800 mln tweets reveal distinct daily cycles in our thought patterns
The analysis of media content, when done correctly, can reveal useful information for both social and biological sciences.
Researchers at the University of Bristol in the UK used artificial intelligence (AI) to analyse aggregated and anonymised twitter content sampled every hour over the course of four years across 54 of the country's largest cities to determine if our thinking modes change collectively.
The, study published in the journal PLOS ONE, revealed different emotional and cognitive modalities in our thoughts by identifying variations in language through tracking the use of specific words across the twitter sample which are associated with 73 psychometric indicators, and are used to help interpret information about our thinking style.
At 6 am, analytical thinking was shown to peak, the words and language at this time were shown to correlate with a more logical way of thinking. However, in the evenings and nights this thinking style changed to a more emotional and existential one.
Although 73 different psychometric quantities were tracked, the team found there were just two independent underlying factors that explained most of the temporal variations across the data.
The first factor, with a peak expression time starting at around 5 am to 6 am, linked with measures of analytical thinking through the high use of nouns, articles and prepositions, which has been related, in other studies, to intelligence, improved class performance and education.
This early-morning period also shows increased concern with achievement and power. At the opposite end of the spectrum, the researchers find a more impulsive, social, and emotional mode.
The second factor had a peak expression time starting at 3 am to 4 am, the aggregated twitter content found this time to be correlated with the language of existential concerns but anti-correlated with expression of positive emotions.
"The analysis of media content, when done correctly, can reveal useful information for both social and biological sciences. We are still trying to learn how to make the most of it," said Nello Cristianini, a professor at University at Bristol.
"Circadian rhythms are a major feature of most systems in the human body, and when these are disrupted they can result in psychiatric, cardiovascular and metabolic disease," said Stafford Lightman, a professor at Bristol Medical.
"The use of media data allows us to analyse neuropsychological parameters in a large unbiased population and gain insights into how mood-related use of language changes as a function of time of day. This will help us understand the basis of disorders in which this process is disrupted," said Lightman.
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