Weekly News A researcher has applied advanced statistics to predict what characters will die in author George R.R. Martin's (pictured) "A Song of Ice and Fire" book series.

Published on October 3rd, 2014 | by Travis Korte

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10 Bits: The Data News Hot List

This week’s list of data news highlights covers September 27-October 3 and includes articles about LinkedIn’s new suite of student decision-making tools and the Centers for Medicare and Medicaid Services’ launch of its Open Payments website.

1. Automatically Tracking Rumors in Social Media

Real-time rumor tracking tool Emergent tracks online claims and debunks hoaxes that propagate through social and traditional media. Emergent’s team combs through Twitter, Facebook, news websites, and other sources to find claims that need verification. Then, after uploading the stories to Emergent’s database, an algorithm takes over and monitors further mentions of the same claim to determine if it has been debunked. The tool also lets users visualize the spread of a given rumor on social media.

2. LinkedIn Introduces Social Data Tools to Guide Student Decisions

LinkedIn introduced a host of tools this week to help student decision making on issues ranging from selecting the right school to planning a career path. The applications were developed on insights gathered from analyzing the social and career data on LinkedIn to remove some of the guesswork involved in choosing where and what to study. By analyzing millions of alumni profiles, LinkedIn can now rank universities on the success of recent graduates in their desired career paths, offer career path advice based on organizational and social analysis, and match prospective students with universities that are most likely to fulfill their career goals.

3. CMS Launches Open Payments Website

The Centers for Medicare and Medicaid Services launched its Open Payments site this week. Open Payments details the $3.5 billion in financial ties between the medical device and pharmaceutical industry and physicians and teaching hospitals. The site, which is the first public repository of national data describing such information, fulfills the requirement for such a database stipulated by the Affordable Care Act.

4. Using Statistics to Predict Who Will Die on “Game of Thrones”

A statistician at the University of Canterbury is using advanced statistical methods to predict what characters will live and die in George R.R. Martin’s “A Song of Ice and Fire” book series. The series, upon which the popular “Game of Thrones” show is based, is well-known for its violent plot, and the researcher hopes to use the contents of the books that have been released so far to predict characters’ fates in the final, as yet unreleased books. The method relies on the fact that each chapter of the books is written from the point of view of a particular character, and the number of chapters each major character narrates can be used to predict how many chapters that character will narrate in future books; when the number gets to zero, that character’s time is up.

5. Global Forest Watch Offers Deforestation Data Where Government Figures are Lacking

Global Forest Watch is an online platform that integrates hundreds of thousands of satellite images and crowdsourced map tagging to create a near-real-time picture of the state of global deforestation. The platform, which can automatically determine areas where the amount of forest cover is changing, could serve as a partial replacement for official government data sources in places where this information might be unreliable. The platform’s creators hope governments and civil society organizations can use it to inform policy around illegal logging and forest conservation.

6. CDC Wants Integrated Disease Tracking Tool

The Centers for Disease Control has filed a request for information regarding a versatile data and analytics tool for disease tracking. The tool has a long list of required features, including the ability to track, analyze, and visualize data from epidemiological, laboratory, environmental, and other sources. At present, the agency tracks data from these sources separately, and an integrated tool could help more rapidly identify and respond to emergencies that create data in multiple domains.

7. MIT Launches Twitter-Funded Social Media Analysis Lab

The Massachusetts Institute of Technology launched its Laboratory for Social Machines this week with a $10 million funding commitment from Twitter. The initiative will focus on developing new technologies to detect and analyze patterns in social media and other digital content. The laboratory, which will be housed at the school’s Media Lab, will also integrate data visualization and mobile app development.

8. How Solar-Ready is Your House?

Mapdwell, a startup that spun off from a Massachusetts Institute of Technology project, maps the solar potential of buildings in cities using data from aerial mapping flights. The company creates a one-by-one meter resolution 3D model of each plot of land, identifying roof surface area, skylights, surrounding trees, and other features. Users can visualize this data on Mapdwell’s site to see how much solar potential their home or business has.

9. Google’s “Physical Web” Aims for Easier IoT Access

Google has launched a new standards project called “Physical Web,” which aims to integrate search technologies into the Internet of Things (IoT). The project’s creators expect that using apps to connect with every IoT device will be impractical, so they have developed a more web-like approach, in which devices are equipped with URLs and any authorized user can navigate to them to receive data. The first manifestation of the Physical Web is an app that passively monitors nearby devices that users can interact with when they approach.

10. New Smartphone App StudentLife Can Chart Student Stress Levels

Researchers at Dartmouth College found that by analyzing behavioral data gathered through their StudentLife app, they could map student stress levels throughout the course of a semester. The app relies on data from students’ phone usage and can determine sleep patterns, exercise habits, and social interactions with minimal qualitative input from users. Researchers were able to analyze the data gathered over a 10 week period to predict stress levels and the overall well-being of the students. StudentLife Developers hope to expand the app to more users beyond Dartmouth students to track activity and alert users whose data indicates they are overstressed, lonely, or even depressed to seek help.

Photo: Flickr user icantu

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About the Author

Travis Korte is a research analyst at the Center for Data Innovation specializing in data science applications and open data. He has a background in journalism, computer science and statistics. Prior to joining the Center for Data Innovation, he launched the Science vertical of The Huffington Post and served as its Associate Editor, covering a wide range of science and technology topics. He has worked on data science projects with HuffPost and other organizations. Before this, he graduated with highest honors from the University of California, Berkeley, having studied critical theory and completed coursework in computer science and economics. His research interests are in computational social science and using data to engage with complex social systems. You can follow him on Twitter @traviskorte.



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