Viviane Ito


Hi! I am Viviane! You can also call me Vivi, Vivian or just Vi.

I am Brazilian, but my family is originally from Japan (although my grandma was born in Korea, during the Japanese occupation). After spending more than 10 years working in advertising, I am making a career shift to academia.

Currently, I am a second-year Ph.D. student in Information Science at the University of North Carolina at Chapel Hill and a Graduate Research Assistant at CITAP.  My main research interest in on information inequality, particularly how platforms and algorithms work to improve or perpetuate gender bias and other types of problematic information. To analyze these objects, I use natural language processing methods that I have learned in my BA and MA in Linguistics, both at the University of Sao Paulo, Brazil.

I am also a yogi, barista, and worked as a volunteer in a dog shelter in Thailand.

I love talking about all those topics in the paragraphs above, so please, feel free to contact me about any of them!

itovivi [AT] unc [DOT] edu



Discurso Y Dolor (jul 2021- jan 2022)

In this project, funded by FONDECYT, I was supervised by Prof. Mariana Pascual from the Pontificia Universidad Católica de Chile.

My goal was to study a corpus of interviews with patients diagnosed with endometriosis. The disease causes chronic pain, and takes in average 7 to 10 years to diagnose. This delay is often due to failures in patient-doctor communication.

Questions that were the basis of the project:

Gender Bias In The Careers Of Olympic Athletes (jan 2021- mar 2022)

I was a Research Assistant in this project during my BA in Linguistics at USP, supervised by Prof. Marcos Lopes. It presented two central objectives, anchored in the hypothesis that the sports careers of professional athletes show mishaps directly related to gender. The main objective was to understand whether themes such as pain, career transition, and motherhood are relevant in differentiating the trajectory of female athletes.

To enable this study, computational analyses were made to quantitatively evaluate textual data, since the corpus of the work consists of a set of interviews. This methodology should allow the extraction of the most critical topics in the differentiation of interviews of men and women, besides generating metrics for visualizing such differences.

Curriculum Vitae