Summary of A Comparative Analysis Of Transformer and Lstm Models For Detecting Suicidal Ideation on Reddit, by Khalid Hasan et al.
A Comparative Analysis of Transformer and LSTM Models for Detecting Suicidal Ideation on Reddit
by Khalid Hasan, Jamil Saquer
First submitted to arxiv on: 23 Nov 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computation and Language (cs.CL); Social and Information Networks (cs.SI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A deep learning-based approach is proposed for detecting suicidal ideation from user posts on Reddit. The authors evaluate various transformer-based models (BERT, RoBERTa, DistilBERT, ALBERT, and ELECTRA) and LSTM-based models to identify the most effective method. The dataset was curated from diverse subreddits and analyzed using linguistic, topic modeling, and statistical techniques. Results indicate that RoBERTa achieved the highest accuracy (93.22%) and F1 score (93.14%), followed by an LSTM model with attention and BERT embeddings (92.65% accuracy, 92.69% F1). The study demonstrates the potential of transformer-based models to improve suicide ideation detection, paving the way for robust mental health monitoring tools from social media. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how well artificial intelligence can detect suicidal thoughts on social media platforms like Reddit. The researchers tested different AI models and found that some did much better than others. They used a lot of data from many different parts of the internet to train their models, and then tested them to see which one worked best. The best model was called RoBERTa, and it was really good at finding suicidal thoughts – almost 94% accurate! The study shows that AI can be very helpful in spotting people who might be struggling with suicide, which could help save lives. |
Keywords
» Artificial intelligence » Attention » Bert » Deep learning » F1 score » Lstm » Transformer
