Datasets:
metadata
language:
- en
license: mit
task_categories:
- text-classification
task_ids:
- regression
tags:
- burnout
- android
- telemetry
- stress-detection
- keyboard-dynamics
pretty_name: Synthetic Burnout Telemetry
size_categories:
- n<1K
FRIDAY Synthetic Burnout Telemetry
Synthetic Android telemetry dataset for training a lightweight burnout / urgency regression model (e.g. RoBERTa fine-tune). Each row represents a single keyboard + notification event captured on a simulated Android device.
Dataset structure
| Split | Rows |
|---|---|
| train | 500 |
| validation | 62 |
| test | 63 |
Fields
| Field | Type | Description |
|---|---|---|
input_text |
string | Serialised signal string fed directly to the tokeniser |
label |
float32 | Burnout / urgency score in [0, 1] |
app |
string | Source application (Slack, Gmail, WhatsApp, Teams, System) |
wpm |
int32 | Typing speed in words per minute |
backspaces |
int32 | Correction / backspace count in the session |
hour |
int32 | Hour-of-day the event was captured (0–23) |
session_min |
int32 | Continuous screen-on duration in minutes |
notif_count |
int32 | Pending notifications at event time |
text |
string | Raw message or notification body |
Citation
@misc{friday_burnout_2026,
title = {FRIDAY Synthetic Burnout Telemetry},
author = {Your Name},
year = {2026},
note = {Synthetic dataset for mobile stress detection research}
}