React Score leverages 17 advanced natural language processing models to provide contextual analysis of media content. The models quantify harm, controversy, spam, and emotionality indicators, enabling AI to automatically detect and classify content rather than requiring manual review. This streamlines understanding of potential content impacts.

Grouped indicators will provide insight as follows:

The red/gray gradient indicates high or low-React scores, with gray representing scores near 0 and red representing scores near 100. Scores below 12% appear mostly gray and neutral. As scores exceed 50%, the red coloring becomes more prominent, signaling the need for attention.

Example: An Emotionality score of 75% shows if there are high levels of negative feelings, sarcasm, or subjectivity.

When viewing a Mention Stream, you can click on ‘Filter’. There you will see a section called ‘React Score’. This will display two categories:

(1) React Score Average: the defaulted option, the slider for the React score average will allow you to choose the desired range to apply as a filter to the mentioned stream.

(2) React Score Categories: the sliders associated with each React category will allow you to choose the desired range to apply as a filter to the mentioned stream.

NOTE: You will have the ability to use either sorting option, however, these options cannot be used simultaneously.

When generating a report, mentions can be sorted by React Score Average, in a ‘ascending’ or ‘descending’ order. In this view, only the Average React Score is shown. To see the score for a sorted React Category, you must hover over the Average React Score.

Within your exported CVS file, you will have access to fields that offer a granular breakdown of React Score. This information illustrates the impact of your mentions.