The Wikipedia of Twitter and the Google Equivalent for Sentiment search
Social Media has become an integrable part of our lives.It is a storehouse of public sentiment and perception.However,a lot of this data lies unused.Tweetopedia,The Wikipedia of Twitter includes some basic functionalities which would let you thoroughly analyse the data on twitter.Some of these are:
The project is built using Django framework so you must have Python installed on your local system and also preferably Anaconda Distribution.Follow the steps given below to set up the project on your local system
$git clone https://github.com/avinsit123/Tweet-o-Pedia.git
$cd Tweet-o-Pedia
$pip install -r requirements.txt
It is a long file and might take some time to install all the dependencies on your local pc.
After the above steps are completed follow the steps given below
$mkdir ~/virtualenvironment
$source activate
Your production environment will be replaced by (base)
$cd mysite
$python manage.py runserver
Your output on the Terminal will be something like this.
Performing system checks...
System check identified no issues (0 silenced).
You have 15 unapplied migration(s). Your project may not work properly until you apply the migrations for app(s): admin, auth, contenttypes, sessions.
Run 'python manage.py migrate' to apply them.
December 29, 2018 - 13:50:33
Django version 2.1.4, using settings 'mysite.settings'
Starting development server at http://127.0.0.1:8000/
Quit the server with CONTROL-C.
Cut and paste http://127.0.0.1:8000/ on any browser of your choice or click on the link in the terminal.A WebPage of the following figure will be loaded:
After Clicking on Tweet Generator the following Window would open.
After Clicking on Twitter trends the following Window would open
After clicking on Sentiment Search,the following would open
Enter your query and click Search a window of the following type would occur.
After clicking on Hate Finder ,the following would open
The percentage of hate would be displayed as :
Because I have used a strict criteria of Evaluation the hate percentage is lower . You can modify the notebooks to change the criteria.
Those who want a downloadable version of the Wordcloud generated by the mined tweets can Dowload it by opening the static directory inside their apps.There you shall find a .jpg file