jonathanbgn

8 ms·

1. 31.▲
   by jonathanbgn 7y ago

   This is not what I said. I said that the accuracy is not 100% perfect, but that you can improve it by turning on BERT in the menu bar.
2. 32.▲
   by jonathanbgn 7y ago

   Let me elaborate a bit more on how the app computes sentiment. For a particular word, its sentiment is the average of the sentences' sentiments which contain both the word and the brandname (in order to identify the sentiment targeted
3. 33.▲
   by jonathanbgn 7y ago

   Thanks!
4. 34.▲
   by jonathanbgn 7y ago

   That's a fair criticism. Sentiment analysis is quite hard to get right on social media messages because of diversity, subtlety, and many other aspects. From my experience with similar commercial and (very!) expensive products, their ac
5. 35.▲
   by jonathanbgn 7y ago

   Thanks for letting me know, I just increased the quota from the hosting service. The website is online again now!
6. 36.▲
   by jonathanbgn 7y ago

   Thanks for the feedback! It's a great idea, I'll definitely implement some Named Entity Recognition or other contextual model in the future to be able to distinguish from common words. As for the subreddit, it's already on my
7. 37.▲
   by jonathanbgn 7y ago

   Thanks! The basic (default) version for the sentiment analysis is based on TextBlob library, but you can choose to activate deep learning to analyze sentiment with Google AI's BERT (trained on Twitter messages), though it is quite slow
8. 38.▲
   Show HN: Visualize how HN/Reddit talk about your company and products(brandimage.io)

   74 points by jonathanbgn 7y ago|33 comments