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Predicting Retweeting Behavior on Breast Cancer Social Networks: Network and Content Characteristics

机译:预测乳腺癌社交网络上的转发行为:网络和内容特征

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This study explored how social media, especially Twitter, serves as a viable place for communicating about cancer. Using a 2-step analytic method that combined social network analysis and computer-aided content analysis, this study investigated (a) how different types of network structures explain retweeting behavior and (b) which types of tweets are retweeted and why some messages generate more interaction among users. The analysis revealed that messages written by users who had a higher number of followers, a higher level of personal influence over the interaction, and closer relationships and similarities with other users were retweeted. In addition, a tweet with a higher level of positive emotion was more likely to be retweeted, whereas a tweet with a higher level of tentative words was less likely to be retweeted. These findings imply that Twitter can be an effective tool for the dissemination of health information. Theoretical and practical implications for psychosocial interventions for people with health concerns are discussed.
机译:这项研究探索了社交媒体(尤其是Twitter)如何成为交流癌症的可行场所。使用结合社交网络分析和计算机辅助内容分析的两步分析方法,本研究调查了(a)不同类型的网络结构如何解释转发行为以及(b)哪些类型的推文被转发以及为什么某些消息产生更多的推文用户之间的互动。分析显示,转发了具有更多关注者,对交互的个人影响力更高以及与其他用户的亲缘关系和相似度更高的用户的邮件。此外,具有较高积极情绪的推文更有可能被转发,而具有较高暂定词语的推文则不太可能被转发。这些发现表明,Twitter可以成为传播健康信息的有效工具。讨论了对有健康问题的人进行社会心理干预的理论和实践意义。

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