Linguistic Cues of Deception in a Multilingual April Fools' Day Context
This work provides an incremental addition to deception detection research by offering a multilingual dataset and analysis, primarily benefiting linguists and NLP researchers focused on cross-lingual applications.
The authors tackled the problem of deception detection by introducing a new corpus of deceptive April Fools' Day news articles in Greek, analyzing linguistic cues and comparing them to an existing English dataset. They built classifiers that showed AFD datasets are useful for deception detection, aligning with prior work.
In this work we consider the collection of deceptive April Fools' Day(AFD) news articles as a useful addition in existing datasets for deception detection tasks. Such collections have an established ground truth and are relatively easy to construct across languages. As a result, we introduce a corpus that includes diachronic AFD and normal articles from Greek newspapers and news websites. On top of that, we build a rich linguistic feature set, and analyze and compare its deception cues with the only AFD collection currently available, which is in English. Following a current research thread, we also discuss the individualism/collectivism dimension in deception with respect to these two datasets. Lastly, we build classifiers by testing various monolingual and crosslingual settings. The results showcase that AFD datasets can be helpful in deception detection studies, and are in alignment with the observations of other deception detection works.