Page Comparison

States whether the classification request has already been processed. If processed data exists, Verity returns the results from the database. If not Verity starts a new processing request.

The current processing status of the analysis request.

The URL of the page, video, image, or text analyzed by Verity, as applicable.

A unique identifier generated for the classification request.

The standard ISO 639-1 code for the language of the content. Verity currently supports content in:

• English

• Japanese

Verity video analysis currently supports English only.

Note: If Verity detects an unsupported language, a status of NOT_SUPPORTED is returned.

The IAB v1.0 categories identified for the page.

IAB v1.0 categories are widely adopted in programmatic and Real-Time-Bidding (RTB) ad marketplaces. IAB v1.0 categories are organized into the following tiers:

• Tier 1  identifies broad level categories, such as Pets, defined with the following targeting depths:

  • Category/portal

  • Site section

  • Page

• Tier 2 and greater identify more granular categories, such as Dogs, and are nested under Tier 1 categories. 

Refer to the Verity Taxonomy document for a listing of IAB v1 categories.

Verity video analysis does not support IAB v1.0 categories.

The IAB v2.0 categories identified for the content.

The IAB defined a more granular content taxonomy in IAB Tech Lab Content Taxonomy v2.0 (released in 2017). IAB v2.0 defines additional content classifications and restructures existing IAB v1.0 classifications. 

Each IAB v2.0 category has a unique three-digit ID, and is structured into a tiered hierarchy with up to 4 tiers of categories.

Refer to the Verity Taxonomy for a listing of IAB v2 categories.

The top Keywords identified for the content, listed in order of prominence.

The final aggregated Brand Safety summary result for the content.  

If any threat classifications are identified with a high-risk level, the safe value is false and the content is considered unsafe.

If no (or low-risk) threat classifications are identified, the safe value is true, and the content is considered safe.

Threat categories are part of GumGum’s brand safety taxonomy. GumGum classifies content into nine threat categories. For a complete list of Threat category IDs and Names, refer to Threat Categories in the Verity Taxonomy document.

To detect possible threats, Verity analyzes and scores all the extracted content. Verity then correlates the scores to determine a per-category threat risk-level for the content.

Possible threat category risk-levels are:

• VERY_HIGH

• HIGH

• MODERATE

• LOW

• VERY_LOW

The Events classifier identifies seasonal events such as the Olympics (e.g. annual, bi-annual, 4-yearly events) for the purposes of contextual ad targeting. 

Verity lists up to five Event categories, in order of prominence. For a complete list of Event category IDs and Names, refer to Event Categories in the Verity Taxonomy document.

Verity video analysis does not support Events.

Identifies and extracts opinions within digital content. 

The positive, neutral, and negative levels of sentiment expressed in the content are evaluated. For contextual targeting purposes, a sentiment level of neutral or positive is generally recommended.

The date and time of the classification. 

Content classifiers predict the likelihood that the given content belongs to one or more IAB categories.

Machine learning predicts event categories by applying data models trained on large-scale collections of event-related content pages.

A set of rules derives, scores, and ranks the most important keywords.

Machine learning predicts the sentiment of each sentence within content by applying models trained on content with varying tones of voice. Verity returns an aggregated breakdown of the proportion of sentences in the content that are positive, neutral or negative (referred to as Document Level Sentiment Analysis).