Gender Bias on Tinder: Transforming an Exploratory Qualitative Survey into Statistical Data for Contextualized Interpretation
Citation:
Gender Bias on Tinder: Transforming an Exploratory Qualitative Survey into Statistical Data for Contextualized Interpretation, Antonio Pedro Costa, Lua?s Paulo Reis, Francisle Neri de Souza, Antonio Moreira , Computer Supported Qualitative Research: Second International Symposium on Qualitative Research (ISQR 2017), Cham, Switzerland, Springer Nature, 2017, 225-236, Milena Ribeiro Lopes and Carl VogelAbstract:
Tinder is an online dating application that enables a human-human interaction. However, the ease of connection brings to light some concerns about possible harmful gender dynamics, which can enhance bias within technological developments and threaten women empowerment. This research aims to investigate whether the application meets women's expectations, whether there is gender bias and sexist behavior during the users' experiences and what is the relation between the findings to the graphical user interface. The research approaches to a mixed method design in order to achieve its goals.
Sponsor
Grant Number
Science Foundation Ireland (SFI)
13/RC/2106
Science Foundation Ireland (SFI)
12/CE/I2267
Author's Homepage:
http://people.tcd.ie/vogelDescription:
PUBLISHEDPart of the Advances in Intelligent Systems and Computing book series (AISC, volume 621)
Cham, Switzerland
Author: VOGEL, CARL
Sponsor:
Science Foundation Ireland (SFI)Science Foundation Ireland (SFI)
Other Titles:
Computer Supported Qualitative Research: Second International Symposium on Qualitative Research (ISQR 2017)Publisher:
Springer NatureType of material:
Book ChapterCollections
Availability:
Full text availableSubject (TCD):
Digital Humanities , Inclusive Society , Intelligent Content & Communications , Computational linguistics , GENDER , Social Media , Social media and social networkingDOI:
http://doi.org/10.1007/978-3-319-61121-1_20Metadata
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