Exploring an Online Community of Blind Programmers by Using Topic Modeling and Network Analysis

Abstract

Much work has been carried out to highlight the accessibility challenges of blind programmers. Yet, relatively little has been known about how blind programmers help each other to solve problems. We present a data‐driven approach to explore collaborative problem‐solving of users in the Program‐l community of, by, and for blind programmers. We collected 8,344 longitudinal email threads from 778 users from 2004 through 2022 to observe the dynamics of collaborative problem‐solving among blind programmers. Our embedding‐based topic modeling and assortativity network analysis reveal that the knowledge of blind programmers diverges between when asking and answering questions. Our findings also suggest that users who have a high cluster level in the first year of activity and members are more likely to interact with other members with different roles. Our paper contributes to the field of social computing by introducing the first large‐scale study of a unique community of blind programmers.