Towards Identifying Concepts in Persuasive Social Networks: Case Study TikTok

Bochra Larbi, Nadia Elouali, Nadir Mahammed

2023

Abstract

Persuasive technology assists users in decision making by influencing their behaviors. It has seen major evolution in recent years, due to the rapid rate at which persuasive design has been integrated in a variety of technologies. This substantial involvement in several fields increased the influence and impact of persuasive technology. Since persuasion delivers an important amount of services, it is recognized as one of the key factors deployed by the human-computer interaction community in the design and development phases; yet, persuasive design has been accused of having problematic aspects. Social networking sites are no exception, they rely heavily on persuasion in their interfaces. Which has led to the emergence of new, diverse concepts exploited by these sites, with the primary goal of maximizing users’ time spent in order to collect data and gain money from ads. Our research idea is to identify these concepts deployed by social networking sites, examine their degree of persuasion, then propose a set of new, moderate ones to preserve as much as possible the user’s autonomy. In this paper, we present the first step of our research that consists of identifying the concepts deployed by TikTok which is the fastest growing social media in 2022.

Paper Citation

in Harvard Style

Larbi B., Elouali N. and Mahammed N. (2023). Towards Identifying Concepts in Persuasive Social Networks: Case Study TikTok. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 2: HUCAPP; ISBN 978-989-758-634-7, SciTePress, pages 236-242. DOI: 10.5220/0011726100003417

in Bibtex Style

@conference{hucapp23,
author={Bochra Larbi and Nadia Elouali and Nadir Mahammed},
title={Towards Identifying Concepts in Persuasive Social Networks: Case Study TikTok},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 2: HUCAPP},
year={2023},
pages={236-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011726100003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 2: HUCAPP
TI - Towards Identifying Concepts in Persuasive Social Networks: Case Study TikTok
SN - 978-989-758-634-7
AU - Larbi B.
AU - Elouali N.
AU - Mahammed N.
PY - 2023
SP - 236
EP - 242
DO - 10.5220/0011726100003417
PB - SciTePress