Analyze tweets' text sentimental data for specific hashtags, keywords or time ranges with a simple Excel Workbook. This project is intended for non-technical researchers, please keep that on mind.
Note: This project uses Twitter API via tweepy module and requires the usage of Academic Research product track valid bearer token. Otherwise, you will get 403 Forbiden error responses from tweepy.
Before going strait to the steps for using this script, please take note of the system requirements. You can download python for Windows here, python for macOS here and python for Linux here.
These are the system requirements:
python >=3.6git
Once we have installed python we must install all the dependecies needed. Please find your computers' shell or command promt (cmd for Windows, terminal for macOS/Linux) and open a new window, then type:
git clone https://github.com/salvamiguel/tweet-sentiment.git
This will clone this repository on your machine. Navigate on your terminal to tweet-sentiment folder. Install dependencies with the following command:
pip3 install -r requirements.txt
Note: While installing depedencies a bunch of files for de model will be downloaded, this is normal.
Inside of tweet-sentiment folder there is a example_input.xlsx document, you can use this file as template for inserting your queries. After adding your queries save this document as input.xlsx in the same folder.
Running this tool for the first time will download all model data that is needed in order to proceed. This is only the first time while you don't delete it. UNDER DEVELOPMENT
If everything went smooth, your results will be in a output.xlsx document.
Please note that this tool wouldn't be possible without the great work from Juan Manuel Pérez, Juan Carlos Giudici and Franco M. Luque in the making of the pysentimiento sentiment analysis toolkit.