ArticleProceedings of the National Academy of Sciences of the United States of America2016
Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- A research agenda for encouraging prosocial behaviour on social media.Nature human behaviour · 2025Review
- The dynamics of mental health policy in Iran over the last century.BMC psychology · 2025Article
- Can deepfakes be used to study emotion perception? A comparison of dynamic face stimuli.Behavior research methods · 2024Article
- Article
- Demography's Changing Intellectual Landscape: A Bibliometric Analysis of the Leading Anglophone Journals, 1950-2020.Demography · 2023Article
- Examining Homophily, Language Coordination, and Analytical Thinking in Web-Based Conversations About Vaccines on Reddit: Study Using Deep Neural Network Language Models and Computer-Assisted Conversational Analyses.Journal of medical Internet research · 2023Article
- [Network analyses as a valuable extension of conventional statistics].Dermatologie (Heidelberg, Germany) · 2022Article
- Reproducibility in the Social Sciences.Annual review of sociology · 2022Article
- Article
- Emotion diffusion effect: Negative sentiment COVID-19 tweets of public organizations attract more responses from followers.PloS one · 2022Article
- Online polarization and cross-fertilization in multi-cleavage societies: the case of Spain.Social network analysis and mining · 2022Article
- How quantifying the shape of stories predicts their success.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Analyzing Spanish News Frames on Twitter during COVID-19-A Network Study of El País and El Mundo.International journal of environmental research and public health · 2020Article
- Computational Social Science and Sociology.Annual review of sociology · 2020Article
- Enhancing big data in the social sciences with crowdsourcing: Data augmentation practices, techniques, and opportunities.PloS one · 2020Article
- Cross-disciplinary evolution of the genomics revolution.Science advances · 2018Article
- Article
- Unmasking the Twitter Discourses on Masks During the COVID-19 Pandemic: User Cluster-Based BERT Topic Modeling Approach.JMIR infodemiologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.