#StopAsianHate Around The Globe

On March 16, 2021 a series of racially motivated murders happened at three spas in Atlanta, Georgia during which eight people, including six Asian women, were killed. This horrific event, occurring on the backdrop of rising anti-Asian sentiment in the United States during the COVID-19 pandemic, fueled a global backlash against such racism, encapsulated by the hashtag #StopAsianHate.

This data visualization uses data scraped from Twitter using the Twitter API and the tweepy Python library. Data was collected for all geo-locatable tweets with the hashtag "#StopAsianHate" that were posted over the course of the 24-hour period from March 18, 2021 at 4:00pm EST to the same time on March 19, 2021.

Because only a small fraction of tweets posted to Twitter have geo data associated with them (less than 1%), these 1,229 data points comprise only a small fraction of all #StopAsianHate tweets. The map below displays these.

We can see that, two days after the events of March 16, people around the globe (though concentrated in the US) continue to express their solidarity with the cause of #StopAsianHate.

The second map below expands on the first to additionally present the text content of tweets. Zoom in to view content for individual tweets around the world.

Next is a series of maps that show the progression of when these tweets were posted over the course of the 24-hour period.

You can notice (and interactively explore) how different regions of the world tweeted in different patterns and frequencies at different times according to location and local time zone, especially in the Asia-Pacific regions.

4pm-10pm EST

10pm-4am EST

4am-10am EST

10am-4pm EST

Finally, the below histogram shows the number of tweets over the course of the day, normalized to correspond to local time and with categories ordered to start at midnight. We can see that, true to intuition, most tweets are posted during waking hours between 9am and 10pm, with a slump in the early morning hours of between 2am and 5am.


Visualizing tweet data by geolocation can illuminate both patterns of sentiment surrounding influential events and insight into the daily rhythms of human awareness and activity. When activists rise, they do so in waves - waves influenced by, yet ultimately transcendent of, geographic boundaries.

Designed and developed by Dana Bullister and Dana Yao with help from Mapbox.com for ARTG6100 Information Design Studio 2: Dynamic Mapping and Models, Spring 2021, IDDV Program, Northeastern University