Allyship and Anti-Racism in Online Verbal Art

     Our project was conducted through a series of processes:

 

1) Data collection: 304 verbal art items were collected from TikTok and YouTube that focused on the topic of anti-racism. Most items were posted from March 2020 onwards, except for a few spoken word poems posted in 2018 and 2019. Verbal art videos were found by using the search tool including keywords and hashtags such as "BLM poetry, Stop Asian hate, racism poetry, anti-racism song, Black Lives Matter song, anti-racism poetry, Indigenous poetry, allyship song, Black Lives Matter, #blm, #racism, #poetry, #song, #rap."​

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     Some videos were suggested in Youtube's "Suggested Videos" section after watching a video found via the search tool, while others appeared on our TikTok “For You page.” The content of these items contain a wide range of topics, including but not limited to anti-Black racism, anti-Asian racism, and Indigenous rights, along with movements such as Black Lives Matter and Every Child Matters. However, the majority of the items focus on anti-Black racism. Content creators used a variety of mediums, including raps, songs, parodies, poems and skits to express their message to a public online audience. Videos were created by people from various demographics, and they ranged from very popular videos with more than 10,000 views, to those with only a few views.  

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     Videos collected for the project were created by users form various areas of the world, including the United States of America, Canada, Australia, and the United Kingdom. However, the majority of videos contain content created by people from the USA, and contain content related to anti-racism in the USA. As a result, there is American bias found in our selection of videos.

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2) Transcript Creation: ​Once these items were collected, transcripts were created to accompany each video recording of the verbal art content. USRI students working on the project in previous years, along with a team of volunteers and Work Study students, contributed to this aspect of the project by finding items and creating video transcripts. All videos and video transcripts were uploaded and organized using the qualitative data analysis platform NVivo.  

 

3) Preliminary Coding and Case Classifications: After this process was completed, we proceeded to do basic coding for each item using NVivo, where we categorized transcripts based on their genre, topic, and type of transcript. Cases were also created for each artist, marked by case attributes such race, gender, language spoken, type of content, and level of professionalism.

 

4) Thematic Coding: As a team we collaborated to create codes for common themes that we observed, along with definitions and criteria to use while coding all items for each theme. The total number of items were evenly split between each team member, and we each coded the items within our respective sections for each theme. Since allyship was the focus of this research project, we collaborated on coding content with this theme and the sub-themes of allyship by both coding ten items at a time, and then comparing with one another to ensure we were both applying the codes the same way to ensure reliability and reduce variability.  .

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5) Coding Analysis Discussion: After data collection, transcription and coding were completed, we sorted through our dataset and discussed reoccurring themes related to the topic of allyship, including items with ambiguous themes or that contain multiple themes. This helped us to narrow down our research questions and focus on specific aspects for the purpose of this project.

 

6) Recording and Writing Analysis Results: We remained in close communication with each other to divide tasks and carry out the analysis process to answer our research questions. We engaged in a final round of coding analysis by examining emerging themes, writing down notes in a shared document and making memos in NVivo, along with relevant examples from online verbal art content collected. We used all of this information to guide our writing and answer our individual research questions.