How editorial teams can use Automated Topic Spotting
When editors have to manually filter, contextualize and evaluate news and events in line with the editorial strategy, topic planning becomes a challenge with the constant flood of information. It raises the question of how this process can be made more efficient in the age of digitalization. One possible answer is “Automated Topic Spotting“.
What is Automated Topic Spotting?
Automated Topic Spotting is an AI-supported, automated process that enables editors to quickly keep track of new trends in a large number of incoming reports and find relevant topics – without manual research. This is made possible by advances in artificial intelligence (AI), especially generative AI.
Modern systems can not only monitor connected sources in real time – from internal feeds to agency reports or social media – but also analyze and pre-filter the collected messages and data. This is achieved through personalization based on the specific interests and preferences of certain target groups or even individual editors and according to defined criteria and search terms. The result: It automatically creates manageable and relevant subject areas for editorial teams and thus a clear overview of current information events.
How can Automated Topic Spotting be used in editorial offices?
Our CEO Jochen Schon explains this in detail in his article for Horizont.net (German only), including:
- How media companies can use AI as a tool and deal more efficiently with the constant stream of information
- What happens when automated, AI-supported topic spotting is seamlessly integrated into workflows
- What the technology can already do – from monitoring to personalization
- Where a collaborative synergy between editors and AI can lead
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