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Study: Twitterati More Logical in the Morning, Emotional in the Evening

They found that the tweets starting at around 5 a.m. to 6 a.m., depicts expressions with measures of analytical thinking through the high use of nouns, articles and prepositions

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Twitter confirms third-party involvement in crypto hackings. Pixabay

Early morning tweets are often based on a logical way of thinking, while those in the evenings and nights are high on emotions, finds an analysis of 800-million tweets.

The findings showed that our mode of thinking changes at different times of the day and follows a 24-hour pattern.

At 6 a.m., 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.

“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, Professor at the Britain’s University of Bristol.

“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.

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Twitter Icon, Pixabay

“This will help us understand the basis of disorders in which this process is disrupted,” Lightman added.

For the study, published in the journal PLOS ONE, the team examined thinking behaviour by analysing seven-billion words used in 800-million tweets.

They found that the tweets starting at around 5 a.m. to 6 a.m., depicts expressions with measures of analytical thinking through the high use of nouns, articles and prepositions.

Also Read: Live News Events on Your Twitter Timeline, Notifications 

This early-morning period also shows increased concern with achievement and power. On the other hand, the researchers found a more impulsive, social, and emotional mode during evening.

The tweets during evening were correlated with the language of existential concerns but anti-correlated with expression of positive emotions.

Overall, the study found strong evidence that our language changes dramatically between night and day, reflecting changes in our concerns and underlying cognitive and emotional processes, the researchers said.

These shifts also occur at times associated with major changes in neural activity and hormonal levels, suggesting possible relations with our circadian clock. (IANS)

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Are you an Avid Twitter User? Your Posts can Reveal How Lonely you are

If we are able to identify lonely individuals and intervene before the health conditions associated with the themes we found begin to unfold, we have a change

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Twitter, User, Posts
Loneliness can be a slow killer, as some of the medical problems associated with it can take decades to manifest. Pixabay

Researchers have found that users who tweet on loneliness are much more likely to write about mental well-being issues and things like struggles with relationships, substance use and insomnia on Twitter.

By applying linguistic analytic models to tweets, researchers were able to gain an insight into the topics and themes that could be associated with loneliness.

“Loneliness can be a slow killer, as some of the medical problems associated with it can take decades to manifest,” said the study’s lead author Sharath Chandra Guntuku, from University of Pennsylvania in the US.

“If we are able to identify lonely individuals and intervene before the health conditions associated with the themes we found begin to unfold, we have a change to help those much earlier in their lives. This could be very powerful and have long-lasting effects on public health,” Guntuku said.

Twitter, User, Posts
By applying linguistic analytic models to tweets, researchers were able to gain an insight into the topics and themes that could be associated with loneliness. Pixabay

By determining typical themes and linguistic markers posted to social media that are associated with people who are lonely, the team has uncovered some of the ingredients necessary to construct a ‘loneliness’ prediction system.

As part of the study, published in the journal BMJ, researchers analysed public accounts from users based in Pennsylvania and found that 6,202 accounts used words such as ‘lonely’ or ‘alone’ more than five times between 2012 and 2016.

Comparing the entire Twitter timelines of these users to a matched group who did not have such language included their posts, the researchers showed that ‘lonely’ users tweeted nearly twice as much and were much more likely to do so at night.

When the tweets were analysed via several different linguistic analytic models, the users who posted about loneliness had an extremely high association with anger, depression and anxiety, when compared to the ‘non-lonely’ group.

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Additionally, the lonely groups were significantly associated with tweeting about struggles with relationships (for example, using phrases like ‘want somebody’ or ‘no one to’) and substance use (‘smoke,’ ‘weed,’ and ‘drunk’)

“On Twitter, we found lonely users expressing a need for social support, and it appears that the use of expletives and the expression of anger is a sign of that being unfulfilled,” Guntuku said.

Users in the group that didn’t post about loneliness seemed to display some social connections, as they were found to be more likely to engage in conversations, especially by including others’ user names (using ‘@twitter_handle’) in their tweets.

In the future, the researchers hope to develop a better measure of the different dimensions of loneliness that online users are feeling and expressing. (IANS)