2021

Laitinen, Kaisa; Laaksonen, Salla-Maaria; Koivula, Minna

Nonhuman communicators are challenging the prevailing conceptualizations of technology-mediated team communication. Slackbot is a social bot that can be configured to respond to trigger words and, thus, take part in discussions on the platform. A set of 84 bot-related communication episodes were identified from a journalistic team’s Slack messages (N = 45,940) and analyzed utilizing both qualitative content analysis and interaction process analysis (IPA). This integrated mixed-methods analysis revealed novel insights into the micro-level dynamics of human–machine communication in organizational teams. In response to Slackbot’s greetings, acclamations, work-related messages, and relational messages, we identified how the team members respond to the bot, discuss it, and summon it to appear on the platform. Further, the IPA revealed that the bot-related communication episodes are shaped by the bot’s responses toward more socioemotional and personal functions. Findings suggest that a team-configured social bot can manifest and facilitate relational team communication.