Twiplomacy Study 2014


Twiplomacy: “World leaders vie for attention, connections and followers on Twitter, that’s the latest finding of Burson-Marsteller’s Twiplomacy study 2014, an annual global study looking at the use of Twitter by heads of state and government and ministers of foreign affairs.
While some heads of state and government continue to amass large followings, foreign ministers have established a virtual diplomatic network by following each other on the social media platform.
For many diplomats Twitter has becomes a powerful channel for digital diplomacy and 21st century statecraft and not all Twitter exchanges are diplomatic, real world differences are spilling over reflected on Twitter and sometimes end up in hashtag wars.
“I am a firm believer in the power of technology and social media to communicate with people across the world,” India’s new Prime Minister Narendra Modi wrote in his inaugural message on his new website. Within weeks of his election in May 2014, the @NarendraModi account has moved into the top four most followed Twitter accounts of world leaders with close to five million followers.
More than half of the world’s foreign ministers and their institutions are active on the social networking site. Twitter has become an indispensable diplomatic networking and communication tool. As Finnish Prime Minister @AlexStubb wrote in a tweet in March 2014: “Most people who criticize Twitter are often not on it. I love this place. Best source of info. Great way to stay tuned and communicate.”
As of 25 June 2014, the vast majority (83 percent) of the 193 UN member countries have a presence on Twitter. More than two-thirds (68 percent) of all heads of state and heads of government have personal accounts on the social network.
As of 24 June 2014, the vast majority (83 percent) of the 193 UN member countries have a presence on Twitter. More than two-thirds (68 percent) of all heads of state and heads of government have personal accounts on the social network.

Most Followed World Leaders

Since his election in late May 2014, India’s new Prime Minister @NarendraModi has skyrocketed into fourth place, surpassing the the @WhiteHouse on 25 June 2014 and dropping Turkey’s President Abdullah Gül (@cbabdullahgul) and Prime Minister Recep Tayyip Erdoğan (@RT_Erdogan) into sixth and seventh place with more than 4 million followers each.
Twiplomacy - Top 50 Most Followed
Modi still has a ways to go to best U.S. President @BarackObama, who tops the world-leader list with a colossal 43.7 million followers, with Pope Francis @Pontifex) with 14 million followers on his nine different language accounts and Indonesia’s President Susilo Bambang Yudhoyono @SBYudhoyono, who has more than five million followers and surpassed President Obama’s official administration account @WhiteHouse on 13 February 2014.
In Latin America Cristina Fernández de Kirchner, the President of Argentina @CFKArgentina is slightly ahead of Colombia’s President @JuanManSantos with 2,894,864 and 2,885,752 followers respectively. Mexico’s President Enrique Peña Nieto @EPN, Brazil’s Dilma Rousseff @dilmabr and Venezuela’s @NicolasMaduro complete the Latin American top five, with more than two million followers each.
Kenya’s Uhuru Kenyatta @UKenyatta is Africa’s most followed president with 457,307 followers, ahead of Rwanda’s @PaulKagame (407,515 followers) and South Africa’s Jacob Zuma (@SAPresident) (325,876 followers).
Turkey’s @Ahmet_Davutoglu is the most followed foreign minister with 1,511,772 followers, ahead of India’s @SushmaSwaraj (1,274,704 followers) and the Foreign Minister of the United Arab Emirates @ABZayed (1,201,364 followers)…”

We Need a Citizen Maker Movement


Lorelei Kelly at the Huffington Post: “It was hard to miss the giant mechanical giraffe grazing on the White House lawn last week. For the first time ever, the President organized a Maker Faire–inviting entrepreneurs and inventors from across the USA to celebrate American ingenuity in the service of economic progress.
The maker movement is a California original. Think R2D2 serving margaritas to a jester with an LED news scroll. The #nationofmakers Twitter feed has dozens of examples of collaborative production, of making, sharing and learning.
But since this was the White House, I still had to ask myself, what would the maker movement be if the economy was not the starting point? What if it was about civics? What if makers decided to create a modern, hands-on democracy?
What is democracy anyway but a never ending remix of new prototypes? Last week’s White House Maker Faire heralded a new economic bonanza. This revolution’s poster child is 3-D printing– decentralized fabrication that is customized to meet local needs. On the government front, new design rules for democracy are already happening in communities, where civics and technology have generated a front line of maker cities.
But the distance between California’s tech capacity and DC does seem 3000 miles wide. The NSA’s over collection/surveillance problem and Healthcare.gov’s doomed rollout are part of the same system-wide capacity deficit. How do we close the gap between California’s revolution and our institutions?

  • In California, disruption is a business plan. In DC, it’s a national security threat.
  • In California, hackers are artists. In DC, they are often viewed as criminals.
  • In California, “cyber” is a dystopian science fiction word. In DC, cyber security is in a dozen oversight plans for Congress.
  • in California, individuals are encouraged to “fail forward.” In DC, risk-aversion is bipartisan.

Scaling big problems with local solutions is a maker specialty. Government policymaking needs this kind of help.
Here’s the issue our nation is facing: The inability of the non-military side of our public institutions to process complex problems. Today, this competence and especially the capacity to solve technical challenges often exist only in the private sector. If something is urgent and can’t be monetized, it becomes a national security problem. Which increasingly means that critical decision making that should be in the civilian remit instead migrates to the military. Look at our foreign policy. Good government is a counter terrorism strategy in Afghanistan. Decades of civilian inaction on climate change means that now Miami is referred to as a battle space in policy conversations.
This rhetoric reflects an understandable but unacceptable disconnect for any democracy.
To make matters more confusing, much of the technology in civics (like list building petitions) is suited for elections, not for governing. It is often antagonistic. The result? policy making looks like campaigning. We need some civic tinkering to generate governing technology that comes with relationships. Specifically, this means technology that includes many voices, but has identifiable channels for expertise that can sort complexity and that is not compromised by financial self-interest.
Today, sorting and filtering information is a huge challenge for participation systems around the world. Information now ranks up there with money and people as a lever of power. On the people front, the loud and often destructive individuals are showing up effectively. On the money front, our public institutions are at risk of becoming purely pay to play (wonks call this “transactional”).
Makers, ask yourselves, how can we turn big data into a political constituency for using real evidence–one that can compete with all the negative noise and money in the system? For starters, technologists out West must stop treating government like it’s a bad signal that can be automated out of existence. We are at a moment where our society requires an engineering mindset to develop modern, tech-savvy rules for democracy. We need civic makers….”

Towards a comparative science of cities: using mobile traffic records in New York, London and Hong Kong


Book chapter by S. Grauwin, S. Sobolevsky, S. Moritz, I. Gódor, C. Ratti, to be published in “Computational Approaches for Urban Environments” (Springer Ed.), October 2014: “This chapter examines the possibility to analyze and compare human activities in an urban environment based on the detection of mobile phone usage patterns. Thanks to an unprecedented collection of counter data recording the number of calls, SMS, and data transfers resolved both in time and space, we confirm the connection between temporal activity profile and land usage in three global cities: New York, London and Hong Kong. By comparing whole cities typical patterns, we provide insights on how cultural, technological and economical factors shape human dynamics. At a more local scale, we use clustering analysis to identify locations with similar patterns within a city. Our research reveals a universal structure of cities, with core financial centers all sharing similar activity patterns and commercial or residential areas with more city-specific patterns. These findings hint that as the economy becomes more global, common patterns emerge in business areas of different cities across the globe, while the impact of local conditions still remains recognizable on the level of routine people activity.”

Index: The Networked Public


The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on the networked public and was originally published in 2014.

Global Overview

  • The proportion of global population who use the Internet in 2013: 38.8%, up 3 percentage points from 2012
  • Increase in average global broadband speeds from 2012 to 2013: 17%
  • Percent of internet users surveyed globally that access the internet at least once a day in 2012: 96
  • Hours spent online in 2012 each month across the globe: 35 billion
  • Country with the highest online population, as a percent of total population in 2012: United Kingdom (85%)
  • Country with the lowest online population, as a percent of total population in 2012: India (8%)
  • Trend with the highest growth rate in 2012: Location-based services (27%)
  • Years to reach 50 million users: telephone (75), radio (38), TV (13), internet (4)

Growth Rates in 2014

  • Rate at which the total number of Internet users is growing: less than 10% a year
  • Worldwide annual smartphone growth: 20%
  • Tablet growth: 52%
  • Mobile phone growth: 81%
  • Percentage of all mobile users who are now smartphone users: 30%
  • Amount of all web usage in 2013 accounted for by mobile: 14%
  • Amount of all web usage in 2014 accounted for by mobile: 25%
  • Percentage of money spent on mobile used for app purchases: 68%
  • Growth of BitCoin wallet between 2013 and 2014: 8 times increase
  • Number of listings on AirBnB in 2014: 550k, 83% growth year on year
  • How many buyers are on Alibaba in 2014: 231MM buyers, 44% growth year on year

Social Media

  • Number of Whatsapp messages on average sent per day: 50 billion
  • Number sent per day on Snapchat: 1.2 billion
  • How many restaurants are registered on GrubHub in 2014: 29,000
  • Amount the sale of digital songs fell in 2013: 6%
  • How much song streaming grew in 2013: 32%
  • Number of photos uploaded and shared every day on Flickr, Snapchat, Instagram, Facebook and Whatsapp combined in 2014: 1.8 billion
  • How many online adults in the U.S. use a social networking site of some kind: 73%
  • Those who use multiple social networking sites: 42%
  • Dominant social networking platform: Facebook, with 71% of online adults
  • Number of Facebook users in 2004, its founding year: 1 million
  • Number of monthly active users on Facebook in September 2013: 1.19 billion, an 18% increase year-over-year
  • How many Facebook users log in to the site daily: 63%
  • Instagram users who log into the service daily: 57%
  • Twitter users who are daily visitors: 46%
  • Number of photos uploaded to Facebook every minute: over 243,000, up 16% from 2012
  • How much of the global internet population is actively using Twitter every month: 21%
  • Number of tweets per minute: 350,000, up 250% from 2012
  • Fastest growing demographic on Twitter: 55-64 year age bracket, up 79% from 2012
  • Fastest growing demographic on Facebook: 45-54 year age bracket, up 46% from 2012
  • How many LinkedIn accounts are created every minute: 120, up 20% from 2012
  • The number of Google searches in 2013: 3.5 million, up 75% from 2012
  • Percent of internet users surveyed globally that use social media in 2012: 90
  • Percent of internet users surveyed globally that use social media daily: 60
  • Time spent social networking, the most popular online activity: 22%, followed by searches (21%), reading content (20%), and emails/communication (19%)
  • The average age at which a child acquires an online presence through their parents in 10 mostly Western countries: six months
  • Number of children in those countries who have a digital footprint by age 2: 81%
  • How many new American marriages between 2005-2012 began by meeting online, according to a nationally representative study: more than one-third 
  • How many of the world’s 505 leaders are on Twitter: 3/4
  • Combined Twitter followers: of 505 world leaders: 106 million
  • Combined Twitter followers of Justin Bieber, Katy Perry, and Lady Gaga: 122 million
  • How many times all Wikipedias are viewed per month: nearly 22 billion times
  • How many hits per second: more than 8,000 
  • English Wikipedia’s share of total page views: 47%
  • Number of articles in the English Wikipedia in December 2013: over 4,395,320 
  • Platform that reaches more U.S. adults between ages 18-34 than any cable network: YouTube
  • Number of unique users who visit YouTube each month: more than 1 billion
  • How many hours of video are watched on YouTube each month: over 6 billion, 50% more than 2012
  • Proportion of YouTube traffic that comes from outside the U.S.: 80%
  • Most common activity online, based on an analysis of over 10 million web users: social media
  • People on Twitter who recommend products in their tweets: 53%
  • People who trust online recommendations from people they know: 90%

Mobile and the Internet of Things

  • Number of global smartphone users in 2013: 1.5 billion
  • Number of global mobile phone users in 2013: over 5 billion
  • Percent of U.S. adults that have a cell phone in 2013: 91
  • Number of which are a smartphone: almost two thirds
  • Mobile Facebook users in March 2013: 751 million, 54% increase since 2012
  • Growth rate of global mobile traffic as a percentage of global internet traffic as of May 2013: 15%, up from .9% in 2009
  • How many smartphone owners ages 18–44 “keep their phone with them for all but two hours of their waking day”: 79%
  • Those who reach for their smartphone immediately upon waking up: 62%
  • Those who couldn’t recall a time their phone wasn’t within reach or in the same room: 1 in 4
  • Facebook users who access the service via a mobile device: 73.44%
  • Those who are “mobile only”: 189 million
  • Amount of YouTube’s global watch time that is on mobile devices: almost 40%
  • Number of objects connected globally in the “internet of things” in 2012: 8.7 billion
  • Number of connected objects so far in 2013: over 10 billion
  • Years from tablet introduction for tables to surpass desktop PC and notebook shipments: less than 3 (over 55 million global units shipped in 2013, vs. 45 million notebooks and 35 million desktop PCs)
  • Number of wearable devices estimated to have been shipped worldwide in 2011: 14 million
  • Projected number of wearable devices in 2016: between 39-171 million
  • How much of the wearable technology market is in the healthcare and medical sector in 2012: 35.1%
  • How many devices in the wearable tech market are fitness or activity trackers: 61%
  • The value of the global wearable technology market in 2012: $750 million
  • The forecasted value of the market in 2018: $5.8 billion
  • How many Americans are aware of wearable tech devices in 2013: 52%
  • Devices that have the highest level of awareness: wearable fitness trackers,
  • Level of awareness for wearable fitness trackers amongst American consumers: 1 in 3 consumers
  • Value of digital fitness category in 2013: $330 million
  • How many American consumers surveyed are aware of smart glasses: 29%
  • Smart watch awareness amongst those surveyed: 36%

Access

  • How much of the developed world has mobile broadband subscriptions in 2013: 3/4
  • How much of the developing world has broadband subscription in 2013: 1/5
  • Percent of U.S. adults that had a laptop in 2012: 57
  • How many American adults did not use the internet at home, at work, or via mobile device in 2013: one in five
  • Amount President Obama initiated spending in 2009 in an effort to expand access: $7 billion
  • Number of Americans potentially shut off from jobs, government services, health care and education, among other opportunities due to digital inequality: 60 million
  • American adults with a high-speed broadband connection at home as of May 2013: 7 out of 10
  • Americans aged 18-29 vs. 65+ with a high-speed broadband connection at home as of May 2013: 80% vs. 43
  • American adults with college education (or more) vs. adults with no high school diploma that have a high-speed broadband connection at home as of May 2013: 89% vs. 37%
  • Percent of U.S. adults with college education (or more) that use the internet in 2011: 94
  • Those with no high school diploma that used the internet in 2011: 43
  • Percent of white American households that used the internet in 2013: 67
  • Black American households that used the internet in 2013: 57
  • States with lowest internet use rates in 2013: Mississippi, Alabama and Arkansas
  • How many American households have only wireless telephones as of the second half of 2012: nearly two in five
  • States with the highest prevalence of wireless-only adults according to predictive modeling estimates: Idaho (52.3%), Mississippi (49.4%), Arkansas (49%)
  • Those with the lowest prevalence of wireless-only adults: New Jersey (19.4%), Connecticut (20.6%), Delaware (23.3%) and New York (23.5%)

Sources

App pays commuters to take routes that ease congestion


Springwise: “Congestion at peak hours is a major problem in the world’s busiest city centres. We’ve recently seen Gothenburg in Sweden offering free bicycles to ease the burden on public transport services, but now a new app is looking to take a different approach to the same problem. Urban Engines uses algorithms to help cities determine key congestion choke points and times, and can then reward commuters for avoiding them.
The Urban Engines system is based on commuters using the smart commuter cards already found in many major cities. The company tracks journeys made with those commuter cards, and uses that data to identify main areas of congestion, and at what times the congestion occurs. The system has already been employed in Washington, D.C, and Sao Paulo, Brazil, helping provide valuable data for work with city planners.
It’s in Singapore, however, where the most interesting work has been achieved so far. There, commuters who have signed up and registered their commuter cards can earn rewards when they travel. They will earn one point for every kilometre travelled during peak hours, or triple that when travelling off-peak. The points earned can then be converted into discounts on future journeys, or put towards an in-app raffle game, where they have the opportunity to win sums of money. Urban Engines claim there’s been a 7 to 13 percent reduction in journeys made during peak hours, with 200,000 commuters taking part.
The company is based on an original experiment carried out in Bangalore. The rewards program there, carried out among 20,000 employees of the Indian company Infosys, lead to 17 percent of traffic shifting to off-peak travel times in six months. A similarly successful experiment has also been carried out on the Stanford University campus, and the plan is to now expand to other major cities…”

New Book on 25 Years of Participatory Budgeting


Tiago Peixoto at Democracy Spot: “A little while ago I mentioned the launch of the Portuguese version of the book organized by Nelson Dias, “Hope for Democracy: 25 Years of Participatory Budgeting Worldwide”.

The good news is that the English version is finally out. Here’s an excerpt from the introduction:

This book represents the effort  of more than forty authors and many other direct and indirect contributions that spread across different continents seek to provide an overview on the Participatory Budgeting (PB) in the World. They do so from different backgrounds. Some are researchers, others are consultants, and others are activists connected to several groups and social movements. The texts reflect this diversity of approaches and perspectives well, and we do not try to influence that.
(….)
The pages that follow are an invitation to a fascinating journey on the path of democratic innovation in very diverse cultural, political, social and administrative settings. From North America to Asia, Oceania to Europe, from Latin America to Africa, the reader will find many reasons to closely follow the proposals of the different authors.

The book can be downloaded here [PDF]. I had the pleasure of being one of the book’s contributors, co-authoring an article with Rafael Sampaio on the use of ICT in PB processes: “Electronic Participatory Budgeting: False Dilemmas and True Complexities” [PDF]...”

The Emerging Science of Computational Anthropology


Emerging Technology From the arXiv: The increasing availability of big data from mobile phones and location-based apps has triggered a revolution in the understanding of human mobility patterns. This data shows the ebb and flow of the daily commute in and out of cities, the pattern of travel around the world and even how disease can spread through cities via their transport systems.
So there is considerable interest in looking more closely at human mobility patterns to see just how well it can be predicted and how these predictions might be used in everything from disease control and city planning to traffic forecasting and location-based advertising.
Today we get an insight into the kind of detailed that is possible thanks to the work of Zimo Yang at Microsoft research in Beijing and a few pals. These guys start with the hypothesis that people who live in a city have a pattern of mobility that is significantly different from those who are merely visiting. By dividing travelers into locals and non-locals, their ability to predict where people are likely to visit dramatically improves.
Zimo and co begin with data from a Chinese location-based social network called Jiepang.com. This is similar to Foursquare in the US. It allows users to record the places they visit and to connect with friends at these locations and to find others with similar interests.
The data points are known as check-ins and the team downloaded more than 1.3 million of them from five big cities in China: Beijing, Shanghai, Nanjing, Chengdu and Hong Kong. They then used 90 per cent of the data to train their algorithms and the remaining 10 per cent to test it. The Jiapang data includes the users’ hometowns so it’s easy to see whether an individual is checking in in their own city or somewhere else.
The question that Zimo and co want to answer is the following: given a particular user and their current location, where are they most likely to visit in the near future? In practice, that means analysing the user’s data, such as their hometown and the locations recently visited, and coming up with a list of other locations that they are likely to visit based on the type of people who visited these locations in the past.
Zimo and co used their training dataset to learn the mobility pattern of locals and non-locals and the popularity of the locations they visited. The team then applied this to the test dataset to see whether their algorithm was able to predict where locals and non-locals were likely to visit.
They found that their best results came from analysing the pattern of behaviour of a particular individual and estimating the extent to which this person behaves like a local. That produced a weighting called the indigenization coefficient that the researchers could then use to determine the mobility patterns this person was likely to follow in future.
In fact, Zimo and co say they can spot non-locals in this way without even knowing their home location. “Because non-natives tend to visit popular locations, like the Imperial Palace in Beijing and the Bund in Shanghai, while natives usually check in around their homes and workplaces,” they add.
The team say this approach considerably outperforms the mixed algorithms that use only individual visiting history and location popularity. “To our surprise, a hybrid algorithm weighted by the indigenization coefficients outperforms the mixed algorithm accounting for additional demographical information.”
It’s easy to imagine how such an algorithm might be useful for businesses who want to target certain types of travelers or local people. But there is a more interesting application too.
Zimo and co say that it is possible to monitor the way an individual’s mobility patterns change over time. So if a person moves to a new city, it should be possible to see how long it takes them to settle in.
One way of measuring this is in their mobility patterns: whether they are more like those of a local or a non-local. “We may be able to estimate whether a non-native person will behave like a native person after a time period and if so, how long in average a person takes to become a native-like one,” say Zimo and co.
That could have a fascinating impact on the way anthropologists study migration and the way immigrants become part of a local community. This is computational anthropology a science that is clearly in its early stages but one that has huge potential for the future.”
Ref: arxiv.org/abs/1405.7769 : Indigenization of Urban Mobility

Humanitarians in the sky


Patrick Meier in the Guardian: “Unmanned aerial vehicles (UAVs) capture images faster, cheaper, and at a far higher resolution than satellite imagery. And as John DeRiggi speculates in “Drones for Development?” these attributes will likely lead to a host of applications in development work. In the humanitarian field that future is already upon us — so we need to take a rights-based approach to advance the discussion, improve coordination of UAV flights, and to promote regulation that will ensure safety while supporting innovation.
It was the unprecedentedly widespread use of civilian UAVs following typhoon Haiyan in the Philippines that opened my eyes to UAV use in post-disaster settings. I was in Manila to support the United Nations’ digital humanitarian efforts and came across new UAV projects every other day.
One team was flying rotary-wing UAVs to search for survivors among vast fields of debris that were otherwise inaccessible. Another flew fixed-wing UAVs around Tacloban to assess damage and produce high-quality digital maps. Months later, UAVs are still being used to support recovery and preparedness efforts. One group is working with local mayors to identify which communities are being overlooked in the reconstruction.
Humanitarian UAVs are hardly new. As far back as 2007, the World Food Program teamed up with the University of Torino to build humanitarian UAVs. But today UAVs are much cheaper, safer, and easier to fly. This means more people own personal UAVs. The distinguishing feature between these small UAVs and traditional remote control airplanes or helicopters is that they are intelligent. Most can be programmed to fly and land autonomously at designated locations. Newer UAVs also have on-board, flight-stabilization features that automatically adapt to changing winds, automated collision avoidance systems, and standard fail-safe mechanisms.
While I was surprised by the surge in UAV projects in the Philippines, I was troubled that none of these teams were aware of each other and that most were apparently not sharing their imagery with local communities. What happens when even more UAV teams show up following future disasters? Will they be accompanied by droves of drone journalists and “disaster tourists” equipped with personal UAVs? Will we see thousands of aerial disaster pictures and videos uploaded to social media rather than in the hands of local communities? What are the privacy implications? And what about empowering local communities to deploy their own UAVs?
There were many questions but few answers. So I launched the humanitarian UAV network (UAViators) to bridge the worlds of humanitarian professionals and UAV experts to address these questions. Our first priority was to draft a code of conduct for the use of UAVs in humanitarian settings to hold ourselves accountable while educating new UAV pilots before serious mistakes are made…”

Making cities smarter through citizen engagement


Vaidehi Shah at Eco-Business: “Rapidly progressing information communications technology (ICT) is giving rise to an almost infinite range of innovations that can be implemented in cities to make them more efficient and better connected. However, in order for technology to yield sustainable solutions, planners must prioritise citizen engagement and strong leadership.
This was the consensus on Tuesday at the World Cities Summit 2014, where representatives from city and national governments, technology firms and private sector organisations gathered in Singapore to discuss strategies and challenges to achieving sustainable cities in the future.
Laura Ipsen, Microsoft corporate vice president for worldwide public sector, identified globalisation, social media, big data, and mobility as the four major technological trends prevailing in cities today, as she spoke at the plenary session with a theme on “The next urban decade: critical challenges and opportunities”.
Despite these increasing trends, she cautioned, “technology does not build infrastructure, but it does help better engage citizens and businesses through public-private partnerships”.
For example, “LoveCleanStreets”, an online tool developed by Microsoft and partners, enables London residents to report infrastructure problems such as damaged roads or signs, shared Ipsen.
“By engaging citizens through this application, cities can fix problems early, before they get worse,” she said.
In Singapore, the ‘MyWaters’ app of PUB, Singapore’s national water agency, is also a key tool for the government to keep citizens up-to-date of water quality and safety issues in the country, she added.
Even if governments did not actively develop solutions themselves, simply making the immense amounts of data collected by the city open to businesses and citizens could make a big difference to urban liveability, Mark Chandler, director of the San Francisco Mayor’s Office of International Trade and Commerce, pointed out.
Opening up all of the data collected by San Francisco, for instance, yielded 60 free mobile applications that allow residents to access urban solutions related to public transport, parking, and electricity, among others, he explained. This easy and convenient access to infrastructure and amenities, which are a daily necessity, is integral to “a quality of life that keeps the talented workforce in the city,” Chandler said….”

Twitter releasing trove of user data to scientists for research


Joe Silver at ArsTechnica: “Twitter has a 200-million-strong and ever-growing user base that broadcasts 500 million updates daily. It has been lauded for its ability to unsettle repressive political regimes, bring much-needed accountability to corporations that mistreat their customers, and combat other societal ills (whether such characterizations are, in fact, accurate). Now, the company has taken aim at disrupting another important sphere of human society: the scientific research community.
Back in February, the site announced its plan—in collaboration with Gnip—to provide a handful of research institutions with free access to its data sets from 2006 to the present. It’s a pilot program called “Twitter Data Grants,” with the hashtag #DataGrants. At the time, Twitter’s engineering blog explained the plan to enlist grant applications to access its treasure trove of user data:

Twitter has an expansive set of data from which we can glean insights and learn about a variety of topics, from health-related information such as when and where the flu may hit to global events like ringing in the new year. To date, it has been challenging for researchers outside the company who are tackling big questions to collaborate with us to access our public, historical data. Our Data Grants program aims to change that by connecting research institutions and academics with the data they need.

In April, Twitter announced that, after reviewing the more than 1,300 proposals submitted from more than 60 different countries, it had selected six institutions to provide with data access. Projects approved included a study of foodborne gastrointestinal illnesses, a study measuring happiness levels in cities based on images shared on Twitter, and a study using geosocial intelligence to model urban flooding in Jakarta, Indonesia. There’s even a project exploring the relationship between tweets and sports team performance.
Twitter did not directly respond to our questions on Tuesday afternoon regarding the specific amount and types of data the company is providing to the six institutions. But in its privacy policy, Twitter explains that most user information is intended to be broadcast widely. As a result, the company likely believes that sharing such information with scientific researchers is well within its rights, as its services “are primarily designed to help you share information with the world,” Twitter says. “Most of the information you provide us is information you are asking us to make public.”
While mining such data sets will undoubtedly aid scientists in conducting experiments for which similar data was previously either unavailable or quite limited, these applications raise some legal and ethical questions. For example, Scientific American has asked whether Twitter will be able to retain any legal rights to scientific findings and whether mining tweets (many of which are not publicly accessible) for scientific research when Twitter users have not agreed to such uses is ethically sound.
In response, computational epidemiologists Caitlin Rivers and Bryan Lewis have proposed guidelines for ethical research practices when using social media data, such as avoiding personally identifiable information and making all the results publicly available….”