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Identifying behaviors that generate positive interactions between museums and people on a social media platform: An analysis of 27 science museums on Twitter.

机译：识别在社交媒体平台上博物馆与人之间产生积极互动的行为：在Twitter上对27个科学博物馆的分析。

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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.

机译：这项研究的目的是详细研究科学博物馆如何使用Twitter，并建议这些博物馆应该做出改变，以改进其在该社交媒体平台上的当前方法。先前的研究已经确定了博物馆在社交媒体上创作的内容的类型，但没有一个定量地调查最有可能与社交媒体受众产生互动和参与的特定内容类型。对来自27个科学博物馆的5278条推文进行了分析，以确定哪种类型的推文在转发和收藏夹中产生最大的影响。这些推文中有1,453条被选中进行其他定性分析。结果表明，具有教育性内容，链接和主题标签的推文导致了最多的转发和收藏。结果还表明，博物馆发布的大多数推文不会与社交媒体受众产生互动和参与。利用这项研究的结果，为现有博物馆改进了Twitter的使用模型。

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作者
Baker, Stacy Christine.;
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作者单位

State University of New York at Buffalo.;

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授予单位 State University of New York at Buffalo.;
学科 Museum studies.;Web studies.;Science education.
学位 M.Ed.
年度 2015
页码 54 p.
总页数 54
原文格式 PDF
正文语种 eng
中图分类
关键词
入库时间 2022-08-17 11:52:21

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Identifying behaviors that generate positive interactions between museums and people on a social media platform: An analysis of 27 science museums on Twitter.

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