United States of #Happy
United States of #Happy
Whether you’re happy, sad, or angry, you might go to social media to post about it. We looked at Twitter, where there are over 320 million monthly users, to see if we could get an impression of how people feel in the United States and what parts of the country express the most emotion online. Let’s take a look to see what our analysis turns up as far as being happy, sad, or angry on Twitter.
Wearing Hashtags on Their Sleeves
First, we looked at where people were the happiest in the nation. Nebraska came out on top with the most tweets mentioning #happy, 99.1 percent more often than expected (based on Twitter usage in the state), followed closely by West Virginia and Michigan.
Interestingly, West Virginia was also the saddest state (89.1 percent more often than expected). What this means is that West Virginia residents had the most tweets mentioning #sad when compared to the total Twitter activity in the state. On the flip side, neighboring Kentucky was the least sad state (-77.1 percent).
When it came to being #angry, New Hampshire posted the most tweets including this hashtag (105.5%), followed by Maine and Minnesota. New Hampshire isn’t the most heavily populated state, but it seems its residents are prone to post about their anger on social media.
The most emotional state overall? Nebraska posted the most tweets mentioning a combination of #happy, #sad, and #angry (86% more often than expected).
Next, we discerned which cities sent out the most hashtagged emotions in tweets relative to what was expected of them. Residents in Madison, Wisconsin, won the #happy hashtag contest here, with a massive percentage of cheerful tweets compared to the usage of Twitter in their state (11,517 percent).
For #Angry, those in Albany, New York, were the most angry relative to the usage in their state (21,616 percent).
As far as #sad went, people in New York, New York, had the most tweets mentioning this hashtag by comparison to how Twitter was used in their state (2,069 percent).
A Little of This, a Little of That
We then checked to see how the ratio of #happy to #sad tweets shook out. Nationwide, the ratio was 4.4 #happy tweets for every #sad tweet. Some parts of the country deviated quite a bit from this average, though.
Kentucky, which we established was the least sad state according to how often residents included #sad in their tweets, had a ratio of 8.3 #happy tweets for every #sad tweet. Nebraska, the happiest state overall, came in second with 6.9 #happy mentions for every #sad tag, followed by Ohio (6.1), Michigan (6.0), and West Virginia (5.9).
When we broke it down by city, the story was a bit different. Chicago is a big city, of course, but its residents don’t seem to let the hustle and bustle get them down, as they tweeted #happy way more often than they did #sad (17.9 to 1). Other cities that were happier than sad were Powell, Ohio (13.9); Southlake, Texas (12.2); Macomb, Michigan (12.0); and Utica, Michigan (11.8).
Utah, however, had the worst ratio countrywide (2.6 to 1), and Intercourse, Pennsylvania, secured the worst ratio out of the cities examined (0.02 to 1).
Pairing Emotional Words
While some people may just tweet a hashtagged word and nothing else, it’s more likely you’ll find an emotive word paired with other words that can help further define the tagger’s temperament. We found #happy was most often paired with “birthday” (9.1 percent). This was followed by “love,” “hope,” “great,” “good,” and “happiness.”
Next, we looked at words that were most often included with #sad. “Sadly” took the top spot (1.2 percent), but “people,” “time,” “happy,” and “today” were also commonly associated with feeling blue.
Finally, “people” were most often associated with #angry, followed by “time,” “sad,” and “never.”
Interestingly, President Trump showed up frequently in tweets mentioning #sad and #angry. His Twitter handle, @realdonaldtrump, found its way into #sad tweets, while “Trump” was the fifth most common word associated with #angry. There were a few expletives in both categories as well, including “sh*t” and “f**king.”
Finally, we wanted to see what time of the year was really the happiest. As it turns out, it wasn’t the holiday season. During April, there were 5.5 #happy tweets for every #sad tweet, which was the most for the entire year. This is possibly due to folks being really happy that winter is finally over, and spring has sprung. Also, don’t forget that people can be affected by the seasons and may experience seasonal affective disorder (SAD), which is common during the colder months when there is less sunlight. Once the weather warms up, SAD usually goes away.
Sunday also tended to have the highest ratio of #happy tweets, and 2 p.m. checked in as the unofficial #happy hour of the day, according to Twitter.
Happy or Sad: Twitter Knows All?
While it’s easy to look at stats from Twitter to figure out how people really feel, it’s probably not completely accurate, as not everyone uses Twitter – and people don’t tweet out every single emotion they feel every single day. So does this mean that people are happiest in Nebraska on Sundays in April at 2 p.m.? Well, according to our findings, yes, but take that knowing this study is limited to people who actually tweet.
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Methodology and Limitations
Tweets were from Jan. 9, 2017, through March 29, 2018. In total, 12,136,288 tweets were collected. The breakdown for each hashtag is as follows:
- #Happy: 9,748,597
- #Sad: 2,142,563
- #Angry: 245,128
The top and bottom states and cities were calculated by looking at Twitter usage rates by each state. We then looked at how much each state and city tweeted each of the hashtags relative to what you would expect them to tweet given their size.
Tweets must have had at least one of these hashtags appear in their text to qualify.
For “The Landscape of #Emotions” and “Most Emotional Cities in Each State” accounts that tweeted one of these hashtags more than 10 times were excluded.
For “#Happy to #Sad Tweet Ratio,” cities needed to have at least 250 #sad tweets to qualify.
For “Words Most Associated With …,” words like “the,” “one,” “don’t,” and “won’t” were hidden.
This survey relies on self-reported information from employees. Problems with self-reported responses include telescoping, selective memory, and exaggeration. This is important to remember when reviewing survey results, as this data was not statistically tested and relies solely on self-reported survey responses.
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