • 关键词:simple random sampling; constructed week sampling; content analysis; Twitter data
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