Making Social Dynamics and Content Evolution Transparent in Collaboratively Written Text

This dissertation presents models and algorithms for accurately and efficiently extracting data from revisioned content in Collaborative Writing Systems about (i) the provenance and history of specific sequences of text, as well as (ii) interactions between editors via the content changes they perform, especially disagreement. Visualization tools are presented to gain further insights into the extracted data. Collaboration mechanisms to be researched with these new data and tools are discussed.