twitter-mbti-personality-classifier

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twitter-mbti-personality-classifier

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Machine Learning classifier to predict MBTI personality type of an individual using their tweets 🙍

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// repository documentation

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# Introduction
This is a *machine learning* project. This trained machine learning classifier can predict a person's **MBTI**(Myers–Briggs Type Indicator)
personality type using an individual's *social media posts* like **twitter posts**. For better understanding and explanation of decision made
in this project, a [jupyter notebook](./main.ipynb) is provided, which contains all the *code, explanation, analysis (EDA), model performance and analysis of
our trained models*.

### Note
For some reason github cannot render complete jupyter notebook last commit. If you are only seeing first 2 sections, I would recommend using 
[nbviewer.jupyter.org](http://nbviewer.jupyter.org/), To view jupyter notebook click 
[here](http://nbviewer.jupyter.org/github/sahilsehwag/twitter-mbti-personality-classifier/blob/master/main.ipynb) or you can clone the repo 
and view locally.

### About MBTI
The Myers Briggs Type Indicator (or MBTI for short) is a personality type system that divides everyone into 16 distinct personality types across 4 axis:
* **Introversion** (I)/**Extroversion** (I)
* **Intuition** (N)/**Sensing** (S)
* **Thinking** (T)/**Feeling** (F)
* **Judging** (J)/**Percieving** (P)
<br>
You can read more about the MBTI test [here](https://en.wikipedia.org/wiki/Myers-Briggs_Type_Indicator).

### Dataset
The [dataset](./personality-test.csv) on which this classifier is trained, contains around 50 posts per user about 8000 users with their *MBTI*
personality type known. Dataset is provided in the repo itself [personality-test.csv](./personality-test.csv).
<br>
Few features of dataset are:
* Posts of more than 8000 users.
* Last 50 posts per user, each entry is separated by '|||'.

### Caveats
We have trained individiual classifier for each characterstics pair. Although script's final prediction will be complete MBTI type, the first 2
pairs/models i.e. Introversion/Extroversion and Intuition/Sensing are not reliable at any level, due to the fact that data regarding these characterstics
is heavily biased towards single attribute. For more explanation or better understanding, look at this [jupter notebook](./main.ipynb).

# Usage
```
python3 main.py <username>
```
**NOTE**: **&lt;username&gt;** is twitter handle of target user(without @)

# Dependencies
* python 3.x
* numpy
* pandas
* matplotlib
* sklearn
* nltk
* colorama

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