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

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.computational social science | advocacy organizations | public deliberation | networks | natural language processing

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“…Hence, we use some excellent studies as reference for validating our approach. From a methodological point of view, we are in line with Bail (2016). In such a work, the author presents remarkable results in the social field combining text mining and network analysis to study how advocacy organizations stimulate conversation on social media.…”

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