“🟢 Amazing! 🚀”, “🟡 Good start but could be better. 🤷♀️”, “🔴 Not very nice. 😬”
are all things your might have seen your community members say. From now on, though, you need not worry about not knowing what emotional tone their messages carry, as…
we just released the widely requested Content: Sentiment feature!
👩🏽🏭 How does it work?
- we pass the contents of your member activities to the Natural Language Toolkit, which returns their sentiment and confidence score
- if you think the automatically assigned sentiment is not up to snuff, we allow for a manual overwrite of the sentiment value
- we also plot charts of
Sentiment Over Timefor keywords to help you understand sentiment trends
- you can also use the new
Activity Sentiment filterto hone in on a specific sentiment subset (for example, just activities with negative sentiment to understand what your community members dislike)
- the technical nitty-gritty
- we sentiment-scored 30days worth of activities for our users + any new activity that will come in
- the thresholds based on which we assign the call out (such as "Overwhelmingly positive") in the overall sentiment chart can be found here 👇
- the activity types we score are listed in this doc
📽️If video is more your jam, check out this Loom demo!
🧙🏽♀️Why is it awesome?
- because you can now understand the emotional tone of your community contributions
- observe trends such as “Is my negative sentiment ratio decreasing?”
- in tandem with our
keywordsfeature, evaluate, for example, the reception of new features