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Serial Killers Should Fear This Algorithm - Bloomberg. On Aug. 18, 2010, a police lieutenant in Gary, Ind., received an e-mail, the subject line of which would be right at home in the first few scenes of a David Fincher movie: “Could there be a serial killer active in the Gary area?” It isn’t clear what the lieutenant did with that e-mail; it would be understandable if he waved it off as a prank. But the author could not have been more serious. He’d attached source material—spreadsheets created from FBI files showing that over several years the city of Gary had recorded 14 unsolved murders of women between the ages of 20 and 50.

The cause of each death was the same: strangulation. Compared with statistics from around the country, he wrote, the number of similar killings in Gary was far greater than the norm. The police lieutenant never replied. The Gary police never responded to that e-mail, either, or to two follow-up letters sent via registered mail. Hargrove spent his career as a data guy. MAP tracks staffing trends on its website, too. 2015-FIeld-Guide-To-Data-Science. Forget big data – it's time for big algorithms to change the world. It's no good just having data – it's what you do with it that counts. In five years, one million new devices will come online every hour, creating billions of new interconnections and relationships, and producing more and more data. But these relationships will not be driven by data, but by algorithms. "Data is inherently dumb," says Peter Sondergaard, senior vice president at Gartner and global head of research.

"It doesn't actually do anything unless you know how to use it, and how to act with it – algorithms are where the real value lies," he adds. Forget big data, it's time for big algorithms – and an algorithmic economy. What is an algorithm? Using a set of rules to follow in making calculations – algorithms – is how many of today's most famous websites and services work their magic. Confused? Other examples include Amazon's recommendation algorithm, and the Waze algorithm that directs thousands of independent cars on the road. Missing the point What is the algorithmic economy? What Does The Data Tell You; Pulsar. Pulsar wins the first DIVA (Data Insight Visualisation Award) « Signal.

The winning visualization is called “How Video Spreads” and shows the diffusion patterns of four viral stories mapped using network analysis. Twitter invited Face to explore how video content goes viral on Twitter. The selected stories had been chosen to represent various types of video content: Commander Hadfield singing Bowie’s “Space Oddity” on the International Space Station (for music videos), Dove “Real Beauty Sketches” (for advertising – the most-watched advert ever on YouTube), “Ryan Gosling Won’t Eat His Cereal” series of Vine videos (for serialised narrative content and mobile) and a grass-roots video of June’s protests in Izmir, Turkey (for real-time, bottom up news content). Based on Pulsar’s content tracking tools, the visualisation shows the diffusion patterns of each viral video. How riot rumours spread on Twitter | UK news.

How it works. Does big data hinder creative thinking? | Alan Hart. Quick Turn Data Projects | Austin Clemens. Does (Data) Size Really Matter? | Eynav (Navi) Azarya. How Analytics can Define the Future of Education Industry – AnalyticBridge. Education continues to play an important role in any country’s overall growth. The education market has become more challenging due to the rapid growth and evolution in the modes of imparting education; schools, colleges, private tuition, online education courses, distance education, test preparations, professional trainings etc. The most concerning factor for universities or educational institutions across the world is student dropout rate, especially in developed countries. Here are some facts based on a research about the student drop out patterns in large economies. Analytics can play a vital role in the education industry by helping universities and institutes make data oriented informed decisions. What-if scenarios, plans, budgets, forecasts Analyzing academic, financial and operational data helps identify specific patterns and trends.

Reports, Dashboards, Scorecards Analyzing the trend Survey Analytics for understanding student sentiment Predictive analytics. How Emergent founder Craig Silverman is using data to hunt down online hoaxes. If anyone can claim to be an expert in online rumors, falsehoods and fakes, it would have to be Craig Silverman, who has written both a book and a blog called Regret The Error and is now a fellow at Columbia University’s Tow Center for Digital Media. But Silverman doesn’t just want to write about online fakery, he wants to help stamp it out, and in order to do so he has launched a data-driven tracker called Emergent, which follows and debunks online hoaxes of various kinds. Silverman is a journalist and former managing editor of PBSMediaShift, as well as a founder of OpenFile, a pioneering Canadian effort at crowdsourced local news (in the interests of disclosure, he is also a friend). I was interested in what he was up to with Emergent, so I called him up and asked him why he started it and how it works.

Trying to gauge truthiness So how does Emergent work? Tracking the spread of rumors Giving journalists better tools Featured image by Brian A Jackson/Shutterstock. What we read about deep learning is just the tip of the iceberg. The artificial intelligence technique known as deep learning is white hot right now, as we have noted numerous times before. It’s powering many of the advances in computer vision, voice recognition and text analysis at companies including Google, Facebook, Microsoft and Baidu, and has been the technological foundation of many startups (some of which were acquired before even releasing a product).

As far as machine learning goes, these public successes receive a lot of media attention. But they’re only the public face of a field that appears to be growing like mad beneath the surface. So much research is happening at places that are not large web companies, and even most of the large web companies’ work goes unreported. We’ll talk more about some of these efforts at our Structure Data conference in March, where speakers include a senior researcher from Facebook’s AI lab, as well as prominent AI and robotics researchers from labs at Stanford and MIT. 5 Common Unconscious Biases That Lead To Bad Decisions. Quick decisions save time and energy, but sometimes those knee-jerk reactions lead to bad choices. That’s because biases impact our thinking every day, but few of us even know they exist, says Norma Montague, assistant professor of accounting at Wake Forest University in Winston-Salem, North Carolina.

"The word bias has a negative connotation, but it’s most often unintentional and a result of heuristics—mental shortcuts that allow people to make quick, efficient decisions," she says. "Good decisions are often the result, but not always. " Biases work well because they’re often systematic and predictable, but problems arise when individuals habitually rely on this method of decision making, excluding or ignoring additional information. While Montague’s research focuses on bias in accounting, her findings apply to any profession. Availability Bias "Individuals have a tendency to make decisions based on whatever information is easily retrievable to them," she says. Anchor Bias. Real insights are truly hard to come by – the best most ‘heads of insight’ can produce are observations. I was sitting in a meeting the other day with an advertising agency in London and one of the agency team said they had a really good ‘insight’. After further discussion it seemed to me it was more of an observation than a flash of inspiration.

It got me thinking a bit more about that particular word because I have seen it used in job descriptions more frequently recently, both on the client and agency side so I thought it was worth a bit of investigation. My conclusion to date is that the word ‘insight’ is a fad and an over-claim. One explanation given to me relating to a very large and famous client was that the ‘head of insight’ worked in the research unit and his/her job was to trawl through all of their research looking for little gems that might affect their marketing and communication. Fair enough, but I was thinking that is what good planners do routinely in an agency. But is that insight? Well here is one I would put in the insight box. Just think about banking as a category. Five major trends in data and analytics for 2015 | World Of Tech News | TechRadar.

Experts have been talking about big data for years, but in 2014 companies started to embrace data insights for business decisions. For example fashion retailer Zara announced that it was using data and new technologies to track items in store to make smarter stocking decisions. Each time a garment was sold, data from its RFID chip prompted an instant order to the stockroom to send out an identical item. In 2015 we'll see companies take this approach one stage further, transforming into completely analytics-driven organisations.

However, this will require a fundamental shift in thinking and approach. Investing in the right tools and technology is essential but for data to be a strategic asset, the company also has to make it a cultural focus. Our five predictions for data this year highlight the fact that numerical insights are bound to become inescapable in business. 1. 2015 will be the year when every business decision derives from analytics. 2. 3. 4. 5. API. Fully featured, in 6 languages Semantria is built upon leading enterprise Text and Analytics technologies. Our clients benefit from years of R&D, field testing and algorithmic tweaking. All features are available in six different languages: English, French, Portuguese, Spanish, German and Mandarin. We also have Italian, Japanese and Korean in the works.

Fast. The Semantria API is designed with performance in mind. Regularly submerged with millions of calls, the Semantria Cloud is well monitored and scales automatically to take the huge number of requests our clients throw at it! Try to overload it. Distributed & Scalable Our API is designed to support every possible integration scenario. We also have batch processing as well as synchronous and asynchronous modes. Highly Customizable What really sets Semantria apart from other enterprise and cloud NLP engines is configurability. Semantria has more features than any other cloud API. Comprehensive SDK Human Support Team. Big Data’s Impact in the World. Welcome to the Age of Big Data. The new megarich of Silicon Valley, first at Google and now Facebook, are masters at harnessing the data of the Web — online searches, posts and messages — with Internet advertising. At the World Economic Forum last month in Davos, Switzerland, Big Data was a marquee topic.

A report by the forum, “Big Data, Big Impact,” declared data a new class of economic asset, like currency or gold. Rick Smolan, creator of the “Day in the Life” photography series, is planning a project later this year, “The Human Face of Big Data,” documenting the collection and uses of data. What is Big Data? Link these communicating sensors to computing intelligence and you see the rise of what is called the Internet of Things or the Industrial Internet. Data is not only becoming more available but also more understandable to computers. But the computer tools for gleaning knowledge and insights from the Internet era’s vast trove of unstructured data are fast gaining ground. Photo. Nielsen’s Mobile Consumer Report. Nielsen have just released their Mobile Consumer Report.

It’s got some interesting findings, so we thought we’d give you a summary. The current landscapeMobile phone ownership in both developed and high-growth countries has reached a critical mass, with no growth from the first half of 2012. The high rates of ownership are shown in the below graph: Nevertheless, the kinds of phone we own are changing. Some countries have a higher prevalence of multiple-device ownership, too, as highlighted by the coloured segments in these pie charts: The report also contains interesting information on where and why we purchase our devices. 49% of Russian mobile users purchased their device at a major electronics or media store, whilst 39% of those in the UK purchased online. Behaviours: shopping, social & videoWorldwide, text messaging is by far the most popular use of a mobile device.

Another big use of smartphones is in watching mobile video, the frequency of which is shown below. Top 5 Myths About Big Data. Brian Gentile is the CEO of Jaspersoft, a commercial open source business intelligence software company. Folllow him @BrianG_Jasper With the amount of hype around Big Data it’s easy to forget that we’re just in the first inning.

More than three exabytes of new data are created each day, and market research firm IDC estimates that 1,200 exabytes of data will be generated this year alone. The expansion of digital data has been underway for more than a decade and for those who’ve done a little homework, they understand that Big Data references more than just Google, eBay, or Amazon-sized data sets. The opportunity for a company of any size to gain advantages from Big Data stem from data aggregation, data exhaust, and metadata — the fundamental building blocks to tomorrow’s business analytics. Combined, these data forces present an unparalleled opportunity. Yet, despite how broadly Big Data is being discussed, it appears that it is still a very big mystery to many. 1. 2. 3. 4. 5.

Measuring the world’s emotions using Twitter and Amazon’s cloud. There are some things that just weren’t possible before the world wide web and cloud computing, and a recently launched emotion-quantification project called “We Feel” is one of them. The project, which is a partnership between Australia’s Black Dog Institute and its Commonwealth Scientific and Industrial Research Organization (CSIRO), is analyzing every English-language Twitter post around the world in order to determine how people are feeling. Using data from Gnip, the social-media data feed that Twitter recently acquired, We Feel gauges where tweets range on a spectrum from “joy” to “fear” (as well as “surprise”) and then breaks them down at a more-granular level (e.g., from “joy” to “zest” to “invigorated”).

It also captures metadata on the countries from which tweets are coming, the sex of the person doing the tweeting and the timestamp of the tweet. An unfiltered look at We Feel as of 11 a.m. Pacific Time on June 5. Finding partners in the cloud. This Site Visualizes Your Death. Ever wonder how you fit into the teeming swarm of humanity, statistically? Now in beta, is a great new site designed by Benedikt Groß (previously featured on Co.Design for his typeface made up of satellite imagery) that visualizes your place in the world population in a series of attractively design tables and charts.

That includes, rather morbidly, an estimate of when you'll die. At the top of the page, you can watch as babies are burped out around the world at a rate of about three every second. It's once you enter your date of birth, your country of origin, and your gender that's magic really happens, though, quantifying exactly what your place in the world's population really is. For example, it might turn out that you're older than you think you are. The stats continue. As for when I'll die? Check out for yourself here. [Cover Photo: Karen Perhus via Shutterstock]