Active Depression Monitoring and Alert System in Reddit through Machine-Learning a social media depression monitoring and alert system using a combination of machine learning and heuristics algorithms.
- raw data: data taken from pushshift for confession, depression, suicidewatch subreddit
- processed data: data after manual labeling and split into test and train dataset
- data for phase 2: data from the result of our most performant model: bag of words model. This is data input for group_14_d_Monitoring System Code.ipynb
- group_14_0_data_scraping.ipynb: Code to pull from pushshift.io
- group_14_0_data_scraping_by_author_for_stage_2.ipynb: Code to pull data from pushshift.io for phase 2 analysis
- group_14_0_data_scrapping_preprocess_before_label: Code to preprocess the data before labeling and split into train and test for phase 1
- group_14_a_BOW_models.ipynb: Machine Learning with Bag of Words Method for post classification stage 1
- group_14_b_CNN-LSTM-Update.ipynb: Deep Learning Model of CNN + LSTM for post classification stage 1
- group_14_c_bert.ipynb: Deep Learning Model with Transfer learning from BERT - ELECTRA for post classification stage 1
- group_14_d_Monitoring System Code.ipynb: Phase 2 Monitoring system rules
- Goh Wen Wei Victor - A0067229Y
- Ken Cheah - A0218906Y
- Krishnan Ananth - A0218894M
- Tommy Kangdra - A0218866N
- Xiao Yidi - A0218962W