1 China January inflation plunges to 0.8% (Straits
Times) China's inflation plunged to 0.8 per cent in January, its lowest level
for more than five years, official data showed. The rise in the consumer price
index (CPI) was sharply down from the 1.5 per cent recorded in December,
according to figures provided by the National Bureau of Statistics (NBS).
The CPI figure reinforces signs of persistent
weakness in the economy and broadens the scope for further stimulus steps by
the central bank to ward off deflationary risks. Analysts had expected annual
consumer inflation to be 1.0 percent in January, compared with 1.5 per cent in
December.
2 India GDP formula baffles experts (BBC) The Indian
economy grew by 7.5% between October and December compared with the same period
a year earlier, official figures say. But there was confusion regarding the
statistics after the way in which the gross domestic product (GDP) figure was
calculated was changed. Economists warned the figures needed to be treated with
caution.
The country's new way of calculating GDP has baffled
analysts since its release last month. India said the new formula is closer to
international standards. But analysts say the new data does not correlate with
other economic indicators, including industrial and factory production.
Some economists have said the latest figures should
be "taken with a pinch of salt" and expressed scepticism over the
figures at a time when India's central bank has been talking about a slowdown. Jyotinder
Kaul, principal economist at HDFC Bank, also questioned the
"credibility" of the numbers.
India was believed to be in the midst of the worst
economic slowdown since the 1980s with below 5% growth, a level that was
considered to be too low to generate jobs for millions of young people. Indian
Prime Minister Narendra Modi won last year's general elections on a promise to
reform and revive the economy and attract much-needed foreign investment.
Optimism has grown, but the country is yet to see any of the big bang reforms Modi
promised to revive the economy.
3 How Twitter predicts heart disease (Kristen V
Brown in San Francisco Chronicle) New research from the University of
Pennsylvania suggests that analyzing tweets on the social network can provide
better insight into the prevalence of coronary heart disease in a community
than many more traditional methods of prediction than factors such as smoking,
diabetes and obesity — combined.
University of Pennsylvania searched geo-tagged
tweets sent from 1,300 US counties between 2009 and 2010, sorting tweets
according to the types of emotions they conveyed. Researches then compared the
findings to CDC heart disease mortality data from the same years. The tweets
conveying negative feelings closely matched with the CDC data.
Tweets about things such as anger, stress and
fatigue, it turned out, were a signifier for heart disease risk. More
optimistic tweets, on the other hand, were associated with a lower risk of
disease. The new research was rooted in previous studies that showed characteristics
such as depression and chronic stress are affiliated with an increased risk of
disease.
Johannes Eichstaedt, the study’s lead author, said
the hope is to eventually expand the research to understand how psychological
traits are linked to physical health. However, big data has its limits. Google
Flu Trends, once the great beacon for the promise of Big Data in health, has
recently come under attack. Last spring, social scientists found that Google
had consistently overshot the number of reported flu cases. Google, they said,
was guilty of “big data hubris.”
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