AI & understanding / INDEPENDENT FIELD GUIDE

Sentiment Tags Feed

A sentiment label needs a defined text unit and a target. Keep tone separate from truth, importance, and any prediction about future events.

Name the tone. Keep the nuance.

The core idea

A positive quotation inside a critical article does not automatically describe the author’s view. Decide whose attitude is being labeled and what it concerns. Whole-document, paragraph, and sentence tasks can produce different interpretations, so the interface should explain the scope rather than show an unexplained colored dot.

A workable starting pattern

Write annotation rules with difficult examples, including negation and mixed viewpoints. Allow uncertainty. Evaluate errors by text type and topic when the sample supports that comparison. Keep numerical outputs tied to their actual model and configuration instead of treating every score as a universal measure.

AN EXAMPLE TO THINK THROUGH

“The interface is attractive, but exports fail” expresses different evaluations of two aspects. A mixed label or separate aspect annotations may be more faithful than one confident positive or negative badge.

What this page does—and does not—offer

TagsFeed does not score live news, infer personal traits, or provide sentiment-based market predictions. This guide concerns interpretation of text.