Sentiment analysis of posts 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 brands 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.
HypeAuditor takes as many posts within a given period (last 90 days for reports) of time as available, in order to improve model quality.
The data is updated weekly.
Why sentiment analysis matters for influencer marketing
Sentiment analysis helps brands and marketers go beyond surface-level engagement metrics and understand how an influencer's audience truly reacts to their content. A high share of positive comments indicates that followers genuinely appreciate the creator's posts. Conversely, a notable share of negative comments may indicate audience dissatisfaction or controversy, which is an important brand-safety consideration before launching a collaboration. For ongoing campaigns, tracking sentiment over time can reveal whether sponsored content is landing well or generating backlash. You can also review Sentiment analysis at the campaign level to aggregate comment sentiment across all posts and influencers in a campaign.
