Research partnerships
Use the Macroscope's data collection and analysis pipeline in your own studies, or partner with us on research projects and proposals involving social media data.
National Center for Supercomputing Applications · University of Illinois Urbana-Champaign
The Social Media Macroscope
An open-source science gateway that makes social media data, analytics, and visualization tools accessible to researchers and students of all levels of expertise.
We are looking for collaborators to help enhance and extend the Social Media Macroscope, from joint research projects to deployments on cloud and on-premises infrastructure.
Collaborate
Work with us
The Social Media Macroscope grew out of collaboration between researchers and research software engineers. We welcome partners who want to use, adapt, or extend it.
Institutional deployments
Bring SMILE to your lab, course, or institution on cloud or on-premises resources. We can help adapt the Docker Compose and Kubernetes setups to your environment.
New analyses and data sources
Contribute new analysis methods, improve existing ones such as sentiment analysis and topic modeling, or add support for new social media platforms. Start with Adding a New Analysis to SMILE.
Integrations and community
Connect the Macroscope with other science gateways, data management systems, and analytics tools, and help define shared workflows for social media research.
Interested in collaborating?
Tell us about your research interests or the infrastructure you have in mind, and we'll follow up.
Projects
Research software
The tools developed as part of the Social Media Macroscope.
Social Media Intelligence and Learning Environment (SMILE)
Open source · Self-hostableOne platform for social media data ingestion, analysis, and data sharing. SMILE collects real-time and historical social media data from Twitter, Reddit, and YouTube, and performs sentiment analysis, phrase mining, named entity recognition, topic modeling, machine learning classification, and network analysis. Results can be shared with collaborators through Clowder.
SMM Clowder
Open source · Self-hostableSMILE integrates with Clowder, a customizable data management framework used by science gateways, so analysis outputs can be shared, visualized, and access-controlled. SMILE's wizard uploads selected outputs to Clowder, where its extractors can provide quick insight into the uploaded data.
Brand Analytics Environment (BAE)
LegacyBAE helped practitioners understand how individuals and groups interact with brands and organizations by comparing the machine-learned personalities of Twitter users with those of consumer brands. It depended on IBM Watson Personality Insights, which has been retired, and is no longer offered.
Self-host
Run SMILE on your own infrastructure
SMILE is packaged for on-premises and cloud deployment. Each component, including the SMILE server, the GraphQL data server, the analysis algorithms, and MinIO, runs as its own Docker container.
On Kubernetes, a Helm chart lets you scale components and configure storage independently, and Kubernetes' internal networking keeps backing services off the public network. For lightweight deployments where scalability is not a concern, Docker Compose offers a simpler setup that needs fewer resources.
Open source
Code repositories
The project is built on open-source libraries and algorithms and is itself fully open source. You are welcome to fork the repositories, open issues, and submit pull requests. See the contributing guide to get started.
Publications
Cite our work
If the Social Media Macroscope supports your research, please cite the following. Your citation helps us continue to maintain and improve the platform.
- Wang, C., Kim, Y. W., Kooper, R., & Yun, J. (2023, October 30). SMILE: A User-Friendly Science Gateway for Social Media Research and Collaboration. Science Gateways 2023 (SG23), Pittsburgh, PA. https://doi.org/10.5281/zenodo.10028454
- Wang, C., Marini, L., Chin, C. L., Vance, N., Donelson, C., Meunier, P., & Yun, J. T. (2019, September). Social Media Intelligence and Learning Environment: an Open Source Framework for Social Media Data Collection, Analysis and Curation. In 2019 15th International Conference on eScience (eScience) (pp. 252–261). IEEE.
- Yun, J. T., Vance, N., Wang, C., Marini, L., Troy, J., Donelson, C., Chin, C. L., & Henderson, M. D. (2019). The Social Media Macroscope: A science gateway for research using social media data. Future Generation Computer Systems. doi:10.1016/j.future.2019.10.029
Contact
Contact us
To discuss a collaboration, a deployment at your institution, or a contribution to the project, write to the Social Media Macroscope team at the address below.
It helps to include:
- your name, institution, and role
- your research interests or the problem you want to address
- any infrastructure or data sources you have in mind
Email
smm@lists.illinois.edu
Social Media Macroscope team
National Center for Supercomputing Applications
University of Illinois Urbana-Champaign