Build a semantic word analysis of the ENRON dataset with PYTHON

Data basis to be used for the analysis: https://www.kaggle.com/wcukierski/enron-email-dataset

Step 1: build a python notebook on the basis of the work done by https://www.kaggle.com/zichen/explore-enron and try to reproduce their results

Step 2: The most important step: Generate a python code for listing which user uses which emoticons how often

Step 3: Please deliver the python code with comments

List of positive and negative emoticons.

Emoticon    Meaning    Sentiment Class
😀    Laughing    Positive
🙂    smile    Positive
o:)-    innocent    Positive
😎    cool    Positive
:$    Happy blush    Positive
🙁    defeated    Negative
🙁    Crying    Negative
😮    shocked    Negative
>(    Grumpy    Negative
(@)    Angry red    Negative
X|    Dead    Negative

Attached: Relevant Papers for this work to be cited whenever possible (1. Buildingemotionaldictionaryforsentimentanalysisofonlinenews, 2. pone.0171649), and additional papers if fragments of their methods are used.