Tag Archives: hedonometer

Where is the happiest city in the USA?

Is Disneyland really the happiest place on Earth?* How happy is the city you live in? We have already seen how the hedonometer can be used to find the happiest street corner in New York City, now it’s time to let it loose on the entire United States.

We plotted over 10 million geotagged tweets from 2011 (all our results are in this paper), coloring each point by the average happiness of nearby words (detail on how we calculate happiness can be found in this article published in PLoS ONE):

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As well as cities and the roads between them, we can make out many regions of higher and lower happiness, even within individual cities. As an example, check out this tweet-generated map of the city of Chicago:

Tweet-generated map of Chicago. Click to enlarge.

Tweet-generated map of Chicago. Click to enlarge.

Notice the striking contrast between the relatively happy Central/North Side of the city, and the sadder South Side. You can also find a few airports in this map, and if you look very closely you might even be able to pick out happy and sad terminals!

To quantify this variation in happiness a bit better, let’s look at the average happiness of each state:

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Southern states tend to produce sadder words than those in northern New England or out west. Hawaii emerges as the happiest state and Louisiana as the saddest, due to relative differences in the frequencies of happy and sad words used in each state. Here at onehappybird, we characterize such differences by “word shifts”, which are basically word clouds for grown-ups. You can find examples of these, as well as the full list of the average happiness of each state, here (page best viewed using Google Chrome).

Zooming in further to the level of cities, we produced a similar list for 373 cities in the lower 48 states (you can find the full list, as well as maps and word shifts for each city, here). With a score of 6.25, we found the happiest city to be Napa, CA, due to a relative abundance of such happy words as “restaurant”, “wine”, and even “cheers”, along with a lack of profanity.

wordshiftNapaRedacted

At the other end of the spectrum, we found the saddest city to be Beaumont, TX, with a score of 5.82. In general, cities in the south tended to be less happy than those in the north, with a major contributing factor being the relative abundance of profanity used in those cities.

We can go even further than this, and group cities by similarities in word usage. Each square in the heatmap below represents the similarity (Spearman correlation for you mathematically minded onehappybird watchers) between word distributions for the largest cities in the US. Red squares mean that the corresponding cities use words in a similar fashion, while blue means that those cities tend to use different types of words with respect to each other. The colors in the tree diagram at the top signify clusters of cities exhibiting similar word usage (below a certain threshold).

As we might expect for two cities that are geographically nearby, New Orleans and Baton Rouge are clumped together at the bottom right of the figure. On the other hand, New York and Seattle get clumped together as well, suggesting that similarities in language depend on more than just geographical proximity.

cityClusters

You can find more information about happiness and cities, as well as details on the methods used to produce these results, in our arxiv research article. In our next post, we’ll look at how these results are related to various underlying socioeconomic characteristics of cities. What makes a city happy or sad? Can we use Big Data to predict future changes in the demographics, health, or happiness of a city? How does happiness relate to the food you eat?

*By the way, to answer the question at the start of this post: According to this analysis Disneyland is not the happiest place on Earth; it isn’t even the happiest place in Southern California! See if you can find it in this tweet-generated map of LA! Or find your city here.

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Filed under geohappiness, mathematics, psychology, social phenomena

Hedonometrics

Our paper “Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter” appears in PLoS ONE this week. Their blog encourages you to tweet for the sake of science!

Among other findings, in this paper we demonstrate that human ratings of the happiness of an individual word correlate very strongly with the average happiness of the words that co-occur with it. This implies that tweets containing particular keywords can be used as an unsolicited public opinion poll.

For example, tweets containing “Tiger Woods” became decidedly less positive after his Thanksgiving disaster in 2009 as the words ‘accident’, ‘crash’, ‘scandal’, and ‘cheating’ are more abundant, while the word ‘love’ appears less often.

Happiness is measured relative to the ambient background of all tweets.

Sad words are blue, happy words are yellow. Up (down) arrow indicates that the word appeared more (less) frequently in tweets containing "Tiger Woods".

Generally, tweets containing personal pronouns tell a positive prosocial story with ‘our’ and ‘you’ outranking ‘I’ and ‘me’ in happiness. The least happy pronoun on our list is the easily demonized ‘they’.

Emoticons in increasing order of happiness are ‘:(’, ‘:-(’, ‘;-)’, ‘;)’, ‘:-)’, and ‘:)’. In terms of increasing information content (diversity of words co-occuring with each emoticon), the order is ‘:(’, ‘:-(’, ‘:)’, ‘:-)’, ‘;)’, and ‘;-)’. We see that happy emoticons co-occur with words of higher levels of both happiness and information but the ordering changes in a way that appears to reflect a richness associated with cheekiness and mischief: the two emoticons involving semi-colon winks are third and fourth in terms of happiness but first and second for information.

A list of the happiness ratings of tweets containing some interesting keywords can be seen here.

And not surprisingly, the happiness of all tweets appearing on a given day of the week correlates well with the happiness ratings humans give each day.

Happiness of tweets appearing on a given day

Human ratings of the happiness of each day of the week

You can download the language assessment by Mechanical Turk (labMT 1.0) word list here. It is a text file containing the set of 10,222 most frequently occurring words in the New York Times, Google Books, music lyrics, and tweets, as well as their average happiness evaluations according to users on Mechanical Turk.  See the paper for details.

Much more to come regarding sociotechnical phenomena…

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Happy and we know it

Science Magazine published a piece today framing twitter as a laboratory for research, Social Scientists Wade Into The Tweet Stream, including the above figure showing our hedonometer’s measure of happiness in 2011 as a function of day. Dodds was also interviewed by Science for their weekly podcast, and by Benedict Carey for a New York Times piece, Happy and You Know It? So Are Millions on Twitter.

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Filed under social phenomena