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Deception detection in text and its relation to the cultural dimension of individualism/collectivism
2021
Natural Language Engineering
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In addition, we investigate if a universal feature set for cross-cultural text deception detection tasks exists. We evaluate the predictive power of different feature sets and approaches. ...
This is more evident for the usage of pronouns and the expression of sentiment in deceptive language. ...
We would like to thank the anonymous reviewers, Yannis Tzitzikas and Stasinos Konstantopoulos for their insightful feedback which helped us to improve this paper. ...
doi:10.1017/s1351324921000152
fatcat:qkjilzrntraxdkszglwynrsg5y
Deception Detection for the Russian Language: Lexical and Syntactic Parameters
2017
Proceedings of the Workshop Natural Language Processing and Information Retrieval
unpublished
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
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The field of automated deception detection in written texts is methodologically challenging. ...
On the example of the Russian Deception Bank Corpus we estimate the impact of three groups of features (POS features including bigrams, sentiment and psycholinguistic features, syntax and readability features ...
Acknowledgments This research is supported by a grant from the Russian Foundation for Basic Research, N 15-34-01221 Lie Detection in a Written Text: A Corpus Study. ...
doi:10.26615/978-954-452-038-0_001
fatcat:bmtoujny65flrmoczglg5ztqfe