Measuring and Fostering Peace through Machine Learning and Artificial Intelligence

TL;DR

This paper presents machine learning methods to measure peace levels in media and social platforms, and introduces a Chrome extension to promote peaceful media consumption and creation.

Contribution

It develops neural network models for peace measurement from news and social media, and creates MirrorMirror, a tool to provide real-time peacefulness feedback to viewers.

Findings

High accuracy in peace measurement across datasets

71% of young adults view news via short videos on social media

MirrorMirror effectively provides real-time feedback on media peacefulness

Abstract

We used machine learning and artificial intelligence: 1) to measure levels of peace in countries from news and social media and 2) to develop on-line tools that promote peace by helping users better understand their own media diet. For news media, we used neural networks to measure levels of peace from text embeddings of on-line news sources. The model, trained on one news media dataset also showed high accuracy when used to analyze a different news dataset. For social media, such as YouTube, we developed other models to measure levels of social dimensions important in peace using word level (GoEmotions) and context level (Large Language Model) methods. To promote peace, we note that 71% of people 20-40 years old daily view most of their news through short videos on social media. Content creators of these videos are biased towards creating videos with emotional activation, making you angry to engage you, to increase clicks. We developed and tested a Chrome extension, MirrorMirror, which provides real-time feedback to YouTube viewers about the peacefulness of the media they are watching. Our long term goal is for MirrorMirror to evolve into an open-source tool for content creators, journalists, researchers, platforms, and individual users to better understand the tone of their media creation and consumption and its effects on viewers. Moving beyond simple engagement metrics, we hope to encourage more respectful, nuanced, and informative communication.