Alleviating Media Bias Through Intelligent Agent Blogging

TL;DR

This paper introduces an intelligent agent framework that combines text analysis and Web 2.0 technologies to help consumers access balanced news and hold media outlets accountable, addressing media bias challenges.

Contribution

It presents a novel framework integrating existing tools to analyze online news sources with minimal manual effort for bias detection and accountability.

Findings

Framework facilitates analysis of online news sources

Combines text analysis with Web 2.0 technologies

Supports rational decision-making and accountability

Abstract

Consumers of mass media must have a comprehensive, balanced and plural selection of news to get an unbiased perspective; but achieving this goal can be very challenging, laborious and time consuming. News stories development over time, its (in)consistency, and different level of coverage across the media outlets are challenges that a conscientious reader has to overcome in order to alleviate bias. In this paper we present an intelligent agent framework currently facilitating analysis of the main sources of on-line news in El Salvador. We show how prior tools of text analysis and Web 2.0 technologies can be combined with minimal manual intervention to help individuals on their rational decision process, while holding media outlets accountable for their work.