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45 changes: 24 additions & 21 deletions projects/home/recap/README.md
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Expand Up @@ -6,40 +6,43 @@ The model receives various features, describing the Tweet and the user whose tim


Those are:
"recap.engagement.is_favorited": The probability the user will favorite the Tweet.
"recap.engagement.is_good_clicked_convo_desc_favorited_or_replied": The probability the user will click into the conversation of this Tweet and reply or Like a Tweet.
"recap.engagement.is_good_clicked_convo_desc_v2": The probability the user will click into the conversation of this Tweet and stay there for at least 2 minutes.
"recap.engagement.is_negative_feedback_v2": The probability the user will react negatively (requesting "show less often" on the Tweet or author, block or mute the Tweet author)
"recap.engagement.is_profile_clicked_and_profile_engaged": The probability the user opens the Tweet author profile and Likes or replies to a Tweet.
"recap.engagement.is_replied": The probability the user replies to the Tweet.
"recap.engagement.is_replied_reply_engaged_by_author": The probability the user replies to the Tweet and this reply is engaged by the Tweet author.
"recap.engagement.is_report_tweet_clicked": The probability the user will click Report Tweet.
"recap.engagement.is_retweeted": The probability the user will ReTweet the Tweet.
"recap.engagement.is_video_playback_50": The probability (for a video Tweet) that the user will watch at least half of the video
- "recap.engagement.is_favorited": The probability the user will favorite the Tweet.
- "recap.engagement.is_good_clicked_convo_desc_favorited_or_replied": The probability the user will click into the conversation of this Tweet and reply or Like a Tweet.
- "recap.engagement.is_good_clicked_convo_desc_v2": The probability the user will click into the conversation of this Tweet and stay there for at least 2 minutes.
- "recap.engagement.is_negative_feedback_v2": The probability the user will react negatively (requesting "show less often" on the Tweet or author, block or mute the Tweet author)
- "recap.engagement.is_profile_clicked_and_profile_engaged": The probability the user opens the Tweet author profile and Likes or replies to a Tweet.
- "recap.engagement.is_replied": The probability the user replies to the Tweet.
- "recap.engagement.is_replied_reply_engaged_by_author": The probability the user replies to the Tweet and this reply is engaged by the Tweet author.
- "recap.engagement.is_report_tweet_clicked": The probability the user will click Report Tweet.
- "recap.engagement.is_retweeted": The probability the user will ReTweet the Tweet.
- "recap.engagement.is_video_playback_50": The probability (for a video Tweet) that the user will watch at least half of the video

For ranking the candidates these predictions are combined into a score by weighting them:
"recap.engagement.is_favorited": 0.5
"recap.engagement.is_good_clicked_convo_desc_favorited_or_replied": 11* (the maximum prediction from these two "good click" features is used and weighted by 11, the other prediction is ignored).
"recap.engagement.is_good_clicked_convo_desc_v2": 11*
"recap.engagement.is_negative_feedback_v2": -74
"recap.engagement.is_profile_clicked_and_profile_engaged": 12
"recap.engagement.is_replied": 27
"recap.engagement.is_replied_reply_engaged_by_author": 75
"recap.engagement.is_report_tweet_clicked": -369
"recap.engagement.is_retweeted": 1
"recap.engagement.is_video_playback_50": 0.005
- "recap.engagement.is_favorited": 0.5
- "recap.engagement.is_good_clicked_convo_desc_favorited_or_replied": 11* (the maximum prediction from these two "good click" features is used and weighted by 11, the other prediction is ignored).
- "recap.engagement.is_good_clicked_convo_desc_v2": 11*
- "recap.engagement.is_negative_feedback_v2": -74
- "recap.engagement.is_profile_clicked_and_profile_engaged": 12
- "recap.engagement.is_replied": 27
- "recap.engagement.is_replied_reply_engaged_by_author": 75
- "recap.engagement.is_report_tweet_clicked": -369
- "recap.engagement.is_retweeted": 1
- "recap.engagement.is_video_playback_50": 0.005


We cannot release the real training data due to privacy restrictions. However, we have included a script to generate random data to ensure you can run the model training code.

To try training the model (assuming you have already followed the repo setup instructions and are inside a virtualenv).

Run
```
$ ./projects/home/recap/scripts/create_random_data.sh
```

This will create some random data (in $HOME/tmp/recap_local_random_data).

```
$ ./projects/home/recap/scripts/run_local.sh
```

This will train the model (for a small number of iterations). Checkpoints and logs will be written to $HOME/tmp/runs/recap_local_debug.

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