Sentiment analysis of video comments shows the percentage of comments that look positive, negative, and neutral. HypeAuditor analyzes comment text and emoji using Machine Learning models to make these conclusions. All languages are supported.
Sentiment analysis feature is focused on helping clients understand the average audience's attitude to influencers' content. It has 3 categories:
Positive: for all comments that represent joy, happiness, approval and overall positive attitude to the given post.
Negative: for all comments that represent anger, sadness, disagreement and overall negative attitude to the given post.
Neutral: comments that could not be considered positive or negative and lack any emotional meaning.
Why does it matter? Understanding comment sentiment helps brands and marketers evaluate how an influencer's audience actually feels about their content. A high volume of negative comments alongside strong engagement may signal controversy rather than genuine affinity, which is a critical signal when selecting a creator for a campaign or assessing brand safety.
HypeAuditor takes as many content within a given period (last 90 days for reports) of time as available, in order to improve model quality.
The data is updated weekly.
Sentiment analysis is also available at the post and campaign level in the Campaigns tool.
