Enterprise platforms have received increasing attention as a core component of social networks and the Web. However, existing work mostly relies on fragmented logs of small units of work, like emails and chats, and focuses on who connects with whom without sufficient account of collaboration content and dynamics. This work systematically explores tracking collaborations across sequences of meetings as a new approach to interpreting their long-horizon dynamics. Linking 45,426 meetings in a large multinational technology company based on full transcripts and 1.6 million extracted agenda items, we establish a cross-meeting collaboration network of 6,065 collaborations. The network recovers the natural shapes of workplace collaborations: meetings, as snapshots of ongoing collaboration, link into largely tree-shaped structures, while the work content forms nested directed acyclic graphs (DAGs). Further, we explore how these networks evolve over time, examining three established perspectives: task division, team composition, and temporal continuity. Each explains part of the dynamics but does not capture the distinctness of long-horizon workplace collaboration: e.g., work flows in a consistent direction between a few pairs of subjects, yet a collaboration's subject explains little of how its meetings are conducted. Instead, accumulating the agenda, interaction, and language of meetings along each tree yields a signature of the collaboration, a distinctive profile that picks out the collaboration of a held-out meeting at 4.5 times chance. The signature models collaboration better than team or task views, individually or combined, in next-meeting prediction and tree-level fitting. We discuss the implications of these cross-meeting dynamics for designing office applications and support tools, and call for next-generation Web systems that represent collaborations over their long horizon.

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