White Paper: Human-AI Collaboration in Conflict Analysis: Text Classifier Development with Peacebuilders

This paper documents a collaborative research process involving peacebuilders and data scientists in Kenya and Sudan to develop AI-based text classifiers for monitoring online polarization and hatespeech. The method describes a participatory annotation process in which practitioners and domain experts contributed to problem definition, annotation design, iterative validation, and model evaluation. Fine-tuned BERT-based classifiers were … Read more

Smart Social Media Analysis (Part 2)

Webinar on annotation Strategies for Text Classification. Join is for this webinar to explore practical strategies for creating high-quality labeled datasets that reflect the nuanced realities of conflict-sensitive topics, like developing annotation guidelines, managing inter-annotator agreement, and how to handle edge cases. Whether you’re preparing to fine-tune models for your own organization’s needs, are curious … Read more

Smart Social Media Analysis (Part 1)

15 October 2025 Join us for an interactive session exploring Phoenix’s newest feature: open-source language model integration for text classification. Learn how to move beyond simple keyword searches to understand meaning, context, and nuanced patterns in social media data. We’ll cover the fundamentals of text classifiers, demonstrate how to apply pre-trained models from our curated … Read more

Understanding to intervene: The codesign of text classifiers with peace practitioners (2024)

This publication was written by Julie Hawke, Helena Puig Larrauri, Andrew Sutjahjo and Benjamin Cerigo. Originating from a unique partnership between data scientists (datavaluepeople) and peacebuilders (Build Up), this commentary explores an innovative methodology to overcome key challenges in social media analysis by developing customized text classifiers through a participatory design approach, engaging both peace … Read more