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结合自然语言处理和网络分析,以研究倡导组织如何在社交媒体上激发对话。

Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.

作者信息

Bail Christopher Andrew

机构信息

Department of Sociology, Duke University, Durham, NC 27708; Network Analysis Center, Duke University, Durham, NC 27708

出版信息

Proc Natl Acad Sci U S A. 2016 Oct 18;113(42):11823-11828. doi: 10.1073/pnas.1607151113. Epub 2016 Sep 30.

DOI:10.1073/pnas.1607151113
PMID:27694580
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5081586/
Abstract

Social media sites are rapidly becoming one of the most important forums for public deliberation about advocacy issues. However, social scientists have not explained why some advocacy organizations produce social media messages that inspire far-ranging conversation among social media users, whereas the vast majority of them receive little or no attention. I argue that advocacy organizations are more likely to inspire comments from new social media audiences if they create "cultural bridges," or produce messages that combine conversational themes within an advocacy field that are seldom discussed together. I use natural language processing, network analysis, and a social media application to analyze how cultural bridges shaped public discourse about autism spectrum disorders on Facebook over the course of 1.5 years, controlling for various characteristics of advocacy organizations, their social media audiences, and the broader social context in which they interact. I show that organizations that create substantial cultural bridges provoke 2.52 times more comments about their messages from new social media users than those that do not, controlling for these factors. This study thus offers a theory of cultural messaging and public deliberation and computational techniques for text analysis and application-based survey research.

摘要

社交媒体网站正迅速成为公众对倡导议题进行审议的最重要场所之一。然而,社会科学家尚未解释为何一些倡导组织发布的社交媒体信息能激发社交媒体用户之间广泛的讨论,而绝大多数组织却很少或根本得不到关注。我认为,如果倡导组织搭建起“文化桥梁”,或者发布的信息能将倡导领域内很少一起讨论的对话主题结合起来,那么它们就更有可能激发新社交媒体受众的评论。我运用自然语言处理、网络分析和一款社交媒体应用程序,来分析在1.5年的时间里文化桥梁如何塑造了脸书上关于自闭症谱系障碍的公众话语,同时控制倡导组织、其社交媒体受众以及它们互动所处的更广泛社会背景的各种特征。我发现,在控制了这些因素后,搭建起大量文化桥梁的组织所发布信息引发新社交媒体用户的评论比未搭建文化桥梁的组织多2.52倍。因此,本研究提供了一种文化信息传播与公众审议理论,以及用于文本分析和基于应用程序的调查研究的计算技术。

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