Characterizing the Social Ties between Black and Tech Communities on Twitter

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Abstract

The slow increasing rate of representation of women and other minorities, particularly in Information Technology (IT) companies, suggests that the current recruiting strategies for attracting underrepresented minorities (URMs) may not be effective. While much can be done to improve hiring strategies, little attention has been paid to how job seekers' perceptions (positive or otherwise) of a company may affect its attractiveness. For instance, newer generations of professionals are more likely to avoid companies that are not committed to diversity causes. Studies have in fact shown that job seekers increasingly rely on social media to inform themselves about targeted companies. In this paper, we investigate the "social-mediascape"of Black Tech communities and IT companies, namely, the spaces of interactions and communications and their influences on individuals' perceptions of particular companies. To this end, we look into the Twitter Black and Tech communities in Brazil and in the United States. We rely on "Twitter lists"that are curated by the users of the platform and effective in capturing topical homophily. A research challenge in itself, we provide the first large-scale compositions of Black Tech communities and their connection to IT companies based on followership data on Twitter. After analyzing these compositions, we can then create perceptual maps between communities and IT companies. Our results suggest that there is a stronger correlation between Black activism and technology in the US context. For the Brazilian context, we found a stronger correlation between the Black Tech and general Software Developer users communities suggesting that both racial activism and technology are important topics to attract the Brazilian Black Tech community's interests.

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APA

Vasconcelos, M., Rocha, P., Nogima, J., & Paula, R. (2022). Characterizing the Social Ties between Black and Tech Communities on Twitter. In ACM International Conference Proceeding Series (pp. 75–86). Association for Computing Machinery. https://doi.org/10.1145/3501247.3531544

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