When it comes to media and the various social perceptions/mis-perceptions of various groups of people, the connection is undoubtable. Whether intentionally or subconsciously, journalists are responsible for shaping the public opinion regarding a topic. An analysis of words most frequently correlated with Asian-Americans narratives can enable other readers, researchers, and policymakers to build upon the work, and help combat AAPI related hate-crimes.
It is notable that racism and discrimination-related words were frequent in headlines associated with Asian-American stories, particularly during the COVID-19 pandemic, as shown in the word cloud visualizations below. It’s also quite telling about the nature of human curiosity and journalism; negative articles receive more views than positive ones.
On the contrary, positive associations with AAPI subjects were in relation to academic experiences and achievements; typically mentioning Ivy League College affiliations.
Some Key takeaways from this analysis by our summer researcher Ms. Minh Anh Phan include:
- Search and learn more from those who blazed the pathway before you.
- There are multiple ways to represent your dataset, so you have to play around, come with an open mind to explore what works for you. The majority of time on a data science project will be spent on preparing the data in the right format.There is also no ‘right’ answer, just supporting data which reflect the stories awaiting to be told.
- Ask yourself, “Does this make sense?” that’s the beauty of data, it doesn’t easily explain why or how, it simply reflects what is.
- Explore and have fun! The amount of data available is expansive…use it to tell the fuller story about people’s lived experiences.
Check out the fuller discussion on H.A.R.P’s Lets HARP About It livestream, and the information including the presentation slides, raw code can be accessed here.
The Summer research technical and summary by Ms. Minh Anh Phan can be found here
