PyTextSentiment
Emotion Detection & Classification of Tweets Using Streaming APIs. [NLTK] [Scikit Learn] [Twitter Streaming API] [Bing API]
Install / Use
/learn @mjaglan/PyTextSentimentREADME
Emotion Detection And Classification of Tweets
How to Run
-
Go to your terminal.
-
Clone this repository and go inside it
git clone https://github.com/mjaglan/PyTextSentiment.git cd PyTextSentiment -
Edit following files:
app/assets/BingCredentials/bingClientId.txt app/assets/BingCredentials/bingClientSecret.txt app/assets/TwitterAPI/credentials.txt app/assets/input.txt -
Run the following script
. ./restart-all.sh
Web UI
- This application inside docker container page can be browsed at http://CONTAINER-IP:9091/
Project Structure
- Training dataset files:
app/assets/Resource/searchKeys - Get Feeds by text search query:
app/assets/Resource/searchKeys/testFiles - Bag of Words for emotion tagging and classification:
app/assets/Resource - Output twitter data directory:
app/assets/twitterData
Project Overview
The term paper of this work is present here. Below are the highlights of the work done + the results generated for live tweets on 28 December 2015.
References
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