Twitter Results
Guardian Results

The Word on the Streets

Installation

pip install -r requirements.txt

Run

python Guardian_API.py

Fill in the entire form, select Show and then click Next

Sentiment Analysis of Twitter and Guardian News.

Used Natural Language Processing (Vader Sentiment Analysis techniques) and Microsoft Cognitive Services to predict sentiment of topics from Twitter and Guardian News.

Visualization of Data.

Of interest in various fields in FinTech as flag indicators for Economic Catastrophies as a result of radical Political Change / Natural Disasters.

It provides a quantitative estimate of the impact of Social, Political, Natural and Economic events.

Results (Between 2016-06-01 and 2016-07-01)

Guardian News:

Alt text

Twitter:

Built With

python

Submitted to

HackPrinceton Fall 2016

Created by

Created code which mines Twitter for keywords in a particular Time-Interval. Used Natural Language Processing with Vader Lexicon (nltk stuff) and Microsoft Cognitive Services to build an Ensemble Sentiment Analysis Entity. Plotted results using Matplotlib. Worked on GUI interface with Dan the Man(?). Put the different parts of the code fragments together.

Private user
Worked on web-based data visualization graphics in Javascript using d3.js, HTML, CSS and hosted it on Azure via Github. Couldn't parse the JSON string at the end to link data, but everything else was complete. GUI and pyplot was used as alternative in the interest of time

Michelle Chen
I created the code which mines data from the Guardian News company from their API and cleanes the corresponding data. The program searches for selected keywords in the Guardian headline database and how many times the key word is found in the Guardian database for a user specified time interval. I also helped creating the input GUI for the program.

Daniel Geirsson

Updates

Private user started this project — Nov 13, 2016 01:42 AM EST

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