Introduction 

added_eScience_2019_SMM.pptx

Get Start

• Register on https://socialmediamacroscope.org and start trying out the tools
• Code base: 
  • https://opensource.ncsa.illinois.edu/bitbucket/projects/SMM (for development)
  • https://github.com/IllinoisSocialMediaMacroscope (mirrored from bitbucket) 

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 

Contributing to existing tools

• SMILE

• 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
  • what's the platforms policy on data collecting 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, Nam Entity Recognition, and Twitter Network analysis
  • you can bringing in your own analysis, ideally in python, but can be any language.
  • or in each of the above mentioned analysis, if you have specific algorithms or innovated ways to perform that analysis, you are welcome to bring in those as well
  • Useful links:
    • Guidance for writing configuration file in SMILE
    • Template for submitting Python algorithm
    • SMILE endpoints

• BAE

• PAHO COVID19 dashboards

• This is the newest project we are working on currently

Other aspects that you could contribute to:

• Community Engaging:
  • How to advertising SMM project and the aforementioned tools to the community
  • Workflow or standards to include new data source and algorithms

• 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