uses tweepy to interact with Twitter's API. Set size of chunk, chunk size, and number of chunk needed, chunk count. Save tweets into each chunk untill it's full, and save the chunk into a file, tweets<filecount>.txt. Python has the module json to convert json file to Python dictionary directly. Keep saveing file until it reaches the chunk count.

tweets will be missed during the reinitialization of the stream if twitter connection is interrupted.

1. ./twitterStream.sh<chunk size><chunk count>
2. Scans files for urls. If url found, retreives the title of the linked page. Parses through files tweets0.txt - tweets.txt twitterURLFinder.py <fileCount>

Implement indexing and searching function with Whoosh library in Python.

Build web-based interface with Flask library in python. Implement map function with flask-googlemaps library.

Implement Okapi BM25 scoring function with Whoosh.

Add time factor: timeFactor = 1/(currentTime - tweetTime).

Most recent posts have largest value. It's then wegighted to blance its relevance to the BM25 score.

Overall Score = Score(BM25) + Score(time)

1. Take in duplicates and retweets as normal.
2. It's not a dynamic interface.
3. Most tweets don't have geo information.

1. pip install flask, flask-googlemaps, geocoder, whoosh.
2. run indexSearch.py:

python indexSearch.py

3. run app.py:

python app.py

4. Input search query into the search box