TY - GEN
T1 - Effect of Online Weight Loss Advertising in Young Women with Body Dissatisfaction
T2 - 22nd International Conference on Human-Computer Interaction, HCII 2020
AU - Almenara, Carlos A.
AU - Aimé, Annie
AU - Maïano, Christophe
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - The weight loss industry is projected to reach USD$ 278.95 billion worldwide by 2023. Weight loss companies devote a large part of their budget for advertising their products. Unfortunately, as revealed by the Federal Trade Commission (FTC), there are many deceptive ads. The effect of weight loss advertising on consumer’s diet and eating behavior is so large that it has been proposed a causal relationship between advertising and diet. Adolescents, women with appearance concerns, and obese people, are the most vulnerable consumers for this kind of advertising. Within the Internet, most weight loss products are advertised under algorithmic rules. This algorithmic regulation refers to the online advertising being established by a series of rules (i.e., algorithms). These algorithms collect information about our online identity and behavior (e.g., sociodemographic characteristics, online searches we do, online content we download, “liked” content, etc.), to personalize the content displayed while we browse the Internet. Because of it, this algorithmic regulation has been described as a “filter bubble”, because most content we see on the Internet is reflecting our idiosyncratic interests, desires, and needs. Following this paradigm, this study presents a research protocol to experimentally examine the effect of online weight loss advertising in the attention (using eye-tracking) and physiological response (using facial electromyography) of women with different levels of body dissatisfaction. The protocol describes the methodology for: participants’ recruitment; collecting weight loss ads; and the experimental study, which includes the stimuli (ads) and the responses (eye fixations and facial muscles activity).
AB - The weight loss industry is projected to reach USD$ 278.95 billion worldwide by 2023. Weight loss companies devote a large part of their budget for advertising their products. Unfortunately, as revealed by the Federal Trade Commission (FTC), there are many deceptive ads. The effect of weight loss advertising on consumer’s diet and eating behavior is so large that it has been proposed a causal relationship between advertising and diet. Adolescents, women with appearance concerns, and obese people, are the most vulnerable consumers for this kind of advertising. Within the Internet, most weight loss products are advertised under algorithmic rules. This algorithmic regulation refers to the online advertising being established by a series of rules (i.e., algorithms). These algorithms collect information about our online identity and behavior (e.g., sociodemographic characteristics, online searches we do, online content we download, “liked” content, etc.), to personalize the content displayed while we browse the Internet. Because of it, this algorithmic regulation has been described as a “filter bubble”, because most content we see on the Internet is reflecting our idiosyncratic interests, desires, and needs. Following this paradigm, this study presents a research protocol to experimentally examine the effect of online weight loss advertising in the attention (using eye-tracking) and physiological response (using facial electromyography) of women with different levels of body dissatisfaction. The protocol describes the methodology for: participants’ recruitment; collecting weight loss ads; and the experimental study, which includes the stimuli (ads) and the responses (eye fixations and facial muscles activity).
KW - Algorithmic regulation
KW - Body dissatisfaction
KW - Eye-tracking
KW - Facial electromyography
KW - Internet
KW - Online advertising
KW - Weight loss
UR - https://www.scopus.com/pages/publications/85088740676
U2 - 10.1007/978-3-030-50732-9_19
DO - 10.1007/978-3-030-50732-9_19
M3 - Contribución a la conferencia
AN - SCOPUS:85088740676
SN - 9783030507312
T3 - Communications in Computer and Information Science
SP - 139
EP - 148
BT - HCI International 2020 - Posters - 22nd International Conference, HCII 2020, Proceedings
A2 - Stephanidis, Constantine
A2 - Antona, Margherita
PB - Springer
Y2 - 19 July 2020 through 24 July 2020
ER -