Evaluating Sampling Methods for Content Analysis of Twitter Data

• Main Authors: Hwalbin Kim, S. Mo Jang, Sei-Hill Kim, Anan Wan
• Format: Article
• Language: English
• Published: SAGE Publishing 2018-04-01
• Series: Social Media + Society
• Online Access: https://doi.org/10.1177/2056305118772836

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.