Murmur Lab's Sentiment Analysis feature provides triple value for brand management by quantifying user sentiment tendencies on social media through natural language processing techniques:
First, the system automatically generates visual charts that clearly show the percentage distribution of positive, negative and neutral comments under the target topic. Brand managers can visualize the tone of public attitudes, for example, 70% positive comments and 15% negative feedbacks after a new product launch.
Secondly, by clicking on "See Insight", you can view the content of specific posts and gain insight into the real user opinions behind the emotions. For example, if you find that negative comments are focused on the design of the new packaging rather than the functionality of the product, you can quickly pinpoint the problem.
Finally, it supports exporting standardized sentiment analysis data for easy integration into weekly brand reports or decision-making meetings. A case study shows that a tech brand discovered 35% users' complaints about updates causing regression in functionality through this feature, and promptly rolled out a patch to fix it after negative reviews dropped 22%.
The function operates on a clear path: enter brand keywords in Network Atlas → view automatically generated sentiment distribution → analyze typical posts in depth → export data to assist decision-making.
This answer comes from the articleMurmur Lab: a smart tool for analyzing social media trends in real timeThe
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