Twitter data offers a unique perspective on American Indian/Alaska Native youth
Around Him, D. Li, W., Gross, E., Warren, J., DeMand, A., Garcia-Baza, I., Habteselasse, (2020). Twitter Analysis Can Help Practitioners, Policymakers, and Researchers Better Understand Topics Relevant to American Indian/Alaska Native Youth. Child Trends. Retrieved November 17, 2020, from https://www.childtrends.org/publications/twitter-analysis-practitioners-policymakers-researchers-understand-topics-american-indian-alaska-native-youth
Summarized by Ariel Ervin
Notes of Interests:
- Although children and youth under age 18 constitute nearly one-third of the American Indian/Alaska Native (AI/AN) population in the United States, data on their needs and interests are still limited.
- Big data, particularly social media data, present an opportunity to learn about population-level trends worthy of focus in research, policy, and practice.
- This brief provides implications and recommendations for researchers, practitioners, and stakeholders who work with this subgroup, based on Twitter data.
- “Activism” (35%), “identity, nationality, or nation” (19%), and “politics” (11%) were salient themes that were identified from hashtags.
- Although the authors only selected hashtags specifically geared towards AI/AN for the initial dataset, 69% of the hashtags in the final analysis were not specific to this subpopulation: e.g. #cdnpoli (Canadian politics), #education, and #blacklivesmatter.
- The findings implicate that researchers must understand that Indigenous identities, nations, and nationalities are intertwined and nuanced and when using social media to address AI/AN topics, stakeholders should be aware of intersectional identities and movements.
Introduction (Reprinted from the Introduction)
In this brief we share key implications for practitioners and policy stakeholders who work with AI/AN communities or on issues relevant to these communities. We also offer recommendations for interpreting these Twitter data that may be useful to researchers and others who seek to use similar social media data in their work. Exploring this data visualization may provide additional insight to practitioners, policymakers, and researchers interested in focusing in more depth on a specific topic or issue.
Implications (Reprinted from the Conclusions)
This analysis offers insights into the varied and dynamic conversations that happen on Twitter related to topics relevant to AI/AN children and youth. Researchers need new tools for analyzing discussions of topics important to populations that are often left out of social science research and policy. Social media analyses present opportunities to dig deeper into these conversations as they play out over time, but researchers must remain aware of how to wield these analyses in a robust and ethical manner.
When studying social media conversations relevant to AI/AN populations, researchers must consider the history and fluidity of geographic borders, the social media platform they use for analysis (and how its particularities will affect the data), the co-opting of identities and online cultural appropriation that can muddy results, and the legacies of abusive data collection and analysis. Navigating these challenges allows for opportunities to create more inclusive data science methods.
Researchers are likely to find that, when analyzing the unstructured data of online conversations, many topics arise that are not specific to AI/AN populations; this is because conversations, like identities, are intersectional. Indeed, the phrase “topics relevant to AI/AN children and youth” may be a misnomer, because AI/AN individuals carry many identities, and because AI/AN communities interact and intersect with other communities and the topics relevant to them. In addition, Twitter is often used for collaboration and coalition-building across political movements and trends. Researchers should embrace this complexity, although it may add new challenges even while opening doors.
Finally, one major benefit of social media analysis is that it allows us to not only produce snapshots of online conversations, but also to track conversations over time. To engage with the needs and interests of AI/AN communities, policymakers and practitioners must remember that online conversations are not static. Understanding how these conversations evolve is another part of seeing AI/AN communities in a complex light as needs shift, new movements take hold, and trends wax and wane.
To access this brief, click here.