Install dependencies

npm i

Rename .env.structure to .env

Acess Twitter Dev portal and create yourself a Bearer token to consume from the twitter API.

Paste your token on the .env file.

Paste your AWS credentials on the .env file.

Make a AWS Bucket with an Input and an output folder in it

Copy the name of the bucket you just created to BUCKET_NAME field in constants.js. do the same for the input and output folders into INPUT_FOLDER and OUTPUT_FOLDER.

You may skip the collection of the data (step 4) if you want to. To do so, in your input folder you can upload the content from temp file OR the tweets.csv.

There are 2 way of collecting data from the Twitter API (there are more, but i'll stick with this two for now):

With the stream option you connects with the Twitter API and listen to a tweet that complies with the rule you've set up. You can read more about Rule's definition here.

In the tweet-stream.js file you can change the rule to fit your needs.

const rules = [
    {
        'value': '"Snyder Cut" lang:pt -is:retweet -has:links',
        'tag': 'liga justiça snyder'
    },
];

To start your stream data gathering just:

npm run stream

Each tweet caught on the stream will be saved in the temp folder as a .csv file and will be sent to the S3 bucket previously configured.

Twitter also gives us the possibility to search for tweets in a 7-day window. For this you must pass your parameter of the search in the body of your request.

In the tweet-search.js file you can change this parameters to fit your needs.

const params = {
    'query': '"Snyder Cut" lang:pt -is:retweet -has:links',
    'tweet.fields': 'author_id',
    'max_results': 100
}

To start your recent seatch data gathering just:

npm run search

It will compile all tweets for each page of the results into a .csv file (named as configured in constants.js) and then upload this file to the S# bucket previously configured.

Now you are ready to set up your analysis on AWS Comprehend.

1. Lauch it from yout console (https://console.aws.amazon.com/comprehend/);
2. Click on 'Analysis Job';
3. Create a Job;
4. Give it a name;
5. Set the Analysis Type to be Sentiment;
6. Set the language of the input;
7. Browse on S3 to set the input file/folder and set the format accordingly;
8. Set the output folder in S3
9. give it a IAM Role
10. Done!

You should wait until the analysis is completed, you can follow its progress on the Analysis Job dashboard.

AWS comprehend will create a folder into you output folder. Copy that folders name and copy it to CPHD_IDfield on constants.js

Now you can see a brief analysis on your console:

npm run analyse

That's it.