Twitter-Healthcare

tweepy_healthcare_finder.py

1.) Streams twitter data

2.) Filters the data based on the keywords in the first column of DiseaseHashtags.csv

3.) Organizes the twitter data into the following file structure:

    ## Data structure for tweets to pass into mongo collection
    
    my_data = {
        'id': decoded['id'],
        'text': decoded['text'],
        'place': {'country': country,
                  'full_name': full_name},
        'user': {'screen_name': decoded['user']['screen_name'],
                 'location': decoded['user']['location']},
        'entities': {'hashtags': hashes}
    }

4.) If a mongod.exe mongoDB instance is open streams the each tweet record into a collection called 'twitter_healthcare' in a database called 'twitter'

mongo_search_healthcare.py

Some basic pymongo search queries on the data being streamed into the twitter.twitter_healthcare collection.

These queries can be dynamically run on the database collection as it is being streamed in.

1.) location_pipeline: creates a query to find the top locations of tweets in the dataset.

2.) hashtag_pipeline: creates a query to find the top hashtags in the dataset.

3.) project_matches_pipeline: creates a query to return the tweets from a specific location.

4.) aggregate: runs the created queries.

DiseaseHashtags.csv

csv file containing the sets of keywords to filter tweets by - first column

fields.txt

List of field names to export mongo collection to csv.

mongoexport create csv.txt