Bridging Dictionary

Identify how words in American political discourse differ across the political divide

In our highly polarized society, it’s not surprising that we see significant differences in how words are used by those with opposing political and cultural viewpoints. The Bridging Dictionary, an interactive web-based prototype developed by MIT’s Center for Constructive Communication, identifies the different way words and phrases are used by different constituencies and–similar to a traditional dictionary or thesaurus–gives meanings and also attempts to suggest less polarized (bridging) alternatives.

Natural Language Processing, Large Language Model, Bridging, Communication, Politics

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How does it work?

Utilizing natural language processing, the Bridging Dictionary compares how two media outlets on the opposite sides of the US political spectrum–foxnews.com on the right, and msnbc.com on the left–differ in the meanings assigned to the same words or phrases. This involved gathering approximately 18,000 articles from foxnews.com and 13,000 from msnbc.com published since 2021. The content was then split into millions of sentences for analysis. The first analysis measured the differences in usage frequency and sentiment. For those terms that show significant differences, a further qualitative comparison was done using a large language model (LLM) to describe the way the usage varies between the two outlets. The LLM was then prompted to provide evidence for its conclusions by citing specific references, as well as alternative “bridging” terms.

For more thoughts on the Bridging Dictionary, its current challenges, and possible future potential, we invite you to visit CCC Senior Advisor and former CBS News President Andrew Heyward’s blog post on the CCC website.


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Introducing the Bridging Dictionary
Could seeing how opposite sides of the US political spectrum use the same words differently be a first step toward greater cross-political understanding?

On January 7, CCC launched the Bridging Dictionary (BD), an interactive web-based prototype that uses natural language processing to identify the different ways two media outlets – foxnews.com on the right and msnbc.com on the left – assign different meanings to the same words and phrases, and then attempts to suggest less polarized (bridging) alternatives.

12.06.2024 | Andrew Heyward