As the field of NLP advances, more NLP approaches find their way into practical applications. Yet while NLP has been successful in helping humans to find and extract information, only few applications help us to consume, evaluate and aggregate information from interconnected, changing texts. The focus of this area is to develop novel applications that assist humans in solving complex real-life text-based tasks - from editorial support to machine-assisted reading via NLP-enhanced annotation.
Peer review is a cornerstone of academic quality control, yet the pressure to publish causes significant reviewing overload in many key scientific fields, jeopardizing scientific progress and undermining public trust in science. While NLP applications for analysis of scientific publications are abundant, the field of peer review analysis is just taking up the pace. Peer review is an excellent target for cross-document discourse analysis, and this area puts special focus on developing NLP applications for peer reviewing assistance.