Banner Portal
The truth below the surface
PDF

Keywords

Hate speech
EEG biosignals

How to Cite

1.
Niebuhr O, Neitsch J. The truth below the surface: Towards quantifying and understanding the evaluation of German and Danish hate speech with EEG biosignals. J. of Speech Sci. [Internet]. 2022 Nov. 14 [cited 2024 Jul. 24];11(00):e022004. Available from: https://econtents.bc.unicamp.br/inpec/index.php/joss/article/view/16153

Funding data

Abstract

The recipient is a stimulus-external factor that has so far hardly been investigated in hate-speech research. However, addressing this factor is essential to understand how and why hate speech unfolds its negative effects and which characteristics of the recipient influence these effects. The present study focuses on the recipient. Building on previous findings from explicit ratings and initial successful replications of such ratings through biosignals, we are conducting the first large-scale, systematic, and cross-linguistic biosignal study on hate speech based on two EEG measures: the beta-alpha ratio associated with arousal and the frontal alpha asymmetry associated with valence. A total of 50 Danish and German participants took part and were presented with spoken and written hate-speech stimuli, derived from authentic hate-speech posts on Twitter. Results show that Danes reacted more sensitively than Germans to hate speech containing figurative language (swear words), while Germans reacted more sensitively to hate speech with Holocaust references than Danes. In addition, teachers and lawyers showed less negative reactions to hate speech than church employees, students, and pensioners. The effect of the presentation medium depended on the respective hate speech type. In particular, speaking out hate speech based on irony and indirectness attenuated its effects on recipients to such an extent that it is questionable whether the stimuli were still perceived as instances of hate speech at all. We discuss the results in terms of key tasks of future studies and practical implication for the punishment and management of hate speech on social media.

https://doi.org/10.20396/joss.v11i00.16153
PDF

References

Asif A, Majid M, Anwar SM. Human stress classification using EEG signals in response to music tracks. Computers in Biology and Medicine. 2019; 107: 182-196.

Balcerzak B, Jaworski W. Application of linguistic cues in the analysis of language of hate groups. Computer Science. 2015; 16.

Baumgarten N, Bick E, Geyer K, Iversen DA, Kleene A, Lindø AV, ... Petersen EN. Towards balance and boundaries in public discourse: expressing and perceiving online hate speech (XPEROHS). International Journal of Language and Communication. 2019; 50: 87-108.

Beer J, Beer J, Markley RP, Camp CJ. Age and living conditions as related to perceptions of ambiguous figures. Psychol. Rep. 1989; 64: 1027–1033.

Bialystok E, Shapero D. Ambiguous benefits: The effect of bilingualism on reversing ambiguous figures. Developmental Science. 2005; 8: 595-604.

Bick E. An Annotated Social Media Corpus for German. Proc. 12th International Conference on Language Resources and Evaluation, Marseille, France. 2020: 6127-6135.

Bick E, Geyer K, Kleene A. „Die ách so friedlichen Muslime “: Eine korpusbasierte Untersuchung von Formulierungsmustern fremdenfeindlicher Aussagen in Sozialen Medien. In Wachs S, Koch-Priewe B, Zick, A, editors. Hate Speech-Multidisziplinäre Analysen und Handlungsoptionen. Wiesbaden: Springer; 2021. pp. 81-103.

Bregman, AS. Auditory scene analysis: The perceptual organization of sound. Cambridge: MIT press; 1994.

Calderón FH., Balani N, Taylor J, Peignon M, Huang YH, Chen YS. Linguistic Patterns for Code Word Resilient Hate Speech Identification. Sensors. 2021; 21: 7859.

Cao T, Wang L, Sun Z, Engel SA, & He S.. The independent and shared mechanisms of intrinsic brain dynamics: Insights from bistable perception. Frontiers in Psychology. 2018; 9: 589.

Carroll EA., Latulipe C, Fung R, Terry M. Creativity factor evaluation: towards a standardized survey metric for creativity support. Proceedings of the seventh ACM conference on Creativity and cognition. 2009: 127-136.

Davidson T, Warmsley D, Macy M, Weber I. Automated hate speech detection and the problem of offensive language. Proc. 11th International AAAI Conference on Web and Social Media ICWSM '17. 2017: 512-515.

D’Errico F, Signorello R, Demolin D, Poggi I. The Perception of Charisma from Voice: A Cross-Cultural Study. Proc. Humaine Association Conference on Affective Computing and Intelligent Interaction. 2013: 552-557.

Fodor, JD. Psycholinguistics Cannot Escape Prosody. Proc. 1st International Conference on Speech Prosody, Aix-en-Provence, France. 2002: 83–88.

Fortuna P, Nunes S. A survey on automatic detection of hate speech in text. ACM Computing Surveys (CSUR). 2018; 51: 1-30.

Gale AG, Findlay JM. Eye movement patterns in viewing ambiguous figures. Eye movements and psychological functions: International views. 1983: 145-168.

Gambäck B, Sikdar UK. Using convolutional neural networks to classify hate-speech. Proc. 1st Workshop on Abusive Language Online. 2017: 85-90.

García-Acosta A., Riva-Rodríguez JDL, Sánchez-Leal J, Reyes-Martínez RM. Neuroergonomic Stress Assessment with Two Different Methodologies in a Manual Repetitive Task-Product Assembly. Computational Intelligence and Neuroscience. 2021.

Garcia-Moreno FM, Bermudez-Edo M, Garrido JL, Rodríguez-Fórtiz MJ. Reducing response time in motor imagery using a headband and deep learning. Sensors. 2020; 20: 6730.

Gentile DA, Woodhouse J, Lynch P, Maier J, McJunkin T. Reliability and validity of the Global Pain Scale with chronic pain sufferers. Pain Physician. 2011; 14: 61-70.

Geyer K. Entmenschlichende Metaphern in ethnotroper („fremdenfeindlicher“) Hatespeech in sozialen Medien. In Bülow L, Marx K, Meyer-Vieracker S, Mroczynski, R, editors. Digitale Pragmatik. Heidelberg: J. B. Metzler; 2021.

Geyer K, Bick E, Kleene A. “I am not a racist, but …”. A Corpus-Based Analysis of Xenophobic Hate Speech Constructions in Danish and German Social Media Discourse. In Knoblock N, editor. Grammar of Hate: Morphosyntactic Features of Hateful, Aggressive, and Dehumanizing Discourse. Cambridge: Cambridge University Press; 2021.

Geyer K. Die ‚Grammatik‘ der Hassrede – am Beispiel des Dänischen. In Strässler J. editor. Sprache(n) für Europa. Mehrsprachigkeit als Chance. Frankfurt: Peter Lang; 2019. pp. 195-207.

Goldstein, EB. Blackwell handbook of sensation and perception. John Wiley & Sons; 2008.

Handel S. Listening: an Introduction to the Perception of Auditory Events. Cambridge: MIT Press; 1989.

Herman K, Ciechanowski L, Przegalińska A. Emotional well-being in urban wilderness: Assessing states of calmness and alertness in informal green spaces (IGSs) with muse—Portable EEG headband. Sustainability. 2021; 13: 2212.

Hrdina M. Identity, activism and hatred: Hate speech against migrants on Facebook in the Czech Republic in 2015. Naše společnost. 2016; 14: 38–47.

Jaki S, De Smedt T. Right-wing German hate speech on Twitter: Analysis and automatic detection. arXiv preprint arXiv:1910.07518. 2019.

Klem GH, Lüders HO, Jasper HH, Elger C. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalography and Clinical Neurophysiology, Supplement. 1999; 52: 3–6.

Klintman H. Original thinking and ambiguous figure reversal rates. Bulletin of the Psychonomic Society. 1984; 22: 129-131.

LaRocco J, Le Minh D, Paeng D-G. A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection. Frontiers in Neuroinformatics. 2020; 14: 1-42.

Laukkonen RE, Tangen JM. Can observing a Necker cube make you more insightful? Consciousness and Cognition. 2017; 48: 198-211

Long GM, Toppino, TC. Multiple representations of the same reversible figure: Implications for cognitive decisional interpretations. Perception. 1981; 10: 231-234.

Levisen C. Dark, but Danish: Ethnopragmatic perspectives on black humor. Intercultural Pragmatics. 2018; 15: 515-531.

Malmasi S, Zampieri M. Detecting hate speech in social media. arXiv preprint arXiv:1712.06427. 2017.

MacAvaney S, Yao HR, Yang E, Russell K, Goharian N, Frieder O. Hate speech detection: Challenges and solutions. PloS one. 2019; 14: e0221152.

Martins R, Gomes M, Almeida JJ, Novais P, Henriques P. Hate speech classification in social media using emotional analysis. Proc. 7th Brazilian Conference on Intelligent Systems (BRACIS), IEEE. 2018: 61-66.

Neitsch J, Niebuhr O. Assessing hate-speech perception through bio-signal measurements: A pilot study. Proc. Biosignale 2020, Kiel, Germany, 2020: 66-67.

Neitsch J, Niebuhr O, Kleene A. What if hate speech really was speech? Towards explaining hate speech in a cross-modal approach. In Wachs S, Koch-Priewe B, Zick, A, editors. Hate Speech-Multidisziplinäre Analysen und Handlungsoptionen. Wiesbaden: Springer; 2021. pp. 105-135.

Neitsch J, Niebuhr O. Types of hate speech: How speakers of Danish rate spoken vs. written hate speech. Proc. 4th International Conference of Phonetics and Phonology in Europe, Barcelona, Spain. 2021: 1-2.

Nielsen PA. Choice of Law for Defamation, Privacy Rights and Freedom of Speech. Oslo Law Review. 2019; 6: 32-42.

Papcunová J, Martončik M, Fedáková D, Kentoš M, Bozogáňová M, Srba I, ... Adamkovič M. Hate speech operationalization: a preliminary examination of hate speech indicators and their structure. Complex & Intelligent Systems. 2021: 1-16.

Peters MA. Limiting the capacity for hate: Hate speech, hate groups and the philosophy of hate. Educational Philosophy and Theory. 2020: 1-6.

Richer R, Zhao N, Amores J, Eskofier BM, Paradiso JA. Real-time mental state recognition using a wearable EEG. Proc. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Honolulu, USA. 2018: 5495-5498.

Roberts R, Woodman T. Personality and performance: Moving beyond the Big 5. Current Opinion In Psychology. 2017; 16: 104-108.

Rodríguez-Martínez GA, Castillo-Parra H. Bistable perception: neural bases and usefulness in psychological research. International Journal of Psychological Research. 2018; 11: 63-76.

Ruwandika NDT, Weerasinghe AR. Identification of hate speech in social media. Proc. 18th International Conference on Advances in ICT for Emerging Regions (ICTer), IEEE. 2018: 273-278.

Shechter S, Hillman P, Hochstein S, Shapley RM. Gender differences in apparent motion perception. Perception. 1991; 20: 307–314.

Waseem Z, Hovy D. Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter. Proc. NAACL Student Res. Work. 2016: 88-93.

Zhang X, Bachmann P, Schilling TM, Naumann E, Schächinger H, Larra, MF. Emotional stress regulation: The role of relative frontal alpha asymmetry in shaping the stress response. Biological psychology. 2018; 138: 231-239.

Zhao G, Zhang Y, Ge Y. Frontal EEG asymmetry and middle line power difference in discrete emotions. Frontiers in behavioral neuroscience. 2018; 12: 225.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright (c) 2022 Oliver Niebuhr, Jana Neitsch

Downloads

Download data is not yet available.