Social media is considered a democratic space in which people connect and interact independently of gender, race, or any other demographic factor.However, there are already indications that social media perpetuate ancient inequalities of world off line. In an article published by researchers from the Federal University of Minas Gerais in Brazil, it shows how users identified as men and whites tend to reach higher positions on Twitter, in terms of the number of followers and incorporation into user lists.
Identifying demographic inequalities and asymmetries in the online world is crucial for the development of measures that can promote equality and diversity in these platforms.Introduction of his article, researchers led by Johnnatan Messias cite recent works that show a gender gap in the production of content on Wikipedia as well as sign Racial discrimination when renting a home in Airbnb or a car in Uber.
But does gender and race affect online interactions on Twitter? It is the question to which these researchers want to answer and, for this, they have tracked a large-scale sample of active Twitter users, identifying the gender and race of about 1.6 million tweeters located in the United States. To do this, they have used the Face ++ software for facial recognition, capable of detecting the gender and race of identifiable faces in the user profile images.In total, collected 341,457,982 tweets published by 50,270,310 for three months until September 2016.
The findings of this team reinforce previous observations on the situation of inequality of Twitter users versus men and also identify gender and race biases when comparing the activity of White tweeters against blacks and Asians. In this way, the team led by Johnnatan Messias concludes that the "glass roofs" of the off-line world are also reflected in the virtual environment.
More information:
White, Man, and Highly Followed: Gender and Race Inequalities in Twitter.Johnnatan Messias, Pantelis Vikatos, Fabricio Benevenuto
Eduardo Graells-Garrido, Mounia Lalmas, and Filippo Menczer.2015.First Women, Second Sex: Gender Bias in Wikipedia.In Proceedings of the 26th ACM Conference on Hypertext&Social Media (HT'15) .New York, NY, USA, 165-174.
Benjamin Edelman, Michael Luca, and Dan Svirsky.2017.Racial discrimination in the sharing economy: Evidence from a field experiment. American Economic Journal: Applied Economics 9, 2 (2017), 1-22.
Image: Pixabay
Identifying demographic inequalities and asymmetries in the online world is crucial for the development of measures that can promote equality and diversity in these platforms.Introduction of his article, researchers led by Johnnatan Messias cite recent works that show a gender gap in the production of content on Wikipedia as well as sign Racial discrimination when renting a home in Airbnb or a car in Uber.
Gender and race on Twitter
But does gender and race affect online interactions on Twitter? It is the question to which these researchers want to answer and, for this, they have tracked a large-scale sample of active Twitter users, identifying the gender and race of about 1.6 million tweeters located in the United States. To do this, they have used the Face ++ software for facial recognition, capable of detecting the gender and race of identifiable faces in the user profile images.In total, collected 341,457,982 tweets published by 50,270,310 for three months until September 2016.
The findings of this team reinforce previous observations on the situation of inequality of Twitter users versus men and also identify gender and race biases when comparing the activity of White tweeters against blacks and Asians. In this way, the team led by Johnnatan Messias concludes that the "glass roofs" of the off-line world are also reflected in the virtual environment.
More information:
White, Man, and Highly Followed: Gender and Race Inequalities in Twitter.Johnnatan Messias, Pantelis Vikatos, Fabricio Benevenuto
Eduardo Graells-Garrido, Mounia Lalmas, and Filippo Menczer.2015.First Women, Second Sex: Gender Bias in Wikipedia.In Proceedings of the 26th ACM Conference on Hypertext&Social Media (HT'15) .New York, NY, USA, 165-174.
Benjamin Edelman, Michael Luca, and Dan Svirsky.2017.Racial discrimination in the sharing economy: Evidence from a field experiment. American Economic Journal: Applied Economics 9, 2 (2017), 1-22.
Image: Pixabay
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