Sentiment Analysis Tool for products based on the recent tweets and review articles fetched from Google. The entire project was done as a part of Veritas CE2016 Hackathon. The task was to be completed within 48 hours and a live demo had to be given to the judges and a ten minute video demo was to created for public viewing. The back end of the project was done in Python using the Django Framework whilst the front end was a web page using HTML, CSS, JavaScript, and Bootstrap. We have used the tweepy library for fetching the tweets and GoogleSearcher library(using Selenium) to get the links of the review articles. These articles were then scraped using Beautiful Soup API. The Sentiment analysis of all the data was done using a Naive Bayes Algorithm and the output was the percentage positivity, percentage negativity, and percentage neutrality in the data. For statistical interpretation of data, several graphs were shown (like the tweet count vs time) using the amCharts.
Install python 2.7, pip from python.org
Once these two are installed then use pip to install these following modules:
pip install django
pip install beautifulsoup
pip install bs4
pip install unirest
pip install requests
pip install tweepy
pip install collections
pip install json
pip install urllib2
pip install lxml
pip install pickle
pip install re
pip install selenium
Go to sentiment_analysis folder and execute the following command: python manage.py runserver A localhost server will start running at '127.0.0.1:8000' Visit this over a browser, preferrably google chrome
If at all after execution the program throws some error of type "{package_name} module not found", then it is because of some dependency. Execute command "pip install {package_name}" to install that package. Inconvenience regretted.