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title: "WatchTower" | |
emoji: "🗼" | |
colorFrom: "black" | |
colorTo: "blue" | |
sdk: "gradio" | |
sdk_version: 3.0.20 | |
app_file: app.py | |
pinned: true | |
**Note: Use WatchTower via the embedded interface at [HF.space](https://hf.space/embed/User1342/WatchTower/?)!** | |
## Files | |
- app.py - Gradio web interface for WatchTower. | |
- radical_tweet_aggregator.py - Pinpoint Wrapper and Tweepy integration for aggregating and assigning extremism scores to user posts. | |
- predictor.py - The Pinpoint wrapper script. Also see /Pinpoint and the respective Github repo for the Pinpoint codebase. | |
## Tweet Attribution and Bias | |
Please Note: If an account is blocked by Pinpoint, that is not to say that the author(s) of this tooling deem such a user to be violent or extremist, instead it is simply a result of the training the machine learning model has undergone and a result of the analysis on the last 10 tweets of the user in question. WatchTower is undergoing tuning to ensure it provides a fair and an as un-bias as possible assessment of Tweets, feedback is always welcome. | |
## Model Statistics | |
Pinpoint has several configurations, the configuration used by WatchTower has the following stats: 0.827 (accuracy), 0.676 (recall), 0.739 (precision), 0.706 (f-measure). | |
## Constraints | |
The Twitter APIv2 rate limits blocking requests to a 'User rate limit (User context): 15 requests per 15-minute window per each authenticated user'. This will pose issues to WatchTower when blocking larger numbers of users and will cause the tooling to hang or crash completely. A fix would be to change hosting and have a running service in the background that performs the blocking tasks adhering to the rate limiting. |