Introduction
added_eScience_2019_SMM.pptx
Geting start
Contributing to existing tools
SMILE is a comprehensive social media data collecting and analytics platform.
Defining new social media platform data source
- how to authenticate and authorize
- what's the data structure like
- what is the platforms policy on data collection and ownership
- learn GraphQL and define your own schema
Adding new analytics metrics
- currently we have Sentiment analysis, NLP Preprocessing, Topic modeling, Automated phrase detection, Name Entity Recognition, and Twitter Network analysis
- you can bring in your own analyses, ideally in Python, but can be any programming languages.
- Alternatively, in each of the above mentioned analyses, if you have specific algorithms or innovated ways to perform that analysis, you are welcomed to bring in those
- Useful links:
This is the newest project we are working on currently!
Writing your own tools
Could be anything novel that utilizing social media data and analyses; preferably using opensource libraries and algorithms that associates with academic publication
Need to have a Graphic Interface
Plan ahead: Need to communicate with Hubzero (where all the tools have been hosted) to decide if the technology stack you plan to use is compatible with their platform
Other aspects that you could contribute to:
UI/UX design
Testing and Monitoring
Exploring new computation platforms and resources
- Other cloud computing platform capability other than AWS
- Container orchestration - one of the direction we are exploring is to dockerize all the components of the tools, and we plan to scale it up using kubernetes
- Exploring the capability of existing analytics and integrate to the tools: such as Google Trend API, IBM watson, Tableau and etc
Community Engaging:
- How to advertise SMM project and tools to the community; How to find our target audience and satisfy their needs
- Workflow or standards to include new data source and algorithms