Automated detection of nostalgic text in the context of societal pessimism

Lena Clever, Frischlich Lena, Trautmann Heike, Grimme Christian

Abstract

In online media environments, nostalgia can be used as important ingredient of propaganda strategies, specifically, by creating societal pessimism. This work addresses the automated detection of nostalgic text as a first step towards automatically identifying nostalgia-based manipulation strategies. We compare the performance of standard machine learning approaches on this challenge and demonstrate the successful transfer of the best performing approach to real-world nostalgia detection in a case study.