Journalists, Gender and Participation in Comment Spaces

Project description

This project will comparatively assess how male and female journalists engage in comment spaces at the Guardian. Using a random sample of journalists, a content analysis will be conducted on their comments 'below the line', scraped from the Guardian website. Interviews will be conducted with the journalists to explore how and why they comment the way they do. The internship will work on the collection and coding of the comment data, contributing to both the scraping and content analysis.

Project outcome

This project performs both large-scale and close analysis of comments by journalists from articles on The Guardian online from 2006-2017. On a large scale, it uses machine learning to establish the emotional content of comments. On a smaller scale, it analyses a representative sample of comments by male and female journalists. We aim to determine whether there are gendered differences between how journalists engage with commenters. To do so, we code comments according to an established system of engagement types (eg argument, correction, moderation). Thus far, machine learning outcomes indicate the importance of trust to these interactions, and closer analysis indicates that men and women at The Guardian engage directly with commenters at nearly equal rates. We will also establish whether they also demonstrate similar kinds of engagement.

2019 Internship project


Associate Professor Scott Wright
School of Culture and Communication


Adam Hembree
School of Culture and Communication