Large scale analysis of violent death count in daily newspapers to quantify bias and censorship

TL;DR

This study develops techniques to quantify bias and censorship in newspapers by analyzing keyword occurrences over time, gender, and location, revealing significant gender bias and historical censorship effects in Italian and US newspapers.

Contribution

The paper introduces novel algorithms for detecting bias and censorship in newspaper archives, applying them to large datasets to quantify historical censorship and gender bias.

Findings

Gender bias in Italian newspapers with fewer reports on female deaths.

Approximately 75% of domestic deaths and suicides were censored during certain periods.

The distribution of reported deaths follows a power law, affected by geographical distance.

Abstract

In this work we develop a series of techniques to quantify the presence of bias and censorship in newspapers. These algorithms are tested analyzing the occurrence of keywords `killed' and `suicide' (`morti', `suicidio' in Italian) and their changes over time, gender and reported location on the complete online archives (42 million records) of the major US newspaper (The New York Times) and the three major Italian ones (Il Corriere della Sera, La Repubblica, La Stampa). Since the Italian language distinguishes between the female and male cases, we find the presence of gender bias in all Italian newspapers, with reported single female deaths to be about one-third of those involving single men. We show evidence of censorship in Italian newspapers both during World War 1 and during the Italian Fascist regime. Censorship in all countries during World Wars and in Italy during the Fascist period is a historically ascertained fact, but so far there was no estimate on the amount on censorship in newspaper reporting: in this work we estimate that about $75\%$ of domestic deaths and suicides were not reported. This is also confirmed by statistical analysis of the distribution of the least significant digit of the number of reported deaths. We also find that the distribution function of the number of articles vs. the number of deaths reported in articles follows a power law, which is broken (with fewer articles being written) when reporting on few deaths occurring in foreign countries. The lack of articles is found to grow with geographical distance from the nation where the newspaper is being printed.