Last month, I gave a talk 🗣️ at the 22×20 Planning Summit at the Brown Institute for Media Innovation at the Columbia Journalism School. The hall packed with media executives and journalists, mostly in their 30s and 40s, was initially full of grins 😂 but quickly turned thoughtful 🤔 as I walked them through my work in emoji data science.
I impressed upon them that while emojis might seem fun and trivial, they are at their core vessels for conveying human emotion. Anywhere we have a topic that people feel strongly about, we’re also likely to find an array of emojis that are used to accentuate and complement those feelings.
For example, this tweet from Election Night last year is my favorite response to people who think emojis are silly:
Consider how effectively and emotionally, in just 21 words and one emoji, the author captures the disappointment and malaise that so many of us experienced on Election Night. This is why emojis are important and this is why we study them.
Over the past few days, #MeToo has emerged as a viral social media trend used by women to express solidarity in the face of a culture of sexual harassment and assault. In the 24 hours after actress Alyssa Milano first tweeted about it last Sunday afternoon – piggybacking on a campaign started by activist Tarana Burke in 2007 – over 12 million people have posted on social media with the hashtag #MeToo.
We were curious about the emojis people were using when talking about #MeToo so we downloaded 28,629 English-language tweets from October 16 using the Twitter Search API. What did we find?
The top three emojis used with #MeToo are the ❤️ red heart, the 💔 broken heart, and the 😔 pensive face – conveying an emoji emotional signature of love, heartbreak, and disappointment. The 💜 purple heart and 💕 two hearts emojis also make an appearance in the top ten, along with the ✊ raised fist 💪 flexed biceps as shows of solidarity.
Only 5.2% of tweets with #MeToo include emojis, a much smaller percentage than we typically observe with most pop culture hashtags (for example, on a typical Wednesday, as many as 41% tweets with the hashtag #wcw included emojis). The proportion is, however, in the same 5-6% range we observed in our analysis of protest hashtags in February.
Here are the top 20 emojis of #MeToo:
|Rank||Emoji||Emoji Name||Frequency Per 1,000 Tweets|
|6||👇||backhand index pointing down||1.7|
|11||😍||smiling face with heart-eyes||1.3|
|20||😥||disappointed but relieved face||0.7|
We find that 8 of the top 20 emojis of #MeToo are hearts, 7 are faces (1 positive and 6 negative) and 5 are hand gestures (4 positive and 1 neutral). Here is another way to to visualize these top 20 emojis, grouped by emoji type:
What about skin tone distributions? Last year, Andrew McGill published the first quantitative analysis of skin tone emoji usage in The Atlantic in a piece entitled “Is It Okay to Use White Emoji?”. His main finding was that even though white Twitter users outnumber black Twitter users four-to-one, usage of the lightest skin emojis was far lower than one might expect, perhaps due to shame among white people or a desire not to be associated with white power.
The #MeToo movement too, despite its mass adoption, has faced some tension on the issue of race. Writing in Ebony, journalist Zahara Hill pointed out that the hashtag had originated with a black woman ten years ago. “A Black Woman Created the “Me Too” Campaign Against Sexual Assault 10 Years Ago…Yet, in the early conversations that spurred the “Me Too” movement, there was a sense it wasn’t for us,” she wrote.
Thus, we were justifiably curious about the distribution of skin tone emojis in tweets mentioning #MeToo. Using the linguist Kate Lyons’ updated emoji dictionary, we looked at the top 6 emojis in our dataset with the highest frequency of skin tone usage. Here’s what we found:
The most common skin tone for these emojis – which all represent gestures – is always either Color 1 or Color 2. (Note that in the table above, we only look at emojis that use a skin tone modifier. The percent of usage for a given emoji that includes a skin tone modifier ranges from 34% for 👇 to 86% for 👊.)
We also find a gradation of emojis based on mean skin tone, with ✊ being the darkest, with a mean skin tone of 2.8, and 🖕 being the lightest, with a mean skin tone of 1.6. (Our numbers are in the same overall range as Andrew Sullivan’s analysis which finds a mean skin tone across all emojis of 2.4).
These are preliminary results, and likely are only meaningful if we compare skin tone emoji usage between multiple hashtags, but they hold promise for better understanding the nuances of our communication about race using emojis.
Enjoyed this analysis? Download the raw data for yourself at GitHub, check out our tutorial on emoji data science in R, and subscribe to our newsletter to keep up with the latest in emoji analysis.
By Hamdan Azhar