Gendering Electoral Truth: AI, Disinformation and Democratic Backsliding In the Global South

Abstract Submissions Closed

WG10 Digital Sociology (host committee)
RC32 Women, Gender, and Society

Language: English and French

Session Type: Oral

Elections in the Global South increasingly unfold in a public space saturated by disinformation, algorithmic amplification, and AI-generated contents. These dynamics do not affect citizens equally: women candidates, vulnerable voters, and feminist activists are disproportionately targeted by manipulated imagery, gendered harassment, and coordinated delegitimation campaigns that reshape who can speak, contest, and be believed. This session invites papers that examine how contemporary struggle over “electoral truth” is gendered, and how the production of doubt and misinformation becomes a mechanism of political exclusion and harassment.

Building on recent Global South experiences, this session welcomes papers that examine how digital citizenship is exercised, denied, or reinvented amid misinformation and fake news. We invite papers that make empirical and theoretical contributions on gendered disinformation and harassment; AI, deepfakes and electoral integrity; women’s digital mobilisation and counter-publics; platform governance and accountability; and the epistemic politics of trust and credibility.

We particularly welcome decolonial perspectives that resist importing theoretical frameworks from the global North wholesale, and that foreground actors — from grassroots movements to electoral institutions — navigating these crises. Comparative papers spanning regions (e.g. Africa, Latin America, South/East Asia) are encouraged.

Submissions to this session should focus on placing gender at the centre of debates on disinformation and democratic erosion, and contribute to how inequalities are produced, contested, and transformed in turbulent times. Submissions in both English and French are welcome.

Session Organizers:
Mireille MANGA, University of Yaoundé II, Cameroon, manmir2001@yahoo.com
Daniel AMOAH, Memorial University, Canada, dkamoah@mun.ca