

To utilize Sonar effectively, adhere to these steps: 1. Select your data sources from options like Twitter and Reddit. 2. Train Sonar using relevant sample data to refine your query. 3. Focus analysis on pertinent data to obtain precise results rapidly. 4. Apply sentiment analysis to gauge the emotional tone of the data. 5. Employ topic tagging to gain insights into conversation trends and sentiments by topic.
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Sonar is a sophisticated social data insights platform that automates social listening and utilizes machine learning for semantic analysis. It reveals the sentiment behind social media data, categorizes text, and analyzes word relationships.
To use Sonar, follow these steps: 1. Choose data sources like Twitter and Reddit. 2. Train Sonar with relevant test data. 3. Analyze relevant data for instant, accurate results. 4. Use sentiment analysis to understand data emotion. 5. Tag data by topic to analyze conversation volume and sentiment by topic.
Sonar currently supports Twitter and Reddit.
Sonar's sentiment analysis surpasses the accuracy of generic AI tools such as Amazon Comprehend and ChatGPT-3.
Yes, Sonar can tag and analyze data by topic, providing insights into conversation trends and sentiments.
Key features of Sonar include automated social listening, machine learning-powered semantic analysis, sentiment analysis, topic modeling, relevant data filtering, and contextual word relationship analysis.
Common use cases for Sonar include brand monitoring, competitor analysis, customer sentiment understanding, and identifying popular social media topics.