Emojis have been called the world's fastest growing language. Yet remarkably little research has been done on differences in emoji usage between cultures. Previous analysis has usually focused on aggregate differences between countries based on data from third party keyboard apps. Here, we analyze emojis in nearly 35,000 tweets in nine languages about a common topic: the Islamic holy month of Ramadan, which began this past weekend. In doing so, we see broad commonalities across languages but also noteworthy and meaningful differences.
Over the past week, our Emojipedia article "The Resistance Will Be Emojified", has gone viral on three continents. Yesterday, Mashable dedicated their entire Snapchat story to covering the analysis. Here's a brief selection of some of our favorite clips!
An emoji data science tutorial in R as a complement to the Emojipedia article: "The resistance will be emojified ✊🏽"
Last week, election results from all states were finally certified. While most headlines focused on Hillary Clinton’s 2.8 million popular votes lead over Donald Trump, the results also debunked claims that had been circulating over the past few weeks.
Apple recently came under fire for proposing a change to the 🍑 peach emoji that made it look more fruit-like and less butt-like. “What’s happening to emojis represents the worst kind of gentrification of the internet,” charged Buzzfeed. Mashable was even more dramatic, exclaiming: “Apple just ruined texting.” While Apple soon retreated, the episode demonstrated the … Continue reading How we really use the peach emoji
The past week has seen a whirlwind of social media activity around the death of Fidel Castro, Thanksgiving, and Black Friday. We were curious about how people used emojis to discuss these topics so we looked at some data from Twitter. Check out the complete post on Emojipedia!
Could emoji data science have predicted the results of the election? Probably not, but emojis still provide a fascinating glimpse into the emotions of American voters. We used the Twitter API to collect nearly 2 million tweets on Election Day. What did we find? Lots of 🖕s, 🇺🇸s, and 👍, and more.