From Newsletters to Insight: A Case Study of Using AI to Map CALA’s Organizational Evolution (2018–2025)

From Newsletters to Insight: A Case Study of Using AI to Map CALA’s Organizational Evolution (2018–2025)

This presentation explores how AI-enabled workflows can transform organizational newsletters into structured datasets for analysis and decision-making. Using CALA Newsletter issues from 2018–2025 as a case study, the project combines AI-assisted text extraction, content classification, metadata creation, and data visualization to identify trends in organizational priorities over time. Attendees will learn how tools such as Microsoft Copilot and Python can be used to analyze narrative content, reveal emerging themes, and generate visualizations that support organizational assessment and historical documentation.

Xiao, Daniel

2026-04-24

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/

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Text; Document; Presentation

This presentation examines how AI-enabled workflows can transform narrative newsletters into a structured evidence base for organizational analysis. Focusing on CALA Newsletter Issues 118–131 (2018–2025), the study demonstrates how computational methods can surface longitudinal patterns in organizational priorities across a period of significant social and technological change. The project employs a multi-stage workflow integrating MS Copilot AI-assisted text extraction, segmentation, classification, and visualization. Newsletter content was first converted from PDF into analyzable text using Copilot, with manual validation to ensure accuracy. The corpus was then segmented into standardized categories—Events, Professional Development (PD), Awards, Advocacy, Publications, and AI-related topics—and organized into a unified Excel-based Master Log. Each issue was further annotated with structured metadata, including dominant themes, key events, notable shifts, topic distributions, and editorial tone. Building on this structured dataset, Python-based analysis combined with AI-assisted reasoning produced a series of cross-issue visualizations, including trend lines, topic density heatmaps, revealing the emergence, decline, and transformation of CALA’s activities over time.

2026-04-24

2026-04-24

Xiao, Daniel