YELP REVIEW SENTIMENT ANALYSIS

IN PROGRESS Project for UC Berkeley Data Science 205 Class Storing and Retrieving Data. Based on the Yelp Dataset Challenge.

Setup

Make sure you already have git configured locally, install virtualenv and download this directory:

pip install virtualenv
virtualenv venv
cd venv
git clone https://github.com/sialan/yelp-review-sentiment-analysis.git

Create a clean virtual environment and install dependencies:

source bin/activate
pip install -r requirements.txt

Download the Yelp dataset from https://www.yelp.com/dataset_challenge/dataset. Extract the json files from the zipped package and save them in the data/input folder.

For running scripts remotely on AWS EMR via MrJob, you will need to first configure account settings in the mrjob.conf file.

runners:
  emr:
	aws_access_key_id: YOUR_ACCESS_KEY
	aws_secret_access_key: YOUR_SECRET_KEY

Create an s3 bucket if it does not already exist and upload the json data files to s3. Make sure you already have the AWS command-line tool installed and configured.

aws configure
aws s3 cp data/input/yelp_dataset_challenge_reviews.json s3://mybucket/input/
aws s3 cp data/input/yelp_dataset_challenge_business.json s3://mybucket/input/
aws s3 cp bootstrap-mrjob.sh s3://mybucket/

An EMR cluster needs to be created and bootstrapped.

aws emr create-cluster --ami-version 3.2.3 --instance-groups InstanceGroupType=MASTER,InstanceCount=1,InstanceType=m1.medium InstanceGroupType=CORE,InstanceCount=2,InstanceType=m1.medium --name "Yelp Review Sentiment Analysis Cluster" --log-uri s3://mybucket/logs/ --enable-debugging --tags Name=emr --bootstrap-actions Path=s3://mybucket/bootstrap-mrjob.sh,Name="Setup mrjob / text analytics"

Run Locally

To perform the sentiment analysis by keyphrase locally, run the main.py file with the --type flag set to keyphrase. Output will be stored in the data/output/ folder.

python main.py --type=keyphrase

To perform the sentiment analysis by topic locally, run the main.py file with the --type flag set to topic. Output will be stored in the data/output/ folder.

python main.py --type=topic

Run Remotely

To perform the sentiment analysis by keyphrase remotely on AWS EMR, retrieve the jobflow-id from the cluster from setup phase and and run:

python src/etl/generate_sentiment_by_keyphrase.py -c mrjob.conf -r emr --emr-job-flow-id=<jobflow-id> --output-dir=s3://mybucket/output/ --no-output s3://mybucket/input/yelp_dataset_challenge_reviews.json

To perform the sentiment analysis by keyphrase remotely on AWS EMR, retrieve the jobflow-id from the cluster from setup phase and and run:

python src/etl/generate_sentiment_by_topic.py -c mrjob.conf -r emr --emr-job-flow-id=<jobflow-id> --output-dir=s3://mybucket/output/ --no-output s3://mybucket/input/yelp_dataset_challenge_reviews.json

Run Demo

To run the developed d3.js visualization for sentiment analysis, change to the demo folder and spin up a local python server. Demo can be accessed http://localhost:8888. Alternatively, a live version of the keyword sentiment analysis is being hosted at http://ucb-205-keyword-demo.s3-website-us-west-2.amazonaws.com/.

cd demo
python -m SimpleHTTPServer 8888