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Filtering the news from topics that increase anxiety Disclosure Number: IPCOM000250541D
Publication Date: 2017-Jul-31
Document File: 2 page(s) / 448K

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The Prior Art Database

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Filtering the News from Topics that Increase Anxiety

News consumers are repeatedly subjected to anxiety-inducing stories, as the same news is often propagated through many outlets (e.g., television, news feeds, email, websites, etc.). This makes it difficult for a consumer to avoid the repetition of distressing news.

A method or system is needed to help alleviate anxiety caused by the consumption of online news content.

There are many wearables that measure the user’s stress level. There is a correlation between types of content and people's emotional state*. These technologies can be combined to form a solution to the problem.

The novel solution is a system that filters media content based on the user’s detected level of anxiety upon previously consuming that content.

The system measures the user’s anxiety level at the moment the user reads certain content in the news. The system follows the user while reading and watching the news, measures the anxiety level, and detects (using Natural Language Processing (NLP) text analytics) what type of content causes the user the most anxiety. With this knowledge, the system can filter newsfeeds for the user going forward, without elevating the anxiety level of certain topics.

To implement this system to filter from the news topics that Increase anxiety:

1.    User indicates to the system that decreased anxiety is wanted when browsing the news

2.    User sees videos and images, and reads text in news feeds

3.    System analyzes contents o...