An experimental data-visualization tool using machine learning seeks to analyze real-time news from a variety of sources based on subjectivity, sentiments, and content analysis. Could this be the answer to determining the bias of news sources?

“The Living News” was created by Jibin Varghese at the National Institute of Design, India. Outside of its valuable capabilities, the visualization is special in itself.

The visualization gives the news a visual identity as if it is an living cell which has its own characteristics and categories. Thus, generating a unique identity to each news feed, hence The Living News.

The experimental tool uses machine learning libraries to analyze incoming news content to then perform three types of NLP analysis:

Sentimental Analysis
How emotional the story is and if it’s a positive, neutral, or negative sentiment.

Subjectivity Analysis
The overall subjectivity of the story. For example, is the content of the story opinionated and subjective, or factual and objective in nature.

Content Analysis
What the topic and overall content of the story related to. The tool finds categories or classifications that the content related to.

Here’s a preview of the prototype:

To see more from the project go here.

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