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Looters of Poor and Middle classes in the past will have to return what they had looted: PM Narendra Modi

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Narendra Modi. Pixabay

New Delhi, April 18, 2017: Prime Minister Narendra Modi said on Tuesday that those who had looted the poor and the middle classes in the past will have to return what they had looted.

“Indeed. There is no place for corruption in India. Those who looted the poor and middle classes will have to return what they have looted,” Modi said on Twitter in response to a tweet by a follower.

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Modi’s remarks came on a day liquor baron Vijay Mallya, wanted in India for defaulting on over Rs 8,000 crore in bank loans, was arrested in London but later granted bail by a court.

Modi’s Twitter follower had written that “corruption not only robs us of hard-earned money but also of our dignity”.

Mallya, 61, was arrested following an extradition warrant from India.

“Mallya was arrested on behalf of the Indian authorities in relation to accusations of fraud,” a Metropolitan Police statement said. (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)