ISSN: 2161-0711

Medicina comunitaria y educación para la salud

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Abstracto

The Main Themes and Experiences Shared with the Hashtag #BlackintheIvory: A Qualitative Analysis

Mopileola Tomi Adewumi, Paul Delgado, Marvin Carr, Emily Sowah, Matt Vassar

Background: The movement #BlackintheIvory gave Black academics an opportunity to connect through social media, sharing common experiences while pursuing higher education. Through analyzing Twitter posts, using the hashtag #BlackintheIvory, this study investigates the main themes identified among Black scholars in academia and their shared experiences with teaching, mentoring, collegiality, identity, service, and racism.

Method: Using the Twitter API, we isolated publicly available tweets, which can include text, images, and links to websites, posted with #BlackintheIvory on the Twitter website (www.twitter.com) from the inception of #BlackintheIvory in June 2020 to the end of December 2020. To evaluate the tweets, we categorized tweets inductively. Based on the content of posts, we identified 6 themes: Teaching, Mentoring, Collegiality, Identity, Service, and Racism.

Result: Our search yielded a total of 12,538 original posts, including tweets between inception in June 2020 to December 2020 from profiles made public (excluding modified and duplicate tweets). We selected and analyzed the top retweeted 2500 tweets, which is 20% (2500/12538) of the total number of downloaded tweets. The greatest percentage of posts was Teaching (881; 35%), Service (441; 18%) and Racism (414; 17%). The remaining tweets were categorized as Collegiality (388; 15%), Identity (210; 8%), and Mentoring (166; 7%) of the total number of tweets from June-December 2020.

Conclusion: The experiences, perspectives, and narratives among the Black diaspora within #BlackintheIvory are not uniform. The commonality exists within the structural systemic racism which impacts Black academics within the ivory tower; this study is a resounding wake up call for action.

Descargo de responsabilidad: este resumen se tradujo utilizando herramientas de inteligencia artificial y aún no ha sido revisado ni verificado.