This Project contains various features for Social Network Analysis on Twitter.

-Creating a recommendation graph:

1. Open "grabData_for_Graph.py"
2. Put your username on screen_name
3. Don't touch credentials (the tokens are valid)
<!--- please read the comments before proceeding to the next step--->
<!---Step 4 running time depends on amout of friends! maybe it takes up to 20 hours to finish (limitations of twitter's API)-->
<!---but you can change setting to speed-up the process, for example: Line 67, you can reduce the friends_count-->
<!---for skiping this part, I put the folder, including all .json files, in my project-->
4. Run the file and wait until it is finished. <!--- you can skip this step if you wish--->
5. Open "Graph.py"
6. Note: screen_name in both files should be the same
7. Run the "Graph.py"
8. "screen_name".png is the final graph.

-Analyzing Tweets:

1. Open "Project.ipynb" in Google Colab or Jupyter Notbook.
2. Enter Username
3. Upload "emotions.txt" on your directory
4. select "Run All" and wait until its finished.
5. it takes at least 45 minutes to run all cells.