Skip to main content
Journal cover image

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

Publication ,  Journal Article
Bail, CA
Published in: Proceedings of the National Academy of Sciences of the United States of America
October 2016

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.

Duke Scholars

Published In

Proceedings of the National Academy of Sciences of the United States of America

DOI

EISSN

1091-6490

ISSN

0027-8424

Publication Date

October 2016

Volume

113

Issue

42

Start / End Page

11823 / 11828

Related Subject Headings

  • Social Media
  • Regression Analysis
  • Organizations
  • Neural Networks, Computer
  • Natural Language Processing
  • Humans
  • Consumer Advocacy
  • Autism Spectrum Disorder
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bail, C. A. (2016). Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media. Proceedings of the National Academy of Sciences of the United States of America, 113(42), 11823–11828. https://doi.org/10.1073/pnas.1607151113
Bail, Christopher Andrew. “Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.Proceedings of the National Academy of Sciences of the United States of America 113, no. 42 (October 2016): 11823–28. https://doi.org/10.1073/pnas.1607151113.
Bail CA. Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media. Proceedings of the National Academy of Sciences of the United States of America. 2016 Oct;113(42):11823–8.
Bail, Christopher Andrew. “Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.Proceedings of the National Academy of Sciences of the United States of America, vol. 113, no. 42, Oct. 2016, pp. 11823–28. Epmc, doi:10.1073/pnas.1607151113.
Bail CA. Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media. Proceedings of the National Academy of Sciences of the United States of America. 2016 Oct;113(42):11823–11828.
Journal cover image

Published In

Proceedings of the National Academy of Sciences of the United States of America

DOI

EISSN

1091-6490

ISSN

0027-8424

Publication Date

October 2016

Volume

113

Issue

42

Start / End Page

11823 / 11828

Related Subject Headings

  • Social Media
  • Regression Analysis
  • Organizations
  • Neural Networks, Computer
  • Natural Language Processing
  • Humans
  • Consumer Advocacy
  • Autism Spectrum Disorder