Introducing AI Sentiment Analysis in the Sonar Ecosystem

What is Sentiment Analysis? Why is it useful?

How does Sentiment Analysis Work?

  1. Data collection — Extracting a large amount of data that is representative of a wide range of opinions, not too biased one way or the other
  2. Data cleaning — Ensuring that aspects of the data unnecessary to the algorithm are cleaned up (URLs, misspellings, erroneous labels)
  3. Algorithm selection — Depending on the problem and data, different algorithms have pros and cons (Naive Bayes, Support Vector Machines, Linear Discriminant Analysis, Neural Networks, etc.)
  4. Model evaluation and deployment — Extrapolating the accuracy of the model in the real world and deploying it to customers.

What makes our Sentiment Analysis cutting-edge?

No. Not this kind of Transformer.

Sentiment Lab

New features in Token Studio

  • Community Mood — The overall market’s current attitude toward the specific project being looked at.
  • Admins Mood — (Something completely unique to Sonar) The measure of the current attitude a project’s leaders have within their community and the tone of their communication — achieved by analyzing community chatrooms and forums!

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