New Paper by William Li, Pablo Azar, David Larochelle, Phil Hill & Andrew Lo: “The agglomeration of rules and regulations over time has produced a body of legal code that no single individual can fully comprehend. This complexity produces inefficiencies, makes the processes of understanding and changing the law difficult, and frustrates the fundamental principle that the law should provide fair notice to the governed. In this article, we take a quantitative, unbiased, and software-engineering approach to analyze the evolution of the United States Code from 1926 to today. Software engineers frequently face the challenge of understanding and managing large, structured collections of instructions, directives, and conditional statements, and we adapt and apply their techniques to the U.S. Code over time. Our work produces insights into the structure of the U.S. Code as a whole, its strengths and vulnerabilities, and new ways of thinking about individual laws. For example, we identify the first appearance and spread of important terms in the U.S. Code like “whistleblower” and “privacy.” We also analyze and visualize the network structure of certain substantial reforms, including the Patient Protection and Affordable Care Act (PPACA) and the Dodd-Frank Wall Street Reform and Consumer Protection Act, and show how the interconnections of references can increase complexity and create the potential for unintended consequences. Our work is a timely illustration of computational approaches to law as the legal profession embraces technology for scholarship, to increase efficiency, and to improve access to justice.”
Mapping the Age of Every Building in Manhattan
Kriston Capps at CityLab: “The Harlem Renaissance was the epicenter of new movements in dance, poetry, painting, and literature, and its impact still registers in all those art forms. If you want to trace the Harlem Renaissance, though, best look to Harlem itself.
Many if not most of the buildings in Harlem today rose between 1900 and 1940—and a new mapping tool called Urban Layers reveals exactly where and when. Harlem boasts very few of the oldest buildings in Manhattan today, but it does represent the island’s densest concentration of buildings constructed during the Great Migration.
Thanks to Morphocode‘s Urban Layers, it’s possible to locate nearly every 19th-century building still standing in Manhattan today. That’s just one of the things that you can isolate with the map, which combines two New York City building datasets (PLUTO and Building Footprints) and Mapbox GL JS vector technology to generate an interactive architectural history.
So, looking specifically at Harlem again (with some of the Upper West Side thrown in for good measure), it’s easy to see that very few of the buildings that went up between 1765 to 1860 still stand today….”
Tell Everyone: Why We Share & Why It Matters
Book review by Tim Currie: “Were the people sharing these stories outraged by Doug Ford’s use of an ethnic stereotype? Joyfully amused at the ongoing campaign gaffes? Or saddened by the state of public discourse at a democratic forum? All of these emotions likely played a part in driving social shares. But a growing body of research suggests some emotions are more influential than others.
Alfred Hermida’s new book, Tell Everyone: Why We Share & Why It Matters, takes us through that research—and a pile more, from Pew Center data on the makeup of our friends lists to a Yahoo! study on the nature of social influencers. One of Hermida’s accomplishments is to have woven that research into a breezy narrative crammed with examples from recent headlines.
Not up on the concept of cognitive dissonance? Homophily? Pluralistic ignorance? Or situational awareness? Not a deal breaker. Just in time for Halloween, Tell Everyone (Doubleday Canada) is a social science literature review masquerading as light bedside reading from the business management section. Hermida has tucked the academic sourcing into 21 pages of endnotes and offered a highly readable 217-page tour of social movements, revolutions, journalistic gaffes and corporate PR disasters.
The UBC journalism professor moves easily from chronicling the activities of Boston Marathon Redditors to Tahrir Square YouTubers to Japanese earthquake tweeters. He dips frequently into the past for context, highlighting the roles of French Revolution-era salon “bloggers,” 18th-century Portuguese earthquake pamphleteers and First World War German pilots.
Indeed, this book is only marginally about journalism, made clear by the absence of a reference to “news” in its title. It is at least as much about sociology and marketing.
Mathew Ingram argued recently that journalism’s biggest competitors don’t look like journalism. Hermida would no doubt agree. The Daily Show’s blurring of comedy and journalism is now a familiar ingredient in people’s information diet, he writes. And with nearly every news event, “the reporting by journalists sits alongside the accounts, experiences, opinions and hopes of millions of others.” Journalistic accounts didn’t define Mitt Romney’s 2012 U.S. presidential campaign, he notes; thousands of users did, with their “binders full of women” meme.
Hermida devotes a chapter to chronicling the ways in which consumers are asserting themselves in the marketplace—and the ways in which brands are reacting. The communications team at Domino’s Pizza failed to engage YouTube users over a gross gag video made by two of its employees in 2009. But Lionsgate films effectively incorporated user-generated content into its promotions for the 2012 Hunger Games movie. Some of the examples are well known but their value lies in the considerable context Hermida provides.
Other chapters highlight the role of social media in the wake of natural disasters and how users—and researchers—are working to identify hoaxes.
Tell Everyone is the latest in a small but growing number of mass-market books aiming to distill social media research from the ivory tower. The most notable is Wharton School professor Jonah Berger’s 2013 book Contagious: Why Things Catch On. Hermida discusses the influential 2009 research conducted by Berger and his colleague Katherine Milkman into stories on the New York Times most-emailed list. Those conclusions now greatly influence the work of social media editors.
But, in this instance at least, the lively pacing of the book sacrifices some valuable detail.
Hermida explores the studies’ main conclusion: positive content is more viral than negative content, but the key is the presence of activating emotions in the user, such as joy or anger. However, the chapter gives only a cursory mention to a finding Berger discusses at length in Contagious—the surprisingly frequent presence of science stories in the list of most-emailed articles. The emotion at play is awe—what Berger characterizes as not quite joy, but a complex sense of surprise, unexpectedness or mystery. It’s an important aspect of our still-evolving understanding of how we use social media….”
Alfred Hermida’s new book, Tell Everyone: Why We Share & Why It Matters, takes us through that research—and a pile more, from Pew Center data on the makeup of our friends lists to a Yahoo! study on the nature of social influencers. One of Hermida’s accomplishments is to have woven that research into a breezy narrative crammed with examples from recent headlines.
Not up on the concept of cognitive dissonance? Homophily? Pluralistic ignorance? Or situational awareness? Not a deal breaker. Just in time for Halloween, Tell Everyone (Doubleday Canada) is a social science literature review masquerading as light bedside reading from the business management section. Hermida has tucked the academic sourcing into 21 pages of endnotes and offered a highly readable 217-page tour of social movements, revolutions, journalistic gaffes and corporate PR disasters.
The UBC journalism professor moves easily from chronicling the activities of Boston Marathon Redditors to Tahrir Square YouTubers to Japanese earthquake tweeters. He dips frequently into the past for context, highlighting the roles of French Revolution-era salon “bloggers,” 18th-century Portuguese earthquake pamphleteers and First World War German pilots.
Indeed, this book is only marginally about journalism, made clear by the absence of a reference to “news” in its title. It is at least as much about sociology and marketing.
Mathew Ingram argued recently that journalism’s biggest competitors don’t look like journalism. Hermida would no doubt agree. The Daily Show’s blurring of comedy and journalism is now a familiar ingredient in people’s information diet, he writes. And with nearly every news event, “the reporting by journalists sits alongside the accounts, experiences, opinions and hopes of millions of others.” Journalistic accounts didn’t define Mitt Romney’s 2012 U.S. presidential campaign, he notes; thousands of users did, with their “binders full of women” meme.
Hermida devotes a chapter to chronicling the ways in which consumers are asserting themselves in the marketplace—and the ways in which brands are reacting. The communications team at Domino’s Pizza failed to engage YouTube users over a gross gag video made by two of its employees in 2009. But Lionsgate films effectively incorporated user-generated content into its promotions for the 2012 Hunger Games movie. Some of the examples are well known but their value lies in the considerable context Hermida provides.
Other chapters highlight the role of social media in the wake of natural disasters and how users—and researchers—are working to identify hoaxes.
Tell Everyone is the latest in a small but growing number of mass-market books aiming to distill social media research from the ivory tower. The most notable is Wharton School professor Jonah Berger’s 2013 book Contagious: Why Things Catch On. Hermida discusses the influential 2009 research conducted by Berger and his colleague Katherine Milkman into stories on the New York Times most-emailed list. Those conclusions now greatly influence the work of social media editors.
But, in this instance at least, the lively pacing of the book sacrifices some valuable detail.
Hermida explores the studies’ main conclusion: positive content is more viral than negative content, but the key is the presence of activating emotions in the user, such as joy or anger. However, the chapter gives only a cursory mention to a finding Berger discusses at length in Contagious—the surprisingly frequent presence of science stories in the list of most-emailed articles. The emotion at play is awe—what Berger characterizes as not quite joy, but a complex sense of surprise, unexpectedness or mystery. It’s an important aspect of our still-evolving understanding of how we use social media….”
Ebola’s Information Paradox
It was a full seven days after Baby Lewis became ill, and four days after the Soho residents began dying in mass numbers, before the outbreak warranted the slightest mention in the London papers, a few short lines indicating that seven people had died in the neighborhood. (The report understated the growing death toll by an order of magnitude.) It took two entire weeks before the press began treating the outbreak as a major news event for the city.
Within Soho, the information channels were equally unreliable. Rumors spread throughout the neighborhood that the entire city had succumbed at the same casualty rate, and that London was facing a catastrophe on the scale of the Great Fire of 1666. But this proved to be nothing more than rumor. Because the Soho crisis had originated with a single-point source — the poisoned well — its range was limited compared with its intensity. If you lived near the Broad Street well, you were in grave danger. If you didn’t, you were likely to be unaffected.
Compare this pattern of information flow to the way news spreads now. On Thursday, Craig Spencer, a New York doctor, was given a diagnosis of Ebola after presenting a high fever, and the entire world learned of the test result within hours of the patient himself learning it. News spread with similar velocity several weeks ago with the Dallas Ebola victim, Thomas Duncan. In a sense, it took news of the cholera outbreak a week to travel the 20 blocks from Soho to Fleet Street in 1854; today, the news travels at nearly the speed of light, as data traverses fiber-optic cables. Thanks to that technology, the news channels have been on permanent Ebola watch for weeks now, despite the fact that, as the joke went on Twitter, more Americans have been married to Kim Kardashian than have died in the United States from Ebola.
As societies and technologies evolve, the velocities vary with which disease and information can spread. The tremendous population density of London in the 19th century enabled the cholera bacterium to spread through a neighborhood with terrifying speed, while the information about that terror moved more slowly. This was good news for the mental well-being of England’s wider population, which was spared the anxiety of following the death count as if it were a stock ticker. But it was terrible from a public health standpoint; the epidemic had largely faded before the official institutions of public health even realized the magnitude of the outbreak….
Information travels faster than viruses do now. This is why we are afraid. But this is also why we are safe.”
Privacy Identity Innovation: Innovator Spotlight
pii2014: “Every year, we invite a select group of startup CEOs to present their technologies on stage at Privacy Identity Innovation as part of the Innovator Spotlight program. This year’s conference (pii2014) is taking place November 12-14 in Silicon Valley, and we’re excited to announce that the following eight companies will be participating in the pii2014 Innovator Spotlight:
* BeehiveID – Led by CEO Mary Haskett, BeehiveID is a global identity validation service that enables trust by identifying bad actors online BEFORE they have a chance to commit fraud.
* Five – Led by CEO Nikita Bier, Five is a mobile chat app crafted around the experience of a house party. With Five, you can browse thousands of rooms and have conversations about any topic.
* Glimpse – Led by CEO Elissa Shevinsky, Glimpse is a private (disappearing) photo messaging app just for groups.
* Humin – Led by CEO Ankur Jain, Humin is a phone and contacts app designed to think about people the way you naturally do by remembering the context of your relationships and letting you search them the way you think.
* Kpass – Led by CEO Dan Nelson, Kpass is an identity platform that provides brands, apps and developers with an easy-to-implement technology solution to help manage the notice and consent requirements for the Children’s Online Privacy Protection Act (COPPA) laws.
* Meeco – Led by CEO Katryna Dow, Meeco is a Life Management Platform that offers an all-in-one solution for you to transact online, collect your own personal data, and be more anonymous with greater control over your own privacy.
* TrustLayers – Led by CEO Adam Towvim, TrustLayers is privacy intelligence for big data. TrustLayers enables confident use of personal data, keeping companies secure in the knowledge that the organization team is following the rules.
* Virtru – Led by CEO John Ackerly, Virtru is the first company to make email privacy accessible to everyone. With a single plug-in, Virtru empowers individuals and businesses to control who receives, reviews, and retains their digital information — wherever it travels, throughout its lifespan.
Learn more about the startups on the Innovator Spotlight page…”
Quantifying the Livable City
Brian Libby at City Lab: “By the time Constantine Kontokosta got involved with New York City’s Hudson Yards development, it was already on track to be historically big and ambitious.
Over the course of the next decade, developers from New York’s Related Companies and Canada-based Oxford Properties Group are building the largest real-estate development in United States history: a 28-acre neighborhood on Manhattan’s far West Side over a Long Island Rail Road yard, with some 17 million square feet of new commercial, residential, and retail space.
Hudson Yards is also being planned as an innovative model of efficiency. Its waste management systems, for example, will utilize a vast vacuum-tube system to collect garbage from each building into a central terminal, meaning no loud garbage trucks traversing the streets by night. Onsite power generation will prevent blackouts like those during Hurricane Sandy, and buildings will be connected through a micro-grid that allows them to share power with each other.
Yet it was Kontokosta, the deputy director of academics at New York University’s Center for Urban Science and Progress (CUSP), who conceived of Hudson Yards as what is now being called the nation’s first “quantified community.” This entails an unprecedentedly wide array of data being collected—not just on energy and water consumption, but real-time greenhouse gas emissions and airborne pollutants, measured with tools like hyper-spectral imagery.
New York has led the way in recent years with its urban data collection. In 2009, Mayor Michael Bloomberg signed Local Law 84, which requires privately owned buildings over 50,000 square feet in size to provide annual benchmark reports on their energy and water use. Unlike a LEED rating or similar, which declares a building green when it opens, the city benchmarking is a continuous assessment of its operations…”
The government wants to study ‘social pollution’ on Twitter
in the Washington Post: “If you take to Twitter to express your views on a hot-button issue, does the government have an interest in deciding whether you are spreading “misinformation’’? If you tweet your support for a candidate in the November elections, should taxpayer money be used to monitor your speech and evaluate your “partisanship’’?
My guess is that most Americans would answer those questions with a resounding no. But the federal government seems to disagree. The National Science Foundation , a federal agency whose mission is to “promote the progress of science; to advance the national health, prosperity and welfare; and to secure the national defense,” is funding a project to collect and analyze your Twitter data.
The project is being developed by researchers at Indiana University, and its purported aim is to detect what they deem “social pollution” and to study what they call “social epidemics,” including how memes — ideas that spread throughout pop culture — propagate. What types of social pollution are they targeting? “Political smears,” so-called “astroturfing” and other forms of “misinformation.”
Named “Truthy,” after a term coined by TV host Stephen Colbert, the project claims to use a “sophisticated combination of text and data mining, social network analysis, and complex network models” to distinguish between memes that arise in an “organic manner” and those that are manipulated into being.
But there’s much more to the story. Focusing in particular on political speech, Truthy keeps track of which Twitter accounts are using hashtags such as #teaparty and #dems. It estimates users’ “partisanship.” It invites feedback on whether specific Twitter users, such as the Drudge Report, are “truthy” or “spamming.” And it evaluates whether accounts are expressing “positive” or “negative” sentiments toward other users or memes…”
Chicago uses big data to save itself from urban ills
Aviva Rutkin in the New Scientist: “THIS year in Chicago, some kids will get lead poisoning from the paint or pipes in their homes. Some restaurants will cook food in unsanitary conditions and, here and there, a street corner will be suddenly overrun with rats. These kinds of dangers are hard to avoid in a city of more than 2.5 million people. The problem is, no one knows for certain where or when they will pop up.
The Chicago city government is hoping to change that by knitting powerful predictive models into its everyday city inspections. Its latest project, currently in pilot tests, analyses factors such as home inspection records and census data, and uses the results to guess which buildings are likely to cause lead poisoning in children – a problem that affects around 500,000 children in the US each year. The idea is to identify trouble spots before kids are exposed to dangerous lead levels.
“We are able to prevent problems instead of just respond to them,” says Jay Bhatt, chief innovation officer at the Chicago Department of Public Health. “These models are just the beginning of the use of predictive analytics in public health and we are excited to be at the forefront of these efforts.”
Chicago’s projects are based on the thinking that cities already have what they need to raise their municipal IQ: piles and piles of data. In 2012, city officials built WindyGrid, a platform that collected data like historical facts about buildings and up-to-date streams such as bus locations, tweets and 911 calls. The project was designed as a proof of concept and was never released publicly but it led to another, called Plenario, that allowed the public to access the data via an online portal.
The experience of building those tools has led to more practical applications. For example, one tool matches calls to the city’s municipal hotline complaining about rats with conditions that draw rats to a particular area, such as excessive moisture from a leaking pipe, or with an increase in complaints about garbage. This allows officials to proactively deploy sanitation crews to potential hotspots. It seems to be working: last year, resident requests for rodent control dropped by 15 per cent.
Some predictions are trickier to get right. Charlie Catlett, director of the Urban Center for Computation and Data in Chicago, is investigating an old axiom among city cops: that violent crime tends to spike when there’s a sudden jump in temperature. But he’s finding it difficult to test its validity in the absence of a plausible theory for why it might be the case. “For a lot of things about cities, we don’t have that underlying theory that tells us why cities work the way they do,” says Catlett.
Still, predictive modelling is maturing, as other cities succeed in using it to tackle urban ills….Such efforts can be a boon for cities, making them more productive, efficient and safe, says Rob Kitchin of Maynooth University in Ireland, who helped launched a real-time data site for Dublin last month called the Dublin Dashboard. But he cautions that there’s a limit to how far these systems can aid us. Knowing that a particular street corner is likely to be overrun with rats tomorrow doesn’t address what caused the infestation in the first place. “You might be able to create a sticking plaster or be able to manage it more efficiently, but you’re not going to be able to solve the deep structural problems….”
Traversing Digital Babel
New book by Alon Peled: “The computer systems of government agencies are notoriously complex. New technologies are piled on older technologies, creating layers that call to mind an archaeological dig. Obsolete programming languages and closed mainframe designs offer barriers to integration with other agency systems. Worldwide, these unwieldy systems waste billions of dollars, keep citizens from receiving services, and even—as seen in interoperability failures on 9/11 and during Hurricane Katrina—cost lives. In this book, Alon Peled offers a groundbreaking approach for enabling information sharing among public sector agencies: using selective incentives to “nudge” agencies to exchange information assets. Peled proposes the establishment of a Public Sector Information Exchange (PSIE), through which agencies would trade information.
After describing public sector information sharing failures and the advantages of incentivized sharing, Peled examines the U.S. Open Data program, and the gap between its rhetoric and results. He offers examples of creative public sector information sharing in the United States, Australia, Brazil, the Netherlands, and Iceland. Peled argues that information is a contested commodity, and draws lessons from the trade histories of other contested commodities—including cadavers for anatomical dissection in nineteenth-century Britain. He explains how agencies can exchange information as a contested commodity through a PSIE program tailored to an individual country’s needs, and he describes the legal, economic, and technical foundations of such a program. Touching on issues from data ownership to freedom of information, Peled offers pragmatic advice to politicians, bureaucrats, technologists, and citizens for revitalizing critical information flows.”
The Role Of Open Data In Choosing Neighborhood
PlaceILive Blog: “To what extent is it important to get familiar with our environment?
If we think about how the world surrounding us has changed throughout the years, it is not so unreasonable that, while walking to work, we might encounter some new little shops, restaurants, or gas stations we had never noticed before. Likewise, how many times did we wander about for hours just to find green spaces for a run? And the only one we noticed was even more polluted than other urban areas!
Citizens are not always properly informed about the evolution of the places they live in. And that is why it would be crucial for people to be constantly up-to-date with accurate information of the neighborhood they have chosen or are going to choose.
London is a neat evidence of how transparency in providing data is basic in order to succeed as a Smart City.
The GLA’s London Datastore, for instance, is a public platform of datasets revealing updated figures on the main services offered by the town, in addition to population’s lifestyle and environmental risks. These data are then made more easily accessible to the community through the London Dashboard.
The importance of dispensing free information can be also proved by the integration of maps, which constitute an efficient means of geolocation. Consulting a map where it’s easy to find all the services you need as close as possible can be significant in the search for a location.
(source: Smart London Plan)
The Open Data Index, published by The Open Knowledge Foundation in 2013, is another useful tool for data retrieval: it showcases a rank of different countries in the world with scores based on openness and availability of data attributes such as transport timetables and national statistics.
Here it is possible to check UK Open Data Census and US City Open Data Census.
As it was stated, making open data available and easily findable online not only represented a success for US cities but favoured apps makers and civic hackers too. Lauren Reid, a spokesperson at Code for America, reported according to Government Technology: “The more data we have, the better picture we have of the open data landscape.”
That is, on the whole, what Place I Live puts the biggest effort into: fostering a new awareness of the environment by providing free information, in order to support citizens willing to choose the best place they can live.
The outcome is soon explained. The website’s homepage offers visitors the chance to type address of their interest, displaying an overview of neighborhood parameters’ evaluation and a Life Quality Index calculated for every point on the map.
The research of the nearest medical institutions, schools or ATMs thus gets immediate and clear, as well as the survey about community’s generic information. Moreover, data’s reliability and accessibility are constantly examined by a strong team of professionals with high competence in data analysis, mapping, IT architecture and global markets.
For the moment the company’s work is focused on London, Berlin, Chicago, San Francisco and New York, while higher goals to reach include more than 200 cities.
US Open Data Census finally saw San Francisco’s highest score achievement as a proof of the city’s labour in putting technological expertise at everyone’s disposal, along with the task of fulfilling users’ needs through meticulous selections of datasets. This challenge seems to be successfully overcome by San Francisco’s new investment, partnering with the University of Chicago, in a data analytics dashboard on sustainability performance statistics named Sustainable Systems Framework, which is expected to be released in beta version by the the end of 2015’s first quarter.
Another remarkable collaboration in Open Data’s spread comes from the Bartlett Centre for Advanced Spatial Analysis (CASA) of the University College London (UCL); Oliver O’Brien, researcher at UCL Department of Geography and software developer at the CASA, is indeed one of the contributors to this cause.
Among his products, an interesting accomplishment is London’s CityDashboard, a real-time reports’ control panel in terms of spatial data. The web page also allows to visualize the whole data translated into a simplified map and to look at other UK cities’ dashboards.
Plus, his Bike Share Map is a live global view to bicycle sharing systems in over a hundred towns around the world, since bike sharing has recently drawn a greater public attention as an original form of transportation, in Europe and China above all….”