chrisengelhardt/sentim-batch repository overview

⁠Sentiment Analysis

This workflow analyzes a large amount of Tweets using a pre-trained Tensorflow Net, or alternatively using NLTK language corpus lookup, to determine sentiment per US state.

⁠Overview

This repository contains a parallel sentiment analysis implementation, orchestrated with the Abstract Function Choreography Language and runnable on the Apollo Engine⁠

Fig 1: workflow.yaml control and data flow

⁠Get the code

git clone https://github.com/Apollo-Workflows/Sentiment-Analysis
cd Sentiment-Analysis

⁠Autodeploy

1. Save the credentials for your cloud provider in the according subfolder:
   • AWS: Put credential file under aws/credentials
   • IBM: Add ibmcloud_api_key to ibm/terraform.tfvars
2. • A: Deploy to all providers: Run from root dir docker run --rm -it --entrypoint=/app/deployAll.sh -v ${PWD}:/app/ chrisengelhardt/apollo-autodeploy
   • B: Deploy single provider with custom settings: Run docker run --rm -v ${PWD}:/app/ chrisengelhardt/apollo-autodeploy --help from within the directory of your chosen cloud provider

Note: For IBM you have to create a namespace first and place it into ibm.tf at line namespace = "YOURNAMESPACE".

Usage: /app/deploy.sh [--help] [--region region] [--url] [--mapping]

Commands:
        --help                  Show this help output.
        --region region         Sets a specific region for the deployment. Use a region from:
                                https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.RegionsAndAvailabilityZones.html
        --url                   Prints out all deployment urls
        --mappings              Creates typeMapping.json with the deployment urls

⁠References

Twitter data set: Z. Cheng, J. Caverlee, and K. Lee. You Are Where You Tweet: A Content-Based Approach to Geo-locating Twitter Users. In Proceeding of the 19th ACM Conference on Information and Knowledge Management (CIKM), Toronto, Oct 2010⁠ (Accessed Dec 14 2020)

Tensorflow Text classification model (used in sentim-inference): Text classification | Tensorflow Lite⁠ (Accessed Dec 22 2020)

Textblob Library & NLTK corpora (used in sentim-inference-textblob): sloria/TextBlob | GitHub⁠ (Accessed Dec 25 2020)