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Evaluating the Robustness of Non-Credible Text Identification by Anticipating Adversarial Actions

Projektbeschreibung

Automatische Inhaltsfilter im Kampf gegen Desinformation

Die Verarbeitung natürlicher Sprache und maschinelles Lernen werden als Maßnahmen gegen Desinformation und ähnliche Probleme betrachtet. Lösungen mit natürlicher Sprachverarbeitung können zum Beispiel Falschmeldungen, Bots in sozialen Medien und den Einsatz von Propagandastrategien erkennen. Doch was ist mit gezielter Desinformation, die so veröffentlicht wird, dass sämtliche automatischen Filteralgorithmen überwunden werden? Das EU-finanzierte Projekt ERINIA wird Methoden zur Erkennung von schädlichen Beispielen untersuchen und die Robustheit von Textklassifikationen analysieren. Die Projektergebnisse werden an Forschungsgemeinschaften weitergereicht, um weitere Debatten über den Einsatz automatischer Inhaltsfilter im Kampf gegen Desinformation anzuregen.

Ziel

As challenges posed by misinformation become apparent in the modern digital society, state-of-the-art methods of Artificial Intelligence, especially Natural Language Processing (NLP) and Machine Learning, are considered as countermeasures. Indeed, previous research has shown that NLP solutions can detect phenomena such as fake news, social media bots or usage of propaganda techniques. However, little attention has been given to the robustness of these approaches, which is especially important in the case of deliberate misinformation, whose authors would likely attempt to deceive any automatic filtering algorithm to achieve their goals.

The goal of the ERINIA project is to explore the robustness of text classifiers in this application area by investigating methods for detecting adversarial examples. Such methods aim to perform small perturbations to a given text piece, so that its meaning is preserved, but the output of the investigated classifier is reversed. To that end, previously unexplored directions will be pursued, including training reinforcement learning solutions and leveraging research on simplification and style transfer. Finally, the developed tools will be used to check the robustness of the current state-of-the-art misinformation detection solutions.

The project includes a range of training activities for the researcher and a plan for dissemination of the obtained results to various research communities. It also takes into account the society at large, as the project outcomes can inform further discussion on whether automatic content filtering is a viable solution to the misinformation problem.

Koordinator

UNIVERSIDAD POMPEU FABRA
Netto-EU-Beitrag
€ 165 312,96
Adresse
PLACA DE LA MERCE, 10-12
08002 Barcelona
Spanien

Auf der Karte ansehen

Region
Este Cataluña Barcelona
Aktivitätstyp
Higher or Secondary Education Establishments
Links
Gesamtkosten
Keine Daten