Even Our Language Is Polarized
Machine Translation Tools Find Word Meanings Vary Based on News Viewership
By Byron Spice
It's not news that U.S. politics are highly polarized or that polarization affects cable news channels. But researchers at Carnegie Mellon University, using computer translation tools in an unprecedented way, have found that even the meanings of some words are now polarized.
Everyone is speaking English, they said, yet the computer analysis of social media discussions shows viewers of different news channels are, in a sense, speaking different languages.
Based on millions of user comments on the YouTube channels for four leading cable news outlets, it seems that viewers of right-wing outlets think of "Burisma," in the same way that their left-wing counterparts think of "Kushner." A "protest" to one set of viewers is a "riot" to another. For one, it's a "mask," to another, a "muzzle."
"Black Lives Matter" (BLM) in CNN English is equivalent to "All Lives Matter" in Fox News English. Even more extreme, some right-wing news viewers use "BLM" in the same context as left-wing news viewers use "KKK" (Ku Klux Klan).
"Some of these so-called misaligned pairs seem pretty obvious," said Mark S. Kamlet, University Professor of Economics and Public Policy. "But it's surprising how different some of them are. It gives you a sense of the really tragic polarization that exists today."
Modern machine translation methods determine the meaning of a word based in large part on context — the other words that it usually appears closest to in texts. "Hello" in English and "hola" in Spanish are identical greetings and, thus, appear in the same context in different languages.
Ashiqur KhudaBukhsh, a project scientist in the School of Computer Science's Language Technologies Institute, said the idea behind the new research was to use the same method to analyze the polarization of social media. The goal was to find different English words that are used in the same context by people speaking different news languages.