/Sentiment-Analysis

A common natural language processing task of performing short-text sentiment analysis

Primary LanguagePythonMIT LicenseMIT

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

workflow diagram

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: Go to the service IAM and create a new user with the access type Programmatic access and attach the AdministratorAccess policy, which is part of the existing policies. You can copy the Access key ID and Secret access key and put it into the following format and save it under aws/credentials: 
      [default]
aws_access_key_id = <Your access key ID>
aws_secret_access_key = <Your secret access key>
    • IBM: Create the ibmcloud_api_key here add it to ibm/terraform.tfvars
    • 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)