Linguistic Cues of Deception in a Multilingual April Fools’ Day Context
Authors: Katerina Papantoniou, Panagiotis Papadakos, Giorgos Flouris, Dimitris Plexousakis (University of Crete, Institute of Computer Science - FORTH, 2021)
Topic: Fact Checking and Fake News Detection

Abstract
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 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 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 datasets can be helpful in deception detection studies, and are in alignment with the observations of other deception detection works.

Introduction
is a long standing custom, mostly in Western societies. It is the only day of the year when practical jokes and deception are expected. This is the case for all social interactions, including journalism, which is generally considered to aim at the presentation of truth. Every year on this day, newspapers and news websites take part in an unofficial competition to invent the most believable, but untrue story. In this respect, news articles fall into the deception spectrum, as they satisfy widely acceptable definitions of deception as in Masip et al. Masip2005Deception. The massive participation of news media in this custom establishes a rich corpus of deceptive articles from a diversity of sources.  Although articles may exploit common linguistic instruments with satire news, like exaggeration, humour, irony and paralogism, they are usually considered a distinct category. This is mainly due to the fact that they also employ other mechanisms which characterize deception in general, like sophisms, and changes in cognitive load and emotions <cit.> to deceive their audience. articles are often believable, and there exist cases where sophisticated articles have been reproduced by major international news agencies worldwide[https://www.nationalgeographic.com/history/article/150331-april-fools-day-hoax-prank-history-holiday]. This motivated us to extend our previous work on linguistic cues of deception and their relation to the cultural dimension of individualism and collectivism <cit.>, in the context of the . That work examines if differences in the usage of linguistic cues of deception (e.g., pronouns) across cultures can be identified and attributed to the individualism/collectivism. Specifically, the contributions of this work are: * A new corpus that includes diachronic and normal articles from Greek newspapers and news websites[The collection is available in: <https://gitlab.isl.ics.forth.gr/papanton/elaprilfoolcorpus>], adding one more collection to the currently unique one in English <cit.>. * A study and discussion of the linguistic cues of deception that prevail in the Greek and English collection, along with their similarities. * A discussion on whether the consideration of the individualism/collectivism cultural dimension in the context of aligns with the results of our previous work. * An examination of the performance of various classifiers in identifying articles, including multilanguage setups.

Conclusion
We introduced a new dataset with news articles in Greek andanalyzed and compared its deception cues with another English one.The results showcased the use of emotional language, especially of positive sentiment, for deceptive articles which is even more prevalent in the individualistic English dataset.Further, deceptive articles use less concrete language, as manifested by the increased use of adverbs, hedges, and boosters and less usage of named entities, spatial related words and conjunctions compared to the truthful ones.The future and past tenses were correlated with deceptive and truthful articles respectively. All the above, mainly align with previous work <cit.>, except from some differences in the usage of pronouns for the Greek dataset, which is attributed to the idiosyncrasies of the news domain.The accuracy of the deployed classifiers offered adequate performance,with no statistically significant differences between the best logistic regression and the BERT models. In the future we aim at creating even more crosslingual datasets for deception detection tasks through crowdsourcing and by employing the Chattack platform <cit.>.