Sentiment Analysis

Opoint’s Sentiment Analysis attaches a sentiment score to every article at the point of indexing, classifying content as positive, negative, or neutral and providing a nuanced score between -1 and +1. The score arrives pre-attached in the feed alongside the article text and other enrichment metadata, with no additional processing required on your end.

How it works

Opoint’s proprietary algorithm scores each article on a scale from -1 (strongly negative) to +1 (strongly positive), with 0 representing neutral. The score reflects the article’s overall tone rather than sentiment toward a specific entity or topic within it.

The algorithm delivers 70% accuracy. For media monitoring use cases where sentiment is one signal among several, this is a practical and useful addition to the feed. For workflows that require high-confidence sentiment classification as a primary decision input, the score works best as a starting point for human review rather than a standalone determinant.

Language and source coverage

Sentiment scoring is available for English, Swedish, Danish, and Norwegian. Within those languages, scoring currently applies to sources with a global rank above 10,000. Sources outside that threshold — lower-traffic regional and local-language outlets — are not scored. If your monitoring universe relies heavily on regional or niche sources, confirm coverage against your specific source list before building sentiment-dependent workflows.

What sentiment scoring adds to your feed

For platforms that already consume Opoint’s structured news feed, sentiment is an additional enrichment layer that requires no integration changes. Each scored article carries the sentiment value as a field in the existing JSON schema alongside IPTC topic codes, entity tags, readership scores, and deduplication signals.

Common uses include tracking tone shifts in brand coverage over time, flagging negative spikes for editorial review, and adding a sentiment dimension to media impact reporting. Sentiment scoring is available across Opoint’s API and feed products.

Your Questions, Answered

What sentiment scores does Opoint provide?

Each article receives a score between -1 and +1, where -1 is strongly negative, 0 is neutral, and +1 is strongly positive. The score reflects the article's overall tone. It is delivered as a field in the JSON payload alongside other enrichment metadata.

How accurate is the sentiment scoring?

Opoint's proprietary algorithm achieves 70% accuracy. For media monitoring workflows where sentiment is one input among several, this provides a reliable signal. For use cases where high-confidence classification is critical, the score works best alongside human review rather than as a standalone decision input.

Which languages does sentiment scoring cover?

English, Swedish, Danish, and Norwegian. Scoring applies to sources with a global rank above 10,000 within those languages. Coverage of lower-traffic regional and local-language sources is not currently included. Contact the solutions team to confirm coverage against your specific source requirements.