| --- |
| license: cc-by-sa-4.0 |
| --- |
| |
| ## Context |
| A *stressor* is a **specific** cause or trigger of an individual’s mental health issue, such as stress, anxiety, or suicidal thoughts. Identifying stressors is a key step toward understanding and improving mental well-being. |
|
|
| ## Content |
| This dataset contains **4,001 manually annotated online posts** collected from **June 2018 to June 2022**. Each sample includes the following fields: |
|
|
| - `text`: The content of the individual's post. |
| - `labels`: The identified stressor(s) within the post, including their start and end positions (word-level). |
| - `time_interval`: A numeric value (1-8) representing the half-year period in which the post was published. |
| - For example, `1` indicates the post was published between 2018-07-01 and 2018-12-31, |
| while `8` corresponds to 2022-01-01 to 2022-06-30. |
| |
| ### Data Partitioning |
| By default, we divide the data based on time to simulate a real-world scenario: 1. Samples from `time_interval = 1` to `7` serve as training data (historical period). 2. Samples from `time_interval = 8` serve as test data (most recent half-year). This setup allows researchers to train models on past data and evaluate performance on future data. |
|
|
| However, you are free to re-partition the dataset based on your specific task or experimental design. |
|
|
|
|
| ## Citation |
| Wang, Xin, et al. *"MISE: Meta-knowledge Inheritance for Social Media-Based Stressor Estimation."* Proceedings of the ACM on Web Conference 2025. |
|
|
|
|
