Public discourse on environmental and health issues has risenon social media. Upon an environmental crisis, various chatterssuch as breaking news, misinformation, and rumor couldaggravate social confusion and proliferate negative publicsentiment. In an effort to study public sentiments on environmentalissues in South Korea, we analyzed 158,964 tweetsgenerated over a 4-year period following the Fukushima accidentin 2011, the largest release of radioactivity to environmentin recent history. This event led to a significant increasein public’s interest on environmental and nuclear issues inKorea. We employed Bayesian network and recursive partitioningto observe the classification regression tree structureof major topics. Topics on health and environment were interlinkedclosely and represented both apprehension and concernabout health threats and pollution. Our methodologyhelps analyze large online discourse efficiently and offers insightto crisis response organizations.

We examine the question of whether we can automatically classify the sentiment of individual tweets in Farsi, to determine their changing sentiments over time toward a number of trending political topics. Examining tweets in Farsi adds challenges such as the lack of a sentiment lexicon and part-of-speech taggers, frequent use of colloquial words, and unique orthography and morphology characteristics. We have collected over 1 million Tweets on political topics in the Farsi language, with an annotated data set of over 3,000 tweets. We find that an SVM classifier with Brown clustering for feature selection yields a median accuracy of 56% and accuracy as high as 70%. We use this classifier to track dynamic sentiment during a key period of Irans negotiations over its nuclear program.

Citigroup is to roll out voice recognition software to its Asian customer base, shrinking its branch network as more customers move to online and mobile banking.

ARTIFICIAL INTELLIGENCE: Can Artificial Intelligence Create the Next Wonder Material? Nicola Nosengo Nature "Instead of continuing to develop new materials the old-fashioned way -- stumbling across them by luck, then painstakingly measuring their properties in the laboratory -- Marzari and like-minded researchers are using computer modelling and machine-learning techniques to generate libraries of candidate materials by the tens of thousands." COMPUTING: Why Machine Vision Is Flawed in the Same Way as Human Vision MIT Technology Review "If machine vision and human vision work in similar ways, are they also restricted by the same limitations? Do humans and machines struggle with the same vision-related challenges? Today we get an answer thanks to the work of Saeed Reza Kheradpisheh at the University of Tehran in Iran and a few pals from around the world.

The big news on March 12 of this year was of the Go-playing AI-system AlphaGo securing victory against 18-time world champion Lee Se-dol by winning the third straight game of a five-game match in Seoul, Korea. After Deep Blue's victory against chess world champion Gary Kasparov in 1997, the game of Go was the next grand challenge for game-playing artificial intelligence. Go has defied the brute-force methods in game-tree search that worked so successfully in chess. In 2012, Communications published a Research Highlight article by Sylvain Gelly et al. on computer Go, which reported that "Programs based on Monte-Carlo tree search now play at human-master levels and are beginning to challenge top professional players." AlphaGo combines tree-search techniques with search-space reduction techniques that use deep learning.

Microsoft has published its latest Security Intelligence Report (SIR), which it does twice a year, covering security issues for the prior six months. This latest edition covers the second half of 2015, analyzing the threat landscape of exploits, vulnerabilities and malware using data from Internet services and over 600 million computers worldwide. It is a massive effort, with dozens of Microsoft staff from different groups contributing. For the first time, they looked at not only PC malware but threats to its Azure cloud service as well, which the company says "reveals how we are leveraging an intelligent security graph to inform how we protect endpoints, better detect attacks and accelerate our response, to help protect our customers." Every day, Microsoft's machine learning systems process more than 10 terabytes of data, including information on over 13 billion logins from hundreds of millions of Microsoft Account users and Azure Active Directory accounts, according to the company.

I wasn't planning to chip in this time, but I stumbled upon an article so compelling I felt I ought to. Uncanny Valley, published by Anna Weiner on N 1 Magazine, is a short literary piece which lives up to its title. Weiner's nameless narrator is going through most commonplaces of the Valley, both physically and mentally, without really being a part of it. "I learn the bare minimum, code-wise, to be able to do my job well -- to ask questions only when I'm truly in over my head," she confesses. She is going from being the start-up's inaugural customer support rep to become a "success manger", a title so corny for her she can't stand having it on her email signature.

In a blitzkrieg attack that took place over 12 hours in late 2012 and early 2013, criminals stole 45-million (U.S.) from two banks by hacking into credit card processing firms in India and the United States, then withdrawing money from ATMs in 27 countries. "In the place of guns and masks, this cybercrime organization used laptops and the Internet," New York attorney Loretta Lynch said at a news conference. "Moving as swiftly as data over the Internet … they became a virtual criminal flash mob, going from machine to machine, drawing as much money as they could, before these accounts were shut down." The mob infiltrated credit card processing firms, stole prepaid Visa and MasterCard debit card account numbers issued by the banks in the Middle-East and programmed them with extreme balances. The account numbers were emailed or texted to cohorts on the ground, who used a device to encode the account numbers onto the magnetic stripes of dummy cards.

When will the technology arrive that makes you obsolete in your current job? It's no idle question, and one that none other than Microsoft CEO Satya Nadella took up this week in remarks to hundreds of Seattle technology and business leaders. We'll explore his comments, a new offering from Textio, the media's failures in covering the presidential primaries; have some fun with drones, Star Wars, Disney's Frozen, and STEM education; and wash it down with a cold home brew in this edition of Xconomy Seattle's Week in Review: He shared his view of Microsoft's unique culture, and how that gives the company an advantage. One aspect is Microsoft's global mindset, which Nadella, born in Hyderabad, India, talked about in a personal way. "I wouldn't be CEO of Microsoft if it was not for Microsoft's technology being a global force," Nadella said.

Humanyze has rolled out Wyze, its flagship product that is designed to measure social interactions and improve teamwork and processes in companies. BOSTON–(BUSINESS WIRE)–Humanyze, the global leader in people analytics technology, announced 4M in Series A financing today from Romulus Capital. The announcement comes as Humanyze rolls out the first of its kind Wyze people analytics platform to its strong Fortune 500 customer base in the US and industry leaders in Japan with the goal of making large corporations more agile and accurate about their most valuable resource (people), and to make these same people more in control of their performance and improvement. "Our customers – which include the largest multinationals and consulting firms – are investing heavily in technology and personnel to make full use of our data-driven people analytics platform. Employees are almost universally opting in as they see the individual benefits.