Discover the range of analytical tools we provide for social media
SOCIAL MEDIA INTELLIGENCE AND LEARNING ENVIRONMENT (SMILE)
One platform for social media data ingestion, analysis, and data sharing. SMILE collects real
time and historical
social media data from Twitter and Reddit, performs sentiment analysis, phrase mining,
entity recognition, machine learning classification, network analysis and so on. You can
share your
computation result to Clowder
and sharing with your collaborators.
At our playground, we provide a temporary space for your experimentation, where no data
is stored beyond a day.
SMM Clowder
Discover seamless data sharing and collaboration with SMILE's social media analytical tools.
Our
platform integrates with Clowder (SMM Clowder), a customizable data management framework
used by
renowned science gateways. With Clowder, you
can easily share analysis outputs, visualize data, and manage access.
SMILE's user-friendly wizard allows you to effortlessly upload targeted analytics
outputs to
Clowder. You can also leverage Clowder's information extractor functionality for drawing
quick insight
of your data uploaded.
BRAND ANALYTICS ENVIRONMENT (BAE)
BAE helps practitioners to gain insight into how individuals and groups may interact with brands and various organizations. BAE investigates the relationships between users of Twitter’s machine-learned personalities and a consumer brand’s machine-learned personalities. You may find an organization’s perfect “bae” through this tool.
Coming Soon...Effortless On-Premises Deployment
Experience hassle-free deployment of our full stack of apps right on your own machine with
ease.
For deployment, SMILE leverages
Kubernetes,
utilizing
Helm charts to define,
install, and manage applications seamlessly. This integration simplifies the deployment and
administration of complex applications through templating and version control. Each
component of SMILE,
such as the SMILE server,
graphql data server, algorithms, and MinIO instance, is encapsulated as
Docker containers
and
individually deployed within Kubernetes. This approach enables independent management of
component
activation, scaling, and storage configuration without causing disruptions. Furthermore, the
internal
networking system provided by Kubernetes enhances the overall security of the system.
For lightweight deployments where scalability is not a concern, SMILE also offers a Docker
Compose
setup option. This alternative provides a simpler learning curve and requires fewer
resources compared
to Kubernetes.
Please refer to the following documentations for more information:
Deploy SMILE with Kubernetes and Helm Chart
Deploy SMILE with Docker Compose
Our docker images are published on Docker Hub and available to the public. Check it out
Embracing Open Source
Our project, built upon open-sourced libraries and algorithms, is fully open-sourced and
appreciates any kind of community contribution. You are welcome to fork our repositories,
open issues and
create pull requests to any of the public
repository.
Visit GitHub repositories:
SMILE
SMILE Data Server
SMILE Deployment
Analytics Algorithms
Landing Page
Cite our work below. Your citation will help us continue to provide and improve this
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