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The importance of tags in online news media

What's New in Publishing 20 Jul 2021 06:30

If you work in news publishing, there’s a good chance you already use some type of tags in your published content.

After all, Parse.ly found that 70 percent of digital media publishers use tags and that was back in 2015. The number is surely even higher in 2021. But as our research has shown, different publishers adopt wildly different approaches to tagging content, with very different results.

So whether or not you already use tags, an overview of what tags are and what they can do might be useful. In this post, I’ll try to summarize not only that but also why using NLP (natural language processing) for tagging might be a good idea.

What are tags?

In the context of news content, tags are a type of metadata. A news article is usually accompanied by metadata, such as the post’s author, timestamp, and info about which of the site’s sections it belongs to (such as news, business, culture, etc.). Tags—sometimes also referred to as topics or keywords—can supplement them.

Before talking about tags themselves, it’s a good idea to briefly discuss the sections that make up a (news) site. Sections form the structure of a news site. The sections can be designed in-house or it can be based on an existing standard. There are several comprehensive classification systems, such as IPTC or IAB, which publishers can use or customize to suit their own needs.

Headquartered in Prague, Czech Republic, Geneea is an AI startup developing products for automatic text processing. They focus on advanced NLP and NLG solutions for media companies and for analysis of news in general. Their Media Assistant is an AI-based tool created specifically for journalists to support them in their work. The system automatically analyses the text of articles, and based on their content, it offers ranked suggestions of keywords, images, and related articles, taking into account internal rules and preferences of the media house.

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