Sadness is the new Twitter trend, university study shows
Over time, users of Twitter have become less happy and more sad in their communicae, according to a study by University of Vermont researchers, who got published in science journal PLoS.
Data was collected via tracking a vast amount of keywords with differing types of sentiment (some happy, some neutral, others not so happy). These words ranged from your everyday sentence connectives to more emotive cases like "pancakes" or "suicide." With this, researchers could calculate the gross domestic happiness amongst Twitter users.
To determine a happiness value of the keywords used in the experiment, the team took advantage of the crowdsourcing capabilities of Human Intelligence Task machine that is Amazon's Mechanical Turk: asking participants to rate the keywords on a scale of 1-10 for how happy it makes them feel. Scores were then averaged to give the overall happiness values of each of the words — examples given include "laughter" at 8.50, "food" at 7.44, "greed" at 3.06, and "terrorist" at 1.30.
46 billion words over the last three years were analysed from all of Twitter's 63 million global users. The average general trend of this massive set of data shows a downward line of happy sentiment in tweets, which they say means that users have become progressively unhappier over time. Upsurges have occurred at the obvious points, holiday season primarily. Whereas the depressions on the can be quite easily linked to different low points in the public agenda: eg. The death of Michael Jackson (25th June 2009) and the Fukushima Nuclear Disaster (23rd July 2011).
The researchers have not drawn a conclusion as to why this overall trend in sadness, and it's also worth noting that the results do not take into account multiple connotations of the keywords selected. Of course, there's some which are pretty decisive (such as 'suicide'); but what's to say that 'reunion' or 'truck' are necessarily positive words. Plus as users strive more to curate their lives in social media, how realistic of a self-representation is your Twitter account in actuality?
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