dayfundora / personality-type

Recognition of Persomnality Types from Facebook status using Machine Learning

Personality Types Predictor

Personality is a fundamental basis of human behavior, it affects the interaction and preferences of an individual. Social networks have become a prominent platform for opinions and thoughts, this indicated that there is a strong correlation between the personality of users and the way they behave on social networks.

In this work we explore the use of Machine Learning techniques to infer personality traits of a user from Facebook status updates.

For personality recognition, the models were trained for each of the five personality traits, given by the Big-5 personality classification, using LIWC (Linguistic Inquiry and Word Count) characteristics and were compared different classification methods, such as Logistic Regression, RandomForestClassifier, Mul tinomialNB, GradientBoostingClassifier, SVC, LinearRegression, Ridge,SGDRegressor; the performance of the systems was measured using precision.

Requeriments

Run the following commands if you don't have them already:

pip install streamlit
pip install nltk
pip install Flask
pip install bson
pip install scikit-learn
pip install numpy
pip install os-sys
pip install scipy
pip install pandas
pip install matplotlib
pip install liwc
pip install selenium

To install it all:

pip install requeriments.txt

Documentation

For a more in-depth documentation read here

Download

If you want to download this project to work on it, you will need the models for each aspect of the personality, both for LIWC and TFIDF.

AGR_categorical_model_liwc.pkl
AGR_categorical_model_tfidf.pkl
CON_categorical_model_liwc.pkl
CON_categorical_model_tfidf.pkl
EXT_categorical_model_liwc.pkl
EXT_categorical_model_tfidf.pkl
NEU_categorical_model_liwc.pkl
NEU_categorical_model_tfidf.pkl
OPN_categorical_model_liwc.pkl
OPN_categorical_model_tfidf.pkl

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