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Chen Wang edited this page Oct 2, 2026 · 3 revisions

The Social Media Macroscope (SMM) is an open-source science gateway from NCSA that makes social media data collection, analytics, and visualization accessible to researchers and students of all levels of expertise.

No hosted instance (as of October 2026): the public SMILE Playground (smile.smm.ncsa.illinois.edu), SMM Clowder (clowder.smm.ncsa.illinois.edu), and the NCSA-hosted deployments have been taken offline. There is currently no public SMILE service to log in to. The source code and Docker images are still available, so you can run the full stack yourself with Docker Compose or Kubernetes and Helm.

Tools

SMILE (Social Media Intelligence and Learning Environment) is one platform for social media data ingestion, analysis, and sharing. It collects real-time and historical data from Twitter, Reddit, and YouTube, and runs sentiment analysis, phrase mining, named entity recognition, topic modeling, machine learning classification, and network analysis on it.

Clowder integration: SMILE can upload analysis outputs to a Clowder instance so you can share, visualize, and manage access to them with collaborators. The hosted SMM Clowder instance is offline, so to use this feature, point a self-hosted SMILE at your own Clowder server (see the Clowder add-on in Run SMILE with Docker Compose).

Legacy: BAE (Brand Analytics Environment) compared the machine-learned personalities of Twitter users with those of consumer brands. It is not currently offered. Its Docker image is still on Docker Hub and its compose file is at smm-deployment/docker/bae, but it depended on IBM Watson Personality Insights, which IBM has retired.

Documentation

Using SMILE

Running SMILE yourself

Developing SMILE

Code repositories

Component Repository
SMILE server ncsa/standalone-smm-smile
SMILE data server (GraphQL) ncsa/standalone-smm-smile-graphql
Analytics algorithms ncsa/standalone-smm-analytics
Deployment (Docker Compose and Helm) ncsa/smm-deployment
Landing page and this wiki ncsa/standalone-smm-landing

Prebuilt images are published on Docker Hub under socialmediamacroscope.

Cite our work

  • Wang, C., Kim, Y. W., Kooper, R., & Yun, J. (2023). 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). Social Media Intelligence and Learning Environment: an Open Source Framework for Social Media Data Collection, Analysis and Curation. 2019 15th International Conference on eScience (eScience), pp. 252–261. IEEE. https://ieeexplore.ieee.org/document/9041717
  • 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. https://doi.org/10.1016/j.future.2019.10.029

Home

Using SMILE

Running SMILE

Developing SMILE

SMM landing page · Contact

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