3 reasons why automated content classification is important

With the latest TrustServista 2.0 release we introduced a couple of news API endpoints, such as Statistics and Classification, reaching a new milestone in the research and development of our text and news analytics capabilities. Why is automated content classification using the IPTC Newscodes and IAB v2 taxonomies is an important tool for every media professional? 

Many newsrooms struggle with maintaining a standardized classification of their content.

There are many classification “standards”, some proving better to use for programmatic advertising purposes (like IAB v2) and some better for common vocabularies used in the news industry (such as IPTC Newscodes). And a lot of times content creators do not follow these standards or even adhere to the standards enforced by their own organizations. The result is content that is hard to search or perform analytics on.

The newsroom software/web content management system does not automatically recommend any classification.

Journalists focus on creating content, marketing experts in making that content reach as wide audience. And software makes everything possible, but does not go a step further. AI-powered content augmentation systems, like TrustServista, can automatically classify the content as its being produced, even finding similar internal or competitive content, in real-time. The process of following internal standards for classification, SEO and programmatic advertising optimization does not have to be a burden, it can be done automatically.

Thorough competitive analysis requires well-structured content.

Nowadays competitive analytics in the online media space is mainly focused on audience reach (social media engagements) and advertising conversions. However, these 2 main KPIs cannot be improved without a good understanding of what topics does the competition focus on, and how they create the content. Intelligent analytics on the competition means understanding and measuring their content automatically, from classification, summarization, named entity extraction and sentiment, to social media engagement metrics and influence measurement.

How does TrustServista classify content?

TrustServista uses two of the main methods for content classification –  IAB v2 and  IPTC Newscodes – using deep learning algorithms. Any webpage or plain text submitted to the API or Web Dashboard is automatically classified using these 2 taxonomies.

Examples

 

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