On Attention of Forensic Experts and Non-Experts in the Perception and Comprehension of Multimodal Text

Autor: Mikhail Osadchiy, Aleksandra Gorbacheva, Alexandra Berlin Khenis
Rok vydání: 2022
Zdroj: Vestnik Volgogradskogo gosudarstvennogo universiteta. Serija 2. Jazykoznanije. :158-175
ISSN: 1998-9911
DOI: 10.15688/jvolsu2.2022.3.13
Popis: The article presents the results of experimental research into psychophysiological and psycholinguistic features of perception and understanding of multimodal texts with extremist content. The hypothesis verification was implemented by means of the analysis of the respondents' eye movement data, involving forensic linguists, practicing in anti-extremism cases, well-informed and not well-informed non-experts. Research methods were eye-tracking, quantitative data processing, structural-semantic analysis. The following statistically reliable data were obtained: experts and poorly informed respondents spent more time on the task and had some similarities in the parameters of oculomotor activity, in contrast to well-informed respondents, who quickly completed the task, avoiding detailed analysis of the stimulus; the respondents who answered "not sure", spent more time on the task, their viewing strategy was characterized by long frequent fixations in comparison to other groups; respondents who gave benchmark answers recognized the elements of the image with longer sparse fixations, within the least amount of time. The longest time of viewing, number and duration of fixations were revealed for the signs that have the largest number of connections with the surrounding components; one of the highest values of viewing time is recorded for incomprehensible signs. The results of the study demonstrate the psycholinguistic and psychophysiological features of perception and understanding multimodal texts in forensic linguists compared to professionals in other fields. Being applicable to fundamental research into information perception and processing, the results can also contribute to working out the methods of multimodal text forensic linguistic analysis.
Databáze: OpenAIRE