Our data science team has developed a Sentiment Analysis process for original posts on the X platform (with other attention sources due to come).

The process is looking at the text to see if the post is recommending, supporting or commenting positively on the research, or whether it is cautioning, negatively commenting or making a warning on the linked publication.

Our processes uses AI and keyword analysis to calculate a strength of recommendation, which is scored on a scale from +3 (Strongly Positive) to -3 (Strongly Negative). +1 and -1 are Weakly Strong / Negative, and 0 is Neutral - typically this is when people only post the title or link, with no commentary. The process takes into account the title of the publication, and looks for additional content.

Examples: