The Unconscious Response of Multimedia Content Consumers to Emotionally Significant Visual Symbols: Experimental Study and Oculometry Dataset

EasyChair Preprint 4137

Abstract

The publication discusses the problem of forming a dataset that can be used as a training sample for a neural network classifier capable of detection of destructive multimedia content. Special attention is paid to the procedure of experimental re-search, detection of anomalies and obtaining categorical estimates. The obtained dataset includes various emotionally significant visual stimuli and oculometric da-ta of the subjects and makes it possible to use quantitative and qualitative criteria for assigning visual content to one of the classes: «toxic», «indifferent», «sanogenic». The dataset is free for non-commercial use and is available to researchers at Kaggle.com

Keyphrases: anomaly detection, destructive multimedia content, neural network classifier, training sample

@booklet{EasyChair:4137,
  author    = {Konstantin Gnidko and Andrey Dudkin and Oleg Ivanov and Vladimir Lokhvitsky and Sergey Pilkevich and Timur Sabirov},
  title     = {The Unconscious Response of Multimedia Content Consumers to Emotionally Significant Visual Symbols: Experimental Study and Oculometry Dataset},
  howpublished = {EasyChair Preprint 4137},
  year      = {EasyChair, 2020}}