From the 1 of 12 linked papers with an AI index.
12 papers
Bias at the Borderline: Who Gets the Benefit of the Doubt in Peer Review?
Hazem Ibrahim, Talal Rahwan, Yasir Zaki
The paper analyzes ICLR peer‑review data to examine whether authors from prestigious institutions, certain countries, or all‑male teams receive more favorable discretionary decisio…
Auditing Differential Visibility of Political Content on TikTok
Hazem Ibrahim, Tewoflos Girmay
Allegations that TikTok shadow bans political content shape what creators post, what advertisers fund, and how regulators act, yet they are hard to adjudicate because platforms do…
Causal evidence of racial and institutional biases in accessing paywalled articles and scientific data
Hazem Ibrahim, Fengyuan Liu, Khalid Mengal +4
Scientific progress depends on researchers' ability to access and build upon the work of others. Yet, much published work remains behind expensive paywalls, and even accessible art…
Schadenfreude in the Digital Public Sphere: A cross-national and decade-long analysis of Facebook news engagement
Nouar Aldahoul, Hazem Ibrahim, Majd Mahmutoglu +4
Schadenfreude, or the pleasure derived from others' misfortunes, has become a visible and performative feature of online news engagement, yet little is known about its prevalence,…
Who Gets Seen in the Age of AI? Adoption Patterns of Large Language Models in Scholarly Writing and Citation Outcomes
Farhan Kamrul Khan, Hazem Ibrahim, Nouar Aldahoul +2
The rapid adoption of generative AI tools is reshaping how scholars produce and communicate knowledge, raising questions about who benefits and who is left behind. We analyze over…
The Political Ideology of Large Language Models: Measurement, Inconsistency, and Persuasive Influence
Nouar Aldahoul, Hazem Ibrahim, Matteo Varvello +4
Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the world. As people become increasingly reli…