UNDERSTANDING STEREOTYPE WITHIN TEXT: AN APPLICATION TO PERCEPTIONS OF COMPUTER SCIENTISTS
Abstract/Contents
- Abstract
- In a world where the technology sector is growing rapidly and computer scientists seem ubiquitous, it is important to take into account the perceptions of these computer scientists who are driving this technological advance forward. Prior literature has described the stereotypical computer scientist as highly intelligent, socially unaware, obsessed with technology, and masculine. This project aims to analyze these stereotypes against some experimental data. With over 500 participants taking part in a survey on Mechanical Turk that asks the participant to describe the stereotype or anti-stereotype of a computer scientist, enough data was collected to answer the questions of how consistent with the literature were the stereotypes presented in this experimental data and could a stereotype score be attributed to each of the words used? To assess whether or not these descriptions were consistent with prior literature, the first step was to calculate the word similarity using word embeddings of each word with lexicons that represented the stereotypes of competence and social (in)ability. The second step was to find where geometrically each word fell on an axes of competence and anti-competence/social and anti-social, before calculating the distance from the middle point as the final stereotype score. Overall, the analysis finds that stereotypes and anti-stereotypes present in experimental data are consistent with literature, and this paper makes a major contribution in providing a method to assign any word a competence or social stereotype score along the lines of stereotyping in computer science.
Description
| Type of resource | text |
|---|---|
| Date created | December 2019 |
Creators/Contributors
| Author | Vera, Ma Francesca Luisa C |
|---|
Subjects
| Subject | Symbolic Systems |
|---|---|
| Subject | Stereotype in Computer Science |
| Subject | Gender in Computer Science |
| Subject | Stereotype Text Analysis |
| Genre | Thesis |
Bibliographic information
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- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Collection
Master's Theses, Symbolic Systems Program, Stanford University
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- fcvera96@gmail.com
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