Independent Computational Content Analysis Lab

Evidence behind media patterns.

Anmat conducts structured content research using computational analysis, documented datasets, and human interpretation to investigate framing, recurring narrative patterns, source representation, and coverage gaps.

The Problem

We examine large media corpora to identify recurring linguistic associations, represented voices, and coverage gaps that require contextual interpretation.

Methodology

Research Infrastructure

Documented corpus decisions, computational methods, human review, contextual interpretation, and clear analytical limitations.

Published research evidence

Model choice changes how Arabic media discourse is interpreted

Anmat and InfoTimes compared Arabic BERT models and general-purpose language models across 10,990 Arabic news headlines related to the 2023 Gaza war.

The study found that model selection is not a neutral technical decision: different models produced materially different sentiment interpretations.

10,990

Arabic headlines analyzed

6specialized Arabic BERT models
3general-purpose language models

Collaborate With Us.

Have a research question about framing, source representation, recurring language, or coverage gaps across a defined media corpus?

Email Us At
info@anmat.media

Tell us what you are studying

We work with researchers, NGOs, journalism schools, think tanks, and media analysts on datasets, methods, workshops, and custom media ecosystem analysis.

Discuss an analysis

Share the topic, outlets, region, or narrative question you want to investigate.