Richard Waters in the Financial Times: “There is much to be lost if companies and nations put up fences around our digital open plains
For all the drawbacks, it is not hard to feel nostalgic about the early days of the web. Surfing between slow-loading, badly designed sites on a dial-up internet connection running at 56 kilobits per second could be frustrating. No wonder it was known as the “world wide wait”. But the “wow” factor was high. There was unparalleled access to free news and information, even if some of it was deeply untrustworthy. Then came that first, revelatory search on Google, which untangled the online jumble with almost miraculous speed.
Later, an uproarious outbreak of blogs converted what had been a passive medium into a global rant. And, with YouTube and Facebook, a mass audience found digital self-expression for the first time.
As the world wide web turns 25, it is easy to take all this for granted. For a generation that has grown up digital, it is part of the fabric of life.
It is also easy to turn away without too many qualms. More than 80 per cent of time spent on smartphones and tablets does not involve the web at all: it is whiled away in apps, which offer the instant gratification that comes from a tap or swipe of a finger.
Typing a URL on a small device, trying to stretch or shrink a web page to fit the small screen, browsing through Google links in a mobile browser: it is all starting to seem so, well, anachronistic.
But if the world wide web is coming to play a smaller part in everyday life, the significance of its relative decline should be kept in perspective. After all, the web is only one of the applications that rides on top of the internet: it is the standards and technologies of the internet itself that provide the main foundation for the modern, connected world. As long as all bits flow freely (and cheaply), the promise of the digital age will remain intact.
Before declaring the web era over and moving on, however, it is worth dwelling on what it represents – and what could be lost if this early manifestation of digital life were to be consigned to history.
Sir Tim Berners-Lee, who wrote the technical paper a quarter of a century ago that laid out the architecture of the web, certainly senses the threat. The open technical standards and open access that lie at the heart of the web – based on the freedom to link any online document to any other – are not guaranteed. What is needed, he argued this week, is nothing less than a digital bill of rights: a statement that would enshrine the ideals on which the medium was founded.
As this suggests, the web has always been much more than a technology. It is a state of mind, a dream of participation, a call to digital freedom that transcends geography. What place it finds in the connected world of tomorrow will help define what it means to be a digital citizen…”
Open Data is a Civil Right
Yo Yoshida, Founder & CEO, Appallicious in GovTech: “As Americans, we expect a certain standardization of basic services, infrastructure and laws — no matter where we call home. When you live in Seattle and take a business trip to New York, the electric outlet in the hotel you’re staying in is always compatible with your computer charger. When you drive from San Francisco to Los Angeles, I-5 doesn’t all-of-a-sudden turn into a dirt country road because some cities won’t cover maintenance costs. If you take a 10-minute bus ride from Boston to the city of Cambridge, you know the money in your wallet is still considered legal tender.
But what if these expectations of consistency were not always a given? What if cities, counties and states had absolutely zero coordination when it came to basic services? This is what it is like for us in the open data movement. There are so many important applications and products that have been built by civic startups and concerned citizens. However, all too often these efforts are confided to city limits, and unavailable to anyone outside of them. It’s time to start reimagining the way cities function and how local governments operate. There is a wealth of information housed in local governments that should be public by default to help fuel a new wave of civic participation.
Appallicious’ Neighborhood Score provides an overall health and sustainability score, block-by-block for every neighborhood in the city of San Francisco. The first time metrics have been applied to neighborhoods so we can judge how government allocates our resources, so we can better plan how to move forward. But, if you’re thinking about moving to Oakland, just a subway stop away from San Francisco and want to see the score for a neighborhood, our app can’t help you, because that city has yet to release the data sets we need.
In Contra Costa County, there is the lifesaving PulsePoint app, which notifies smartphone users who are trained in CPR when someone nearby may be in need of help. This is an amazing app—for residents of Contra Costa County. But if someone in neighboring Alameda County needs CPR, the app, unfortunately, is completely useless.
Buildingeye visualizes planning and building permit data to allow users to see what projects are being proposed in their area or city. However, buildingeye is only available in a handful of places, simply because most cities have yet to make permits publicly available. Think about what this could do for the construction sector — an industry that has millions of jobs for Americans. Buildingeye also gives concerned citizens access to public documents like never before, so they can see what might be built in their cities or on their streets.
Along with other open data advocates, I have been going from city-to-city, county-to-county and state-to-state, trying to get governments and departments to open up their massive amounts of valuable data. Each time one city, or one county, agrees to make their data publicly accessible, I can’t help but think it’s only a drop in the bucket. We need to think bigger.
Every government, every agency and every department in the country that has already released this information to the public is a case study that points to the success of open data — and why every public entity should follow their lead. There needs to be a national referendum that instructs that all government data should be open and accessible to the public.
Last May, President Obama issued an executive order requiring that going forward, any data generated by the federal government must be made available to the public in open, machine-readable formats. In the executive order, Obama stated that, “openness in government strengthens our democracy, promotes the delivery of efficient and effective services to the public, and contributes to economic growth.”
If this is truly the case, Washington has an obligation to compel local and state governments to release their data as well. Many have tried to spur this effort. California Lt. Gov. Gavin Newsom created the Citizenville Challenge to speed up adoption on the local level. The U.S. Conference of Mayors has also been vocal in promoting open data efforts. But none of these initiatives could have the same effect of a federal mandate.
What I am proposing is no small feat, and it won’t happen overnight. But there should be a concerted effort by those in the technology industry, specifically civic startups, to call on Congress to draft legislation that would require every city in the country to make their data open, free and machine readable. Passing federal legislation will not be an easy task — but creating a “universal open data” law is possible. It would require little to no funding, and it is completely nonpartisan. It’s actually not a political issue at all; it is, for lack of a better word, and administrative issue.
Often good legislation is blocked because lawmakers and citizens are concerned about project funding. While there should be support to help cities and towns achieve the capability of opening their data, a lot of the time, they don’t need it. In 2009, the city and county of San Francisco opened up its data with zero dollars. Many other cities have done the same. There will be cities and municipalities that will need financial assistance to accomplish this. But it is worth it, and it will not require a significant investment for a substantial return. There are free online open data portals, like ckan, dkan and a new effort from Accela, CivicData.com, to centralize open data efforts.
When the UK Government recently announced a £1.5 million investment to support open data initiatives, its Cabinet Office Minister said, “We know that it creates a more accountable, efficient and effective government. Open Data is a raw material for economic growth, supporting the creation of new markets, business and jobs and helping us compete in the global race.”
We should not fall behind these efforts. There is too much at stake for our citizens, not to mention our economy. A recent McKinsey report found that making open data has the potential to create $3 trillion in value worldwide.
Former Speaker Tip O’Neil famously said, “all politics are local.” But we in the civic startup space believe all data is local. Data is reporting potholes in your neighborhood and identifying high crime areas in your communities. It’s seeing how many farmers’ markets there are in your town compared to liquor stores. Data helps predict which areas of a city are most at risk during a heat wave and other natural disasters. A federal open data law would give the raw material needed to create tools to improve the lives of all Americans, not just those who are lucky enough to live in a city that has released this information on its own.
It’s a different way of thinking about how a government operates and the relationship it has with its citizens. Open data gives the public an amazing opportunity to be more involved with governmental decisions. We can increase accountability and transparency, but most importantly we can revolutionize the way local residents communicate and work with their government.
Access to this data is a civil right. If this is truly a government by, of and for the people, then its data needs to be available to all of us. By opening up this wealth of information, we will design a better government that takes advantage of the technology and skills of civic startups and innovative citizens….”
Social Media as Government Watchdog
Gordon Crovitz in the Wall Street Journal: “Two new data points for the debate on whether greater access to the Internet leads to more freedom and fewer authoritarian regimes:
According to reports last week, Facebook plans to buy a company that makes solar-powered drones that can hover for years at high altitudes without refueling, which it would use to bring the Internet to parts of the world not yet on the grid. In contrast to this futuristic vision, Russia evoked land grabs of the analog Soviet era by invading Crimea after Ukrainians forced out Vladimir Putin‘s ally as president.
Internet idealists can point to another triumph in helping bring down Ukraine’s authoritarian government. Ukrainian citizens ignored intimidation including officious text messages: “Dear subscriber, you are registered as a participant in a mass disturbance.” Protesters made the most of social media to plan demonstrations and avoid attacks by security forces.
But Mr. Putin quickly delivered the message that social media only goes so far against a fully committed authoritarian. His claim that he had to invade to protect ethnic Russians in Crimea was especially brazen because there had been no loud outcry, on social media or otherwise, among Russian speakers in the region.
A new book reports the state of play on the Internet as a force for freedom. For a decade, Emily Parker, a former Wall Street Journal editorial-page writer and State Department staffer, has researched the role of the Internet in China, Cuba and Russia. The title of her book, “Now I Know Who My Comrades Are,” comes from a blogger in China who explained to Ms. Parker how the Internet helps people discover they are not alone in their views and aspirations for liberty.
Officials in these countries work hard to keep critics isolated and in fear. In Russia, Ms. Parker notes, there is also apathy because the Putin regime seems so entrenched. “Revolutions need a spark, often in the form of a political or economic crisis,” she observes. “Social media alone will not light that spark. What the Internet does create is a new kind of citizen: networked, unafraid, and ready for action.”
Asked about lessons from the invasion of Crimea, Ms. Parker noted that the Internet “chips away at Russia’s control over information.” She added: “Even as Russian state media tries to shape the narrative about Ukraine, ordinary Russians can go online to seek the truth.”
But this same shared awareness may also be accelerating a decline in U.S. influence. In the digital era, U.S. failure to make good on its promises reduces the stature of Washington faster than similar inaction did in the past.
Consider the Hungarian uprising of 1956, the first significant rebellion against Soviet control. The U.S. secretary of state, John Foster Dulles, said: “To all those suffering under communist slavery, let us say you can count on us.” Yet no help came as Soviet tanks rolled into Budapest, tens of thousands were killed, and the leader who tried to secede from the Warsaw Pact, Imre Nagy, was executed.
There were no Facebook posts or YouTube videos instantly showing the result of U.S. fecklessness. In the digital era, scenes of Russian occupation of Crimea are available 24/7. People can watch Mr. Putin’s brazen press conferences and see for themselves what he gets away with.
The U.S. stood by as Syrian civilians were massacred and gassed. There was instant global awareness when President Obama last year backed down from enforcing his “red line” when the Syrian regime used chemical weapons. American inaction in Syria sent a green light for Mr. Putin and others around the world to act with impunity.
Just in recent weeks, Iran tried to ship Syrian rockets to Gaza to attack Israel; Moscow announced it would use bases in Cuba, Venezuela and Nicaragua for its navy and bombers; and China budgeted a double-digit increase in military spending as President Obama cut back the U.S. military.
All institutions are more at risk in this era of instant communication and awareness. Reputations get lost quickly, whether it’s a misstep by a company, a gaffe by a politician, or a lack of resolve by an American president.
Over time, the power of the Internet to bring people together will help undermine authoritarian governments. But as Mr. Putin reminds us, in the short term a peaceful world depends more on a U.S. resolute in using its power and influence to deter aggression.”
The disruptive power of collaboration: An interview with Clay Shirky
McKinsey: “From the invention of the printing press to the telephone, the radio, and the Internet, the ways people collaborate change frequently, and the effects of those changes often reverberate through generations. In this video interview, Clay Shirky, author, New York University professor, and leading thinker on the impact of social media, explains the disruptive impact of technology on how people live and work—and on the economics of what we make and consume. This interview was conducted by McKinsey Global Institute partner Michael Chui, and an edited transcript of Shirky’s remarks follows….
Shirky:…The thing I’ve always looked at, because it is long-term disruptive, is changes in the way people collaborate. Because in the history of particularly the Western world, when communications tools come along and they change how people can contact each other, how they can share information, how they can find each other—we’re talking about the printing press, or the telephone, or the radio, or what have you—the changes that are left in the wake of those new technologies often span generations.
The printing press was a sustaining technology for the scientific revolution, the spread of newspapers, the spread of democracy, just on down the list. So the thing I always watch out for, when any source of disruption comes along, when anything that’s going to upset the old order comes along, is I look for what the collaborative penumbra is.”
Open Government -Opportunities and Challenges for Public Governance
New volume of Public Administration and Information Technology series: “Given this global context, and taking into account both the need of academicians and practitioners, it is the intention of this book to shed light on the open government concept and, in particular:
• To provide comprehensive knowledge of recent major developments of open government around the world.
• To analyze the importance of open government efforts for public governance.
• To provide insightful analysis about those factors that are critical when designing, implementing and evaluating open government initiatives.
• To discuss how contextual factors affect open government initiatives’success or failure.
• To explore the existence of theoretical models of open government.
• To propose strategies to move forward and to address future challenges in an international context.”
Big Data, Big New Businesses
Nigel Shaboldt and Michael Chui: “Many people have long believed that if government and the private sector agreed to share their data more freely, and allow it to be processed using the right analytics, previously unimaginable solutions to countless social, economic, and commercial problems would emerge. They may have no idea how right they are.
Even the most vocal proponents of open data appear to have underestimated how many profitable ideas and businesses stand to be created. More than 40 governments worldwide have committed to opening up their electronic data – including weather records, crime statistics, transport information, and much more – to businesses, consumers, and the general public. The McKinsey Global Institute estimates that the annual value of open data in education, transportation, consumer products, electricity, oil and gas, health care, and consumer finance could reach $3 trillion.
These benefits come in the form of new and better goods and services, as well as efficiency savings for businesses, consumers, and citizens. The range is vast. For example, drawing on data from various government agencies, the Climate Corporation (recently bought for $1 billion) has taken 30 years of weather data, 60 years of data on crop yields, and 14 terabytes of information on soil types to create customized insurance products.
Similarly, real-time traffic and transit information can be accessed on smartphone apps to inform users when the next bus is coming or how to avoid traffic congestion. And, by analyzing online comments about their products, manufacturers can identify which features consumers are most willing to pay for, and develop their business and investment strategies accordingly.
Opportunities are everywhere. A raft of open-data start-ups are now being incubated at the London-based Open Data Institute (ODI), which focuses on improving our understanding of corporate ownership, health-care delivery, energy, finance, transport, and many other areas of public interest.
Consumers are the main beneficiaries, especially in the household-goods market. It is estimated that consumers making better-informed buying decisions across sectors could capture an estimated $1.1 trillion in value annually. Third-party data aggregators are already allowing customers to compare prices across online and brick-and-mortar shops. Many also permit customers to compare quality ratings, safety data (drawn, for example, from official injury reports), information about the provenance of food, and producers’ environmental and labor practices.
Consider the book industry. Bookstores once regarded their inventory as a trade secret. Customers, competitors, and even suppliers seldom knew what stock bookstores held. Nowadays, by contrast, bookstores not only report what stock they carry but also when customers’ orders will arrive. If they did not, they would be excluded from the product-aggregation sites that have come to determine so many buying decisions.
The health-care sector is a prime target for achieving new efficiencies. By sharing the treatment data of a large patient population, for example, care providers can better identify practices that could save $180 billion annually.
The Open Data Institute-backed start-up Mastodon C uses open data on doctors’ prescriptions to differentiate among expensive patent medicines and cheaper “off-patent” varieties; when applied to just one class of drug, that could save around $400 million in one year for the British National Health Service. Meanwhile, open data on acquired infections in British hospitals has led to the publication of hospital-performance tables, a major factor in the 85% drop in reported infections.
There are also opportunities to prevent lifestyle-related diseases and improve treatment by enabling patients to compare their own data with aggregated data on similar patients. This has been shown to motivate patients to improve their diet, exercise more often, and take their medicines regularly. Similarly, letting people compare their energy use with that of their peers could prompt them to save hundreds of billions of dollars in electricity costs each year, to say nothing of reducing carbon emissions.
Such benchmarking is even more valuable for businesses seeking to improve their operational efficiency. The oil and gas industry, for example, could save $450 billion annually by sharing anonymized and aggregated data on the management of upstream and downstream facilities.
Finally, the move toward open data serves a variety of socially desirable ends, ranging from the reuse of publicly funded research to support work on poverty, inclusion, or discrimination, to the disclosure by corporations such as Nike of their supply-chain data and environmental impact.
There are, of course, challenges arising from the proliferation and systematic use of open data. Companies fear for their intellectual property; ordinary citizens worry about how their private information might be used and abused. Last year, Telefónica, the world’s fifth-largest mobile-network provider, tried to allay such fears by launching a digital confidence program to reassure customers that innovations in transparency would be implemented responsibly and without compromising users’ personal information.
The sensitive handling of these issues will be essential if we are to reap the potential $3 trillion in value that usage of open data could deliver each year. Consumers, policymakers, and companies must work together, not just to agree on common standards of analysis, but also to set the ground rules for the protection of privacy and property.”
Disinformation Visualization: How to lie with datavis
Mushon Zer-Aviv at School of Data: “Seeing is believing. When working with raw data we’re often encouraged to present it differently, to give it a form, to map it or visualize it. But all maps lie. In fact, maps have to lie, otherwise they wouldn’t be useful. Some are transparent and obvious lies, such as a tree icon on a map often represents more than one tree. Others are white lies – rounding numbers and prioritising details to create a more legible representation. And then there’s the third type of lie, those lies that convey a bias, be it deliberately or subconsciously. A bias that misrepresents the data and skews it towards a certain reading.
It all sounds very sinister, and indeed sometimes it is. It’s hard to see through a lie unless you stare it right in the face, and what better way to do that than to get our minds dirty and look at some examples of creative and mischievous visual manipulation.
Over the past year I’ve had a few opportunities to run Disinformation Visualization workshops, encouraging activists, designers, statisticians, analysts, researchers, technologists and artists to visualize lies. During these sessions I have used the DIKW pyramid (Data > Information > Knowledge > Wisdom), a framework for thinking about how data gains context and meaning and becomes information. This information needs to be consumed and understood to become knowledge. And finally when knowledge influences our insights and our decision making about the future it becomes wisdom. Data visualization is one of the ways to push data up the pyramid towards wisdom in order to affect our actions and decisions. It would be wise then to look at visualizations suspiciously.
Centuries before big data, computer graphics and social media collided and gave us the datavis explosion, visualization was mostly a scientific tool for inquiry and documentation. This history gave the artform its authority as an integral part of the scientific process. Being a product of human brains and hands, a certain degree of bias was always there, no matter how scientific the process was. The effect of these early off-white lies are still felt today, as even our most celebrated interactive maps still echo the biases of the Mercator map projection, grounding Europe and North America on the top of the world, over emphasizing their size and perceived importance over the Global South. Our contemporary practices of programmatically data driven visualization hide both the human eyes and hands that produce them behind data sets, algorithms and computer graphics, but the same biases are still there, only they’re harder to decipher…”
The Power to Give
Press Release: “HTC, a global leader in mobile innovation and design, today unveiled HTC Power To Give™, an initiative that aims to create the a supercomputer by harnessing the collective processing power of Android smartphones.
Currently in beta, HTC Power To Give aims to galvanize smartphone owners to unlock their unused processing power in order to help answer some of society’s biggest questions. Currently, the fight against cancer, AIDS and Alzheimer’s; the drive to ensure every child has clean water to drink and even the search for extra-terrestrial life are all being tackled by volunteer computing platforms.
Empowering people to use their Android smartphones to offer tangible support for vital fields of research, including medicine, science and ecology, HTC Power To Give has been developed in partnership with Dr. David Anderson of the University of California, Berkeley. The project will support the world’s largest volunteer computing initiative and tap into the powerful processing capabilities of a global network of smartphones.
Strength in numbers
One million HTC One smartphones, working towards a project via HTC Power To Give, could provide similar processing power to that of one of the world’s 30 supercomputers (one PetaFLOP). This could drastically shorten the research cycles for organizations that would otherwise have to spend years analyzing the same volume of data, potentially bringing forward important discoveries in vital subjects by weeks, months, years or even decades. For example, one of the programs available at launch is IBM’s World Community Grid, which gives anyone an opportunity to advance science by donating their computer, smartphone or tablet’s unused computing power to humanitarian research. To date, the World Community Grid volunteers have contributed almost 900,000 years’ worth of processing time to cutting-edge research.
Limitless future potential
Cher Wang, Chairwoman, HTC commented, “We’ve often used innovation to bring about change in the mobile industry, but this programme takes our vision one step further. With HTC Power To Give, we want to make it possible for anyone to dedicate their unused smartphone processing power to contribute to projects that have the potential to change the world.”
“HTC Power To Give will support the world’s largest volunteer computing initiative, and the impact that this project will have on the world over the years to come is huge. This changes everything,” noted Dr. David Anderson, Inventor of the Shared Computing Initiative BOINC, University of California, Berkeley.
Cher Wang added, “We’ve been discussing the impact that just one million HTC Power To Give-enabled smartphones could make, however analysts estimate that over 780 million Android phones were shipped in 2013i alone. Imagine the difference we could make to our children’s future if just a fraction of these Android users were able to divert some of their unused processing power to help find answers to the questions that concern us all.”
Opt-in with ease
After downloading the HTC Power To Give app from the Google Play™ store, smartphone owners can select the research programme to which they will divert a proportion of their phone’s processing power. HTC Power To Give will then run while the phone is chargingii and connected to a WiFi network, enabling people to change the world whilst sitting at their desk or relaxing at home.
The beta version of HTC Power To Give will be available to download from the Google Play store and will initially be compatible with the HTC One family, HTC Butterfly and HTC Butterfly s. HTC plans to make the app more widely available to other Android smartphone owners in the coming six months as the beta trial progresses.”
Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters
Pew Internet: “Conversations on Twitter create networks with identifiable contours as people reply to and mention one another in their tweets. These conversational structures differ, depending on the subject and the people driving the conversation. Six structures are regularly observed: divided, unified, fragmented, clustered, and inward and outward hub and spoke structures. These are created as individuals choose whom to reply to or mention in their Twitter messages and the structures tell a story about the nature of the conversation.
If a topic is political, it is common to see two separate, polarized crowds take shape. They form two distinct discussion groups that mostly do not interact with each other. Frequently these are recognizably liberal or conservative groups. The participants within each separate group commonly mention very different collections of website URLs and use distinct hashtags and words. The split is clearly evident in many highly controversial discussions: people in clusters that we identified as liberal used URLs for mainstream news websites, while groups we identified as conservative used links to conservative news websites and commentary sources. At the center of each group are discussion leaders, the prominent people who are widely replied to or mentioned in the discussion. In polarized discussions, each group links to a different set of influential people or organizations that can be found at the center of each conversation cluster.
While these polarized crowds are common in political conversations on Twitter, it is important to remember that the people who take the time to post and talk about political issues on Twitter are a special group. Unlike many other Twitter members, they pay attention to issues, politicians, and political news, so their conversations are not representative of the views of the full Twitterverse. Moreover, Twitter users are only 18% of internet users and 14% of the overall adult population. Their demographic profile is not reflective of the full population. Additionally, other work by the Pew Research Center has shown that tweeters’ reactions to events are often at odds with overall public opinion— sometimes being more liberal, but not always. Finally, forthcoming survey findings from Pew Research will explore the relatively modest size of the social networking population who exchange political content in their network.
Still, the structure of these Twitter conversations says something meaningful about political discourse these days and the tendency of politically active citizens to sort themselves into distinct partisan camps. Social networking maps of these conversations provide new insights because they combine analysis of the opinions people express on Twitter, the information sources they cite in their tweets, analysis of who is in the networks of the tweeters, and how big those networks are. And to the extent that these online conversations are followed by a broader audience, their impact may reach well beyond the participants themselves.
Our approach combines analysis of the size and structure of the network and its sub-groups with analysis of the words, hashtags and URLs people use. Each person who contributes to a Twitter conversation is located in a specific position in the web of relationships among all participants in the conversation. Some people occupy rare positions in the network that suggest that they have special importance and power in the conversation.
Social network maps of Twitter crowds and other collections of social media can be created with innovative data analysis tools that provide new insight into the landscape of social media. These maps highlight the people and topics that drive conversations and group behavior – insights that add to what can be learned from surveys or focus groups or even sentiment analysis of tweets. Maps of previously hidden landscapes of social media highlight the key people, groups, and topics being discussed.
Conversational archetypes on Twitter
The Polarized Crowd network structure is only one of several different ways that crowds and conversations can take shape on Twitter. There are at least six distinctive structures of social media crowds which form depending on the subject being discussed, the information sources being cited, the social networks of the people talking about the subject, and the leaders of the conversation. Each has a different social structure and shape: divided, unified, fragmented, clustered, and inward and outward hub and spokes.
After an analysis of many thousands of Twitter maps, we found six different kinds of network crowds.
Polarized Crowd: Polarized discussions feature two big and dense groups that have little connection between them. The topics being discussed are often highly divisive and heated political subjects. In fact, there is usually little conversation between these groups despite the fact that they are focused on the same topic. Polarized Crowds on Twitter are not arguing. They are ignoring one another while pointing to different web resources and using different hashtags.
Why this matters: It shows that partisan Twitter users rely on different information sources. While liberals link to many mainstream news sources, conservatives link to a different set of websites.
Tight Crowd: These discussions are characterized by highly interconnected people with few isolated participants. Many conferences, professional topics, hobby groups, and other subjects that attract communities take this Tight Crowd form.
Why this matters: These structures show how networked learning communities function and how sharing and mutual support can be facilitated by social media.
Brand Clusters: When well-known products or services or popular subjects like celebrities are discussed in Twitter, there is often commentary from many disconnected participants: These “isolates” participating in a conversation cluster are on the left side of the picture on the left). Well-known brands and other popular subjects can attract large fragmented Twitter populations who tweet about it but not to each other. The larger the population talking about a brand, the less likely it is that participants are connected to one another. Brand-mentioning participants focus on a topic, but tend not to connect to each other.
Why this matters: There are still institutions and topics that command mass interest. Often times, the Twitter chatter about these institutions and their messages is not among people connecting with each other. Rather, they are relaying or passing along the message of the institution or person and there is no extra exchange of ideas.
Community Clusters: Some popular topics may develop multiple smaller groups, which often form around a few hubs each with its own audience, influencers, and sources of information. These Community Clusters conversations look like bazaars with multiple centers of activity. Global news stories often attract coverage from many news outlets, each with its own following. That creates a collection of medium-sized groups—and a fair number of isolates (the left side of the picture above).
Why this matters: Some information sources and subjects ignite multiple conversations, each cultivating its own audience and community. These can illustrate diverse angles on a subject based on its relevance to different audiences, revealing a diversity of opinion and perspective on a social media topic.
Broadcast Network: Twitter commentary around breaking news stories and the output of well-known media outlets and pundits has a distinctive hub and spoke structure in which many people repeat what prominent news and media organizations tweet. The members of the Broadcast Network audience are often connected only to the hub news source, without connecting to one another. In some cases there are smaller subgroups of densely connected people— think of them as subject groupies—who do discuss the news with one another.
Why this matters: There are still powerful agenda setters and conversation starters in the new social media world. Enterprises and personalities with loyal followings can still have a large impact on the conversation.
Support Network: Customer complaints for a major business are often handled by a Twitter service account that attempts to resolve and manage customer issues around their products and services. This produces a hub and spoke structure that is different from the Broadcast Network pattern. In the Support Network structure, the hub account replies to many otherwise disconnected users, creating outward spokes. In contrast, in the Broadcast pattern, the hub gets replied to or retweeted by many disconnected people, creating inward spokes.
Why this matters: As government, businesses, and groups increasingly provide services and support via social media, support network structures become an important benchmark for evaluating the performance of these institutions. Customer support streams of advice and feedback can be measured in terms of efficiency and reach using social media network maps.
Why is it useful to map the social landscape this way?
Social media is increasingly home to civil society, the place where knowledge sharing, public discussions, debates, and disputes are carried out. As the new public square, social media conversations are as important to document as any other large public gathering. Network maps of public social media discussions in services like Twitter can provide insights into the role social media plays in our society. These maps are like aerial photographs of a crowd, showing the rough size and composition of a population. These maps can be augmented with on the ground interviews with crowd participants, collecting their words and interests. Insights from network analysis and visualization can complement survey or focus group research methods and can enhance sentiment analysis of the text of messages like tweets.
Like topographic maps of mountain ranges, network maps can also illustrate the points on the landscape that have the highest elevation. Some people occupy locations in networks that are analogous to positions of strategic importance on the physical landscape. Network measures of “centrality” can identify key people in influential locations in the discussion network, highlighting the people leading the conversation. The content these people create is often the most popular and widely repeated in these networks, reflecting the significant role these people play in social media discussions.
While the physical world has been mapped in great detail, the social media landscape remains mostly unknown. However, the tools and techniques for social media mapping are improving, allowing more analysts to get social media data, analyze it, and contribute to the collective construction of a more complete map of the social media world. A more complete map and understanding of the social media landscape will help interpret the trends, topics, and implications of these new communication technologies.”
Are bots taking over Wikipedia?
Kurzweil News: “As crowdsourced Wikipedia has grown too large — with more than 30 million articles in 287 languages — to be entirely edited and managed by volunteers, 12 Wikipedia bots have emerged to pick up the slack.
The bots use Wikidata — a free knowledge base that can be read and edited by both humans and bots — to exchange information between entries and between the 287 languages.
Which raises an interesting question: what portion of Wikipedia edits are generated by humans versus bots?
To find out (and keep track of other bot activity), Thomas Steiner of Google Germany has created an open-source application (and API): Wikipedia and Wikidata Realtime Edit Stats, described in an arXiv paper.
The percentages of bot vs. human edits as shown in the application is constantly changing. A KurzweilAI snapshot on Feb. 20 at 5:19 AM EST showed an astonishing 42% of Wikipedia being edited by bots. (The application lists the 12 bots.)
Anonymous vs. logged-In humans (credit: Thomas Steiner)
The percentages also vary by language. Only 5% of English edits were by bots; but for Serbian pages, in which few Wikipedians apparently participate, 96% of edits were by bots.
The application also tracks what percentage of edits are by anonymous users. Globally, it was 25 percent in our snapshot and a surprising 34 percent for English — raising interesting questions about corporate and other interests covertly manipulating Wikipedia information.