Identifying behaviors that generate positive interactions between museums and people on a social media platform: An analysis of 27 science museums on Twitter
Baker, Stacy Christine
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The aim of this study was to provide a detailed examination of how science museums use Twitter and suggest changes these museums should make to improve their current approach on this social media platform. Previous studies have identified the types of content museums are creating on social media, but none have quantitatively investigated the specific types of content most likely to generate interaction and engagement with a social media audience. A total of 5,278 tweets from 27 science museums were analyzed to determine what type of tweet yields the greatest impact measured in retweets and favorites. 1,453 of those tweets were selected for additional qualitative analysis. The results indicate that tweets with educational content, links, and hashtags lead to the greatest number of retweets and favorites. The results also indicate that the majority of tweets posted by museums do not generate interaction and engagement with a social media audience. A model for existing museums to improve their use of Twitter was created using the results of this study.