Loading...
Paper Number
ICIS2025-1729
Paper Type
Complete
Abstract
Although open collaboration communities adopt bots to perform a wide range of tasks, many bots struggle to establish effective collaboration with humans. To address this issue, we draw on sociotechnical theory and a network perspective, proposing that human-bot collaboration emerges from human-bot task fit. We examine how task attributes, including variety, uniqueness, homogeneity, and combinative power, shape the formation of collaboration between humans and bots. Using data from Wikipedia, we apply exponential random graph models to analyze a bipartite human-bot network. Results show that bots with higher task variety, uniqueness, and combinative power foster collaboration, while human task variety and human-bot task homogeneity inhibit it. These findings enrich the literature on human-bot collaboration by uncovering the role of task attributes in shaping collaborative relationships. They also offer practical implications for community managers in approving and governing bots.
Recommended Citation
Huang, Rongjiang; Qiu, Jiangnan; Gao, Shuangyan; and Liu, Jiaming, "Understanding the Formation of Human-bot Collaboration in Open Collaboration Communities: Human-bot Tasks Perspective" (2025). ICIS 2025 Proceedings. 18.
https://aisel.aisnet.org/icis2025/hti/hti/18
Understanding the Formation of Human-bot Collaboration in Open Collaboration Communities: Human-bot Tasks Perspective
Although open collaboration communities adopt bots to perform a wide range of tasks, many bots struggle to establish effective collaboration with humans. To address this issue, we draw on sociotechnical theory and a network perspective, proposing that human-bot collaboration emerges from human-bot task fit. We examine how task attributes, including variety, uniqueness, homogeneity, and combinative power, shape the formation of collaboration between humans and bots. Using data from Wikipedia, we apply exponential random graph models to analyze a bipartite human-bot network. Results show that bots with higher task variety, uniqueness, and combinative power foster collaboration, while human task variety and human-bot task homogeneity inhibit it. These findings enrich the literature on human-bot collaboration by uncovering the role of task attributes in shaping collaborative relationships. They also offer practical implications for community managers in approving and governing bots.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
15-Interaction