ToTS & TiP

Identifying Stereotypes in the Online Perception of Physical Attractiveness Stereotyping can be viewed as oversimplified ideas about social groups. They can be positive, neutral or negative. The main goal of our work is to identify stereotypes for female physical attractiveness in images available in the Web. We look at the search engines as possible sources of stereotypes. We conducted experiments on Google and Bing by querying the search engines for beautiful and ugly women. We then collect images and extract information of faces. We propose a methodology and apply it to analyze photos gathered from search engines to understand how race and age manifest in the observed stereotypes and how they vary according to countries and regions. Our findings demonstrate the existence of stereotypes for female physical attractiveness, in particular negative stereotypes about black women and positive stereotypes about white women in terms of beauty. In a following study, we examine the local and global impact of the internet on the formation of female physical attractiveness stereotypes in search engine results. By investigating datasets of images collected from two major search engines in 42 countries, we identify a significant fraction of replicated images. We find that common images are clustered around countries with the same language. We also show that existence of common images among countries is practically eliminated when the queries are limited to local sites. In summary, we show evidence that results from search engines are biased towards the language used to query the system, which leads to certain attractiveness stereotypes that are often quite different from the majority of the female population of the country. Speaker: Gabriel Magno is a PhD student of Computer Science at Federal University of Minas Gerais (UFMG), Brazil. He is interested in studying social interactions, language patterns and privacy issues in social media and online social networks. He received an MS and a BS in Computer Science from UFMG, Brazil. He was a research assistant at the Social Computing group of the Qatar Computing Research Institute.