Ferretly analyzes each post from your subject's social media for both risks as well as sentiment. These factors are then combined to arrive at at a social media score. Our sentiment algorithm is a rule-based tool that was specifically attuned to sentiments expressed in social media. We incorporate a lexicon (list of features e.g., words) that are labelled according to their semantic orientation.
Each post is given a sentiment value from -1 to 1. You can view the posts sentiment (positive, neutral or negative) by the icon representation on the post within the subject's POSTS view. From left to right is the negative, neutral and positive icons for sentiment.
By clicking on the sentiment icon you can toggle the value of the sentiment. This allows you to make corrections and then you can use the Refresh Report action from the subject's fly-out menu to regenerate your background report.
From the dashboard, you can also see the sentiment over time which averages the post sentiment over a dynamic range to better understand how sentiment trends over time. A red sentiment line means that your subject's posts are on average negative, whereas a green line indicates your subject's posts are positive overall. Below this chart on the dashboard is the sentiment makeup with will you with the total number of posts as well as how many were positive, neutral or negative.
Sentiment analysis within Ferretly compliments the machine learning algorithm that looks at specific risk factors for each post. It can provide you with a broad understanding of how an individual expresses themselves on Social Media. Note that Sentiment has a lower weighting than risks classifications in the overall score.