Sentiment analysis is a helpful tool for qualifying the way your online audience feels about your products or services, or any given topic. However, as with any written or verbal communication, the way these feelings are conveyed is complex - not even humans can correctly identify the sentiment of a sentence if they lack context! As such, we have honed Aina's deep learning AI algorithms to take into account all the background information that exists about a particular online mention.
As a result of this new model of sentiment detection, Aina can now:
- Better understand the context around the subject of sentiment analysis;
- Analyze the original post as well as the comments to the post;
- Detect post sentiment with higher accuracy.
For example, let's say your search query returned a post where the author asks the online community to weigh in and compare your brand against the competitor. On the face of it, such a post can be considered neutral - after all, the author of the original mention is not passing positive or negative judgment. However, the comments to that post can be either favourable or critical to your brand. With its improved understanding of context, Aina can now better detect post comments' sentiment by understanding the original post context.
This kind of analysis reveals a more accurate picture of how your monitoring subject is perceived by your online audience.
Note that, since Aina has gotten better at accurately detecting sentiment, the ratio of your positive, negative and neutral posts may change starting Dec. 1 compared to the previous monitoring period. Consider this in your future analysis and reports!
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