Learning from The Wealth of the Commons


Paper by Mae Shaw in Special issue of the Community Development Journal on “Commons Sense New thinking about an old idea: “We are poised between an old world that no longer works and a new one struggling to be born. Surrounded by centralized hierarchies on the one hand and predatory markets on the other, people around the world are searching for alternatives’.

This is the starting point for what David Bollier and Silke Helfrich, the editors of The Wealth of the Commons: A World Beyond Market and State (2012), describe as ‘an extended global exercise in commoning’ – Peter Linebaugh’s term for ‘the self-determination of commoners in managing their shared resources’ (p. 396). In other words, the book itself is offered as an active process of ‘making the path’ by presenting ‘some of the most promising new paths now being developed’. It is intended to be ‘rigorous enough for academic readers yet accessible enough for the layperson’. In this, it more than achieves its ambitions. The Wealth of the Commons is an edited collection of seventy-three short papers from thirty countries: ‘a collective venture of sharing, collaboration, negotiation and creative production among some of the most diverse commons scholars, activists and projects leaders imaginable’. This rich and diverse source of knowledge and inspiration could be described as ‘polyvocal’ in the sense that it presents a multiplicity of voices improvising around a single theme – sometimes in harmony, sometimes discordant, but always interesting.

The book brings together an impressive collection of contributors from different places, backgrounds and interests to explore the meaning of the commons and to advocate for it ‘as a new paradigm’ for the organization of public and private life. In this sense, it represents a project rather than an analysis: essentially espousing a cause with imperative urgency. This is not necessarily a weakness, but it does raise specific questions about what is included and what is absent or marginalized in this particular selection of accounts, and what might be lost along the way. What counts as ‘commons’ or ‘the commons’ or ‘the common’ (all used in the text) is a subject of discussion and contestation here, as elsewhere. The effort to ‘name and claim’ is an integral aspect of the project. As Jeffrey et al. (2012, p. 10) comment, ‘the struggle for the commons has never been without its own politics of separation and division’, raising valid questions about the prospects for a coherent paradigm at this stage. At the very least, however, this rich resource may prove seminal in countering those dominant paradigms of growth and development in which structural and cultural adjustments ‘serve as a justifying rhetoric for continuity in plunder’ of common resources (Mattei, p. 41).

The contributions fall into three general categories: those offering a critique of existing ‘increasingly dysfunctional’ market/state relations; those that ‘enlarge theoretical understandings of the commons as a way to change the world’; and those that ‘describe innovative working projects which demonstrate the feasibility’ of the commons.

What counts as the commons?

As acknowledged in many of the chapters, defining the commons in any consistent and convincing way can be deeply problematic. Like ‘community’ itself, it can be regarded to some degree as an ideological portmanteau which contains a variety of meanings. Nonetheless, there is a general commitment to confront such difficulties in an open way, and to be as clear as possible about what the commons might represent, what it might replace, and what it should not be confused with. Put most simply, the commons refers to what human beings share in nature and society that should be cherished for all now and for the future: ‘the term … provides the binding element between the natural and the social or cultural worlds’ (Weber p.11). Its profound challenge to the logic of competitive capitalist relations, therefore, is to ‘validate new schemes of human relations, production and governance … commonance’ (Bollier and Helfrich, p. xiv) that penetrate all levels of public and private life. This idea is explored in detail in many of the contributions.

The commons, then, claims to represent a philosophical stance, an intellectual framework, a moral and economic imperative, a set of organizing principles and commitments, a movement, and an emerging ‘global community of practice’ (O’Connell, 2012). It has also developed an increasingly shared discourse, which is designed to unsettle institutionalized norms and values and to reclaim or remake the language of co-operation, fairness and social justice. As the editorial points out, the language of capitalism is one that becomes ‘encoded into the epistemology of our language and internalized by people’. In community development, and elsewhere, we have become sensitized to the way in which progressive language can be appropriated to support individualistic market values. When empowerment can mean facilitated asset-stripping of local communities, and solidarity targets can be set by government (e.g. Scottish Government, 2007), then we must be wary about assuming proprietorial closure on the term ‘commons’ itself.

As Federici, in a particularly persuasive chapter, warns: ‘… capital is learning about the virtues of the common good’ (p. 46). She argues that, ‘since at least the 1990s, the language of the commons has been appropriated … by the World Bank and put at the service of privatization’. For this reason, it is important to think of the commons as a ‘quality of relations, a principle of co-operation and of responsibility to each other and to the earth, the forests, the seas, the animals’ (p. 50). This produces a different operational logic, which is explored in depth across the collection.

Deficiencies in the commons framework

To advance the commons as ‘a new paradigm’, it is necessary to locate it historically and to show the ways in which it has been colonized and compromised, as some of these pieces do. It may seem ironic that the meaning of ‘the commons’ to many people in the UK, for example, is that bear pit of parliamentary business, the House of Commons, in which adversarial rather than consensual politics is the order of the day. Reclaiming such foundational ideas is a lengthy and demanding process, as David Graeber shows in The Democracy Project, his recent account of the Occupy Movement, which for a time commanded considerable international interest. Drawing on Linebaugh, Federici contends that ‘commons have been the thread that has connected the history of the class struggle into our time’.

It is unfortunate, therefore, that the volume fails to address the relationship between organized labour and the commons, as highlighted in the introduction, because there is a distinctive contribution to be made here. As Harvey (2012) argues, decentralization and autonomy are also primary vehicles for reinforcing neoliberal class strategies of social reproduction and producing greater inequality. For example, in urban environments in particular, ‘the better the common qualities a social group creates, the more likely it is to be raided and appropriated by private profit-maximising interests’ leading inexorably to economic cleansing of whole areas. Gentrification and tourism are the clearest examples. The salience of class in general is an underdeveloped line of argument. If this authoritative collection is anything to go by, this may be a significant deficiency in the commons framework.

Without historical continuity – honouring the contribution of those ‘commoners’ who came before in various guises and places – there is a danger of falling into the contemporary trap of regarding ‘innovation’ as a way of separating us from our past. History in the past as well as in the making is as essential a part of our commons as is the present and the future – material, temporal and spiritual….”

Civic Crowdfunding: Participatory Communities, Entrepreneurs and the Political Economy of Place


Rodrigo Davis: “Today I’m capping two years of studying the emergence of civic crowdfunding by submitting my master’s thesis to the MIT archives…You can read Civic Crowdfunding: Participatory Communities, Entrepreneurs and the Political Economy of Place in its entirety (173 pages) now,…
Crowdfunding is everywhere. People are using it to fund watches, comic books, even famous film directors are doing it. In what is now a $6 billion industry globally, I think the most interesting, disruptive and exciting work that’s happening is in donation-based crowdfunding. That’s worth, very roughly, $1.2 billion a year worldwide per year. Within that subset, I’ve been looking at civic projects, people who are producing shared goods for a community or broader public. These projects build on histories of community fundraising and resource pooling that long predate the Internet; what’s changed is that we’ve created a scalable, portable platform model to carry out these existing practices.
So how is civic crowdfunding doing? When I started this project very few people were using that term. No one had done any aggregated data collection and published it. So I decided to take on that task. I collected data on 1224 projects between 2010 and March 2014, which raised $10.74 million in just over three years. I focused on seven platforms: Catarse (Brazil), Citizinvestor (US), Goteo (Spain), IOBY (US), Kickstarter (US), Neighbor.ly (US) and Spacehive (UK). I didn’t collect everything. …
Here are four things I found out about civic crowdfunding.

  1. Civic crowdfunding is small-scale but relatively successful, and it has big ambitions.Currently the average civic crowdfunding project is small in scale: $6,357 is the median amount raised. But these civic projects seem to be doing pretty well. Projects tagged ‘civic’ on Kickstarter, for instance, succeed 81% of the time. If Civic were a separate category, it would be Kickstarter’s most successful category. Meanwhile, most platform owners and some incumbent institutions see civic crowdfunding as a new mechanism for public-private partnerships capable of realizing large-scale projects. In a small minority of cases, such as the three edge-case projects I explored in Chapter 3 of my thesis, civic crowdfunding has begun to fulfill some of those ambitions. For the center of gravity to shift further in the direction of these potential outcomes, though, existing institutions, including government, large non-profits and the for-profit sector, will need to engage more comprehensively with the process.
  2. Civic crowdfunding started as a hobby for green space projects by local non-profits, but larger organizations are getting involved. Almost a third of campaigners are using civic crowdfunding platforms for park and garden-related projects (29%). Event-based projects, and education and training are also popular. Sports and mobility projects are pretty uncommon. The frequency of garden and park projects is partly because these projects are not capital intensive, and they’re uncontroversial. That’s also changing. Organizations from governments to corporations and large foundations, are exploring ways to support crowdfunding for a much wider range of community-facing activities. Their modes of engagement include publicizing campaigns, match-funding campaigns on an ad-hoc basis, running their own campaigns and even building new platforms from the ground up.
  3. Civic crowdfunding is concentrated in cities (especially those where platforms are based). The genre is too new to have spread very effectively, it seems. Five states account for 80% of the projects, and this is partly a function of where the platforms are located. New York, California are our top two, followed by Illinois and Oregon. We know there’s a strong trend towards big cities. It’s hard work for communities to use crowdfunding to get projects off the ground, especially when it’s an unfamiliar process. The platforms have played a critical role in building participants’ understanding of crowdfunding and supporting them through the process.
  4. Civic crowdfunding has the same highly unequal distributional tendencies as other crowd markets. When we look at the size distribution of projects, the first thing we notice is something close to a Pareto distribution, or Long Tail. Most projects are small-scale, but a small number of high-value projects have taken a large share of the total revenue raised by civic crowdfunding. We shouldn’t be surprised by this. On Kickstarter most successful projects are between 5 and 10k, and 47% of civic projects I studied are in the same bracket. The problem is that we tend to remember the outliers, such as Veronica Mars and Spike Lee – because they show what’s possible. But they are still the outliers.

Now, here are two things we don’t know.

  1. Will civic crowdfunding deter public investment or encourage it?
  2. Will civic crowdfunding widen wealth gaps?”

Conceptualizing Open Data ecosystems: A timeline analysis of Open Data development in the UK


New paper by Tom Heath et al: “In this paper, we conceptualize Open Data ecosystems by analysing the major stakeholders in the UK. The conceptualization is based on a review of popular Open Data definitions and business ecosystem theories, which we applied to empirical data using a timeline analysis. Our work is informed by a combination of discourse analysis and in-depth interviews, undertaken during the summer of 2013. Drawing on the UK as a best practice example, we identify a set of structural business ecosystem properties: circular flow of resources, sustainability, demand that encourages supply, and dependence developing between suppliers, intermediaries, and users. However, significant gaps and shortcomings are found to remain. Most prominently, demand is not yet fully encouraging supply and actors have yet to experience fully mutual interdependence.”

On the barriers for local government releasing open data


Paper by Peter Conradie and Dr. Sunil Choenni in Government Information Quarterly: “Due to expected benefits such as citizen participation and innovation, the release of Public Sector Information as open data is getting increased attention on various levels of government. However, currently data release by governments is still novel and there is little experience and knowledge thus far about its benefits, costs and barriers. This is compounded by a lack of understanding about how internal processes influence data release. Our aim in this paper is to get a better understanding of these processes and how they influence data release, i.e., to find determinants for the release of public sector information. For this purpose, we conducted workshops, interviews, questionnaires, desk research and practice based cases in the education program of our university, involving six local public sector organizations. We find that the way data is stored, the way data is obtained and the way data is used by a department are crucial indicators for open data release. We conclude with the lessons learned based on our research findings. These findings are: we should take a nuanced approach towards data release, avoid releasing data for its own sake, and take small incremental steps to explore data release.”

Winds of Change: The Progress of Open Government Policymaking in Latin America and the Caribbean


Inter-American Development Bank paper by Ramírez Alujas, Álvaro V.; and Dassen, Nicolás: “The year 2013 has become known as the year of Open Government. The continuing progress of the Open Government Partnership represents the consolidation of a process that, in less than two years, has strengthened the promotion and implementation of public policies. These policies are founded on the principles of transparency and access to public information, citizen participation, integrity, and the harnessing of technology on behalf of openness and accountability in 63 participating countries. The Latin American and Caribbean region, in particular, stands out with the most widespread participation, including 15 borrowing member countries of the Inter-American Development Bank (IDB). Fourteen of these have action plans in process for the implementation and/or evaluation of these policies, reinforcing their commitment to open government. Trinidad and Tobago, one of the 15 member countries, will soon present its own action plan. To date, various countries are developing public consultation processes and opportunities for participation for a new two-year period of commitments relating to open government. It is, therefore, worthwhile to review, country-by-country, the commitments that have been carried out and to consider the views expressed by relevant stakeholders. This analysis will further contribute to this emerging domain a new paradigm for public policy and management reform in the 21st century.”

Innovation Contests


Paper by David Pérez Castrillo and David Wettstein: “We study innovation contests with asymmetric information and identical contestants, where contestants’ efforts and innate abilities generate inventions of varying qualities. The designer offers a reward to the contestant achieving the highest quality and receives the revenue generated by the innovation. We characterize the equilibrium behavior, outcomes and payoffs for both nondiscriminatory and discriminatory (where the reward is contestant-dependent) contests. We derive conditions under which the designer obtains a larger payoff when using a discriminatory contest and describe settings where these conditions are satisfied.”

Saving Big Data from Big Mouths


Cesar A. Hidalgo in Scientific American: “It has become fashionable to bad-mouth big data. In recent weeks the New York Times, Financial Times, Wired and other outlets have all run pieces bashing this new technological movement. To be fair, many of the critiques have a point: There has been a lot of hype about big data and it is important not to inflate our expectations about what it can do.
But little of this hype has come from the actual people working with large data sets. Instead, it has come from people who see “big data” as a buzzword and a marketing opportunity—consultants, event organizers and opportunistic academics looking for their 15 minutes of fame.
Most of the recent criticism, however, has been weak and misguided. Naysayers have been attacking straw men, focusing on worst practices, post hoc failures and secondary sources. The common theme has been to a great extent obvious: “Correlation does not imply causation,” and “data has biases.”
Critics of big data have been making three important mistakes:
First, they have misunderstood big data, framing it narrowly as a failed revolution in social science hypothesis testing. In doing so they ignore areas where big data has made substantial progress, such as data-rich Web sites, information visualization and machine learning. If there is one group of big-data practitioners that the critics should worship, they are the big-data engineers building the social media sites where their platitudes spread. Engineering a site rich in data, like Facebook, YouTube, Vimeo or Twitter, is extremely challenging. These sites are possible because of advances made quietly over the past five years, including improvements in database technologies and Web development frameworks.
Big data has also contributed to machine learning and computer vision. Thanks to big data, Facebook algorithms can now match faces almost as accurately as humans do.
And detractors have overlooked big data’s role in the proliferation of computational design, data journalism and new forms of artistic expression. Computational artists, journalists and designers—the kinds of people who congregate at meetings like Eyeo—are using huge sets of data to give us online experiences that are unlike anything we experienced in paper. If we step away from hypothesis testing, we find that big data has made big contributions.
The second mistake critics often make is to confuse the limitations of prototypes with fatal flaws. This is something I have experienced often. For example, in Place Pulse—a project I created with my team the M.I.T. Media Lab—we used Google Street View images and crowdsourced visual surveys to map people’s perception of a city’s safety and wealth. The original method was rife with limitations that we dutifully acknowledged in our paper. Google Street View images are taken at arbitrary times of the day and showed cities from the perspective of a car. City boundaries were also arbitrary. To overcome these limitations, however, we needed a first data set. Producing that first limited version of Place Pulse was a necessary part of the process of making a working prototype.
A year has passed since we published Place Pulse’s first data set. Now, thanks to our focus on “making,” we have computer vision and machine-learning algorithms that we can use to correct for some of these easy-to-spot distortions. Making is allowing us to correct for time of the day and dynamically define urban boundaries. Also, we are collecting new data to extend the method to new geographical boundaries.
Those who fail to understand that the process of making is iterative are in danger of  being too quick to condemn promising technologies.  In 1920 the New York Times published a prediction that a rocket would never be able to leave  atmosphere. Similarly erroneous predictions were made about the car or, more recently, about iPhone’s market share. In 1969 the Times had to publish a retraction of their 1920 claim. What similar retractions will need to be published in the year 2069?
Finally, the doubters have relied too heavily on secondary sources. For instance, they made a piñata out of the 2008 Wired piece by Chris Anderson framing big data as “the end of theory.” Others have criticized projects for claims that their creators never made. A couple of weeks ago, for example, Gary Marcus and Ernest Davis published a piece on big data in the Times. There they wrote about another of one of my group’s projects, Pantheon, which is an effort to collect, visualize and analyze data on historical cultural production. Marcus and Davis wrote that Pantheon “suggests a misleading degree of scientific precision.” As an author of the project, I have been unable to find where I made such a claim. Pantheon’s method section clearly states that: “Pantheon will always be—by construction—an incomplete resource.” That same section contains a long list of limitations and caveats as well as the statement that “we interpret this data set narrowly, as the view of global cultural production that emerges from the multilingual expression of historical figures in Wikipedia as of May 2013.”
Bickering is easy, but it is not of much help. So I invite the critics of big data to lead by example. Stop writing op–eds and start developing tools that improve on the state of the art. They are much appreciated. What we need are projects that are worth imitating and that we can build on, not obvious advice such as “correlation does not imply causation.” After all, true progress is not something that is written, but made.”

Crowdsourcing the future: predictions made with a social network


New Paper by Clifton Forlines et al: “Researchers have long known that aggregate estimations built from the collected opinions of a large group of people often outperform the estimations of individual experts. This phenomenon is generally described as the “Wisdom of Crowds”. This approach has shown promise with respect to the task of accurately forecasting future events. Previous research has demonstrated the value of utilizing meta-forecasts (forecasts about what others in the group will predict) when aggregating group predictions. In this paper, we describe an extension to meta-forecasting and demonstrate the value of modeling the familiarity among a population’s members (its social network) and applying this model to forecast aggregation. A pair of studies demonstrates the value of taking this model into account, and the described technique produces aggregate forecasts for future events that are significantly better than the standard Wisdom of Crowds approach as well as previous meta-forecasting techniques.”
VIDEO:

This is what happens when you give social networking to doctors


in PandoDaily: “Dr. Gregory Kurio will never forget the time he was called to the ER because a epileptic girl was brought in suffering a cardiac arrest of sorts (HIPAA mandates he doesn’t give out the specific details of the situation). In the briefing, he learned the name of her cardiac physician who he happened to know through the industry. He subsequently called the other doctor and asked him to send over any available information on the patient — latest meds, EKGs, recent checkups, etc.

The scene in the ER was, to be expected, one of chaos, with trainees and respiratory nurses running around grabbing machinery and meds. Crucial seconds were ticking past, and Dr. Kurio quickly realized the fax machine was not the best approach for receiving the records he needed. ER fax machines are often on the opposite of the emergency room, take awhile to print lengthy of records, frequently run out of paper, and aren’t always reliable – not exactly the sort of technology you want when a patient’s life or death hangs in the midst.

Email wasn’t an option either, because HIPAA mandates that sensitive patient files are only sent through secure channels. With precious little time to waste, Dr. Kurio decided to take a chance on a new technology service he had just signed up for — Doximity.

Doximity is a LinkedIn for Doctors of sorts. It has, as one feature, a secure e-fax system that turns faxes into digital messages and sends them to a user’s mobile device. Dr. Kurio gave the other physician his e-fax number, and a little bit of techno-magic happened.

….

With a third of the nation’s doctors on the platform, today Doximity announced a $54 million Series C from DFJ,  T. Rowe Price Associates, Morgan Stanley, and existing investors. The funding news isn’t particularly important, in and of itself, aside from the fact that the company is attracting the attention of private market investors very early in its growth trajectory. But it’s a good opportunity to take a look at Doximity’s business model, how it mirrors the upwards growth of other vertical professional social networks (say that five times fast), and the way it’s transforming our healthcare providers’ jobs.

Doximity works, in many ways, just like LinkedIn. Doctors have profiles with pictures and their resume, and recruiters pay the company to message medical professionals. “If you think it’s hard to find a Ruby developer in San Francisco, try to find an emergency room physician in Indiana,” Doximity CEO Jeff Tangney says. One recruiter’s pain is a smart entrepreneur’s pleasure — a simple, straightforward monetization strategy.

But unlike LinkedIn, Doximity can dive much deeper on meeting doctors’ needs through specialized features like the e-fax system. It’s part of the reason Konstantin Guericke, one of LinkedIn’s “forgotten” co-founders, was attracted to the company and decided to join the board as an advisor. “In some ways, it’s a lot like LinkedIn,” Guericke says, when asked why he decided to help out. “But for me it’s the pleasure of focusing on a more narrow audience and making more of an impact on their life.”

In another such high-impact, specialized feature, doctors can access Doximity’s Google Alerts-like system for academic articles. They can sign up to receive notifications when stories are published about their obscure specialties. That means time-strapped physicians gain a more efficient way to stay up to date on all the latest research and information in their field. You can imagine that might impact the quality of the care they provide.

Lastly, Doximity offers a secure messaging system, allowing doctors to email one another regarding a fellow patient. Such communication is a thorny issue for doctors given HIPPA-related privacy requirements. There are limited ways to legally update say, a primary care physician when a specialist learns one of their patients has colon cancer. It turns into a big game of phone tag to relay what should be relatively straightforward information. Furthermore, leaving voicemails and sending faxes can result in details getting lost in what its an searchable system.

The platform is free for doctors, and it has attracted them quickly join in droves. Doximity co-founder and CEO Jeff Tangney estimates that last year the platform had added 15 to 16 percent of US doctors. But this year, the company claims it’s “on track to have half of US physicians as members by this summer.” Fairly impressive growth rate and market penetration.

With great market penetration comes great power. And dollars. Although the company is only monetizing through recruitment at the moment, the real money to be made with this service is through targeted advertising. Think about how much big pharma and medtech companies would be willing to cough up to to communicate at scale with the doctors who make purchasing decisions. Plus, this is an easy way for them to target industry thought leaders or professionals with certain specialties.

Doximity’s founders’ and investors’ eyes might be seeing dollar signs, but they haven’t rolled anything out yet on the advertising front. They’re wary and want to do so in a way that ads value to all parties while avoiding pissing off medical professionals. When they finally pul lthe trigger, however, it’s has the potential to be a Gold Rush.

Doximity isn’t the only company to have discovered there’s big money to be made in vertical professional social networks. As Pando has written, there’s a big trend in this regard. Spiceworks, the social network for IT professionals which claims to have a third of the world’s IT professionals on the site, just raised $57 million in a round led by none other than Goldman Sachs. Why does the firm have such faith in a free social network for IT pros — seemingly the most mundane and unprofitable of endeavors? Well, just like with doctor and pharma corps, IT companies are willing to shell out big to market their wares directly to such IT pros.

Although the monetization strategies differ from business to business, ResearchGate is building a similar community with a social network of scientists around the world, Edmodo is doing it with educators, GitHub with developers, GrabCAD for mechanical engineers. I’ve argued that such vertical professional social networks are a threat to LinkedIn, stealing business out from under it in large industry swaths. LinkedIn cofounder Konstantin Guericke disagrees.

“I don’t think it’s stealing revenue from them. Would it make sense for LinkedIn to add a profile subset about what insurance someone takes? That would just be clutter,” Guericke says. “It’s more going after an opportunity LinkedIn isn’t well positioned to capitalize on. They could do everything Doximity does, but they’d have to give up something else.”

All businesses come with their own challenges, and Doximity will certainly face its share of them as it scales. It has overcome the initial hurdle of achieving the network effects that come with penetrating the a large segment of the market. Next will come monetizing sensitively and continuing to protecting users — and patients’ — privacy.

There are plenty of data minefields to be had in a sector as closely regulated as healthcare, as fellow medical startup Practice Fusion recently found out. Doximity has to make sure its system for onboarding and verifying new doctors is airtight. The company has already encountered some instances of individuals trying to pose as medical professionals to get access to another’s records — specifically a former lover trying to chase down their ex-spouse’s STI tests. One blowup where the company approves someone they shouldn’t or hackers break into the system, and doctors could lose trust in the safety of the technology….”

Twitter Can Now Predict Crime, and This Raises Serious Questions


Motherboard: “Police departments in New York City may soon be using geo-tagged tweets to predict crime. It sounds like a far-fetched sci-fi scenario a la Minority Report, but when I contacted Dr. Matthew Greber, the University of Virginia researcher behind the technology, he explained that the system is far more mathematical than metaphysical.
The system Greber has devised is an amalgam of both old and new techniques. Currently, many police departments target hot spots for criminal activity based on actual occurrences of crime. This approach, called kernel density estimation (KDE), involves pairing a historical crime record with a geographic location and using a probability function to calculate the possibility of future crimes occurring in that area. While KDE is a serviceable approach to anticipating crime, it pales in comparison to the dynamism of Twitter’s real-time data stream, according to Dr. Gerber’s research paper “Predicting Crime Using Twitter and Kernel Density Estimation”.
Dr. Greber’s approach is similar to KDE, but deals in the ethereal realm of data and language, not paperwork. The system involves mapping the Twitter environment; much like how police currently map the physical environment with KDE. The big difference is that Greber is looking at what people are talking about in real time, as well as what they do after the fact, and seeing how well they match up. The algorithms look for certain language that is likely to indicate the imminent occurrence of a crime in the area, Greber says. “We might observe people talking about going out, getting drunk, going to bars, sporting events, and so on—we know that these sort of events correlate with crime, and that’s what the models are picking up on.”
Once this data is collected, the GPS tags in tweets allows Greber and his team to pin them to a virtual map and outline hot spots for potential crime. However, everyone who tweets about hitting the club later isn’t necessarily going to commit a crime. Greber tests the accuracy of his approach by comparing Twitter-based KDE predictions with traditional KDE predictions based on police data alone. The big question is, does it work? For Greber, the answer is a firm “sometimes.” “It helps for some, and it hurts for others,” he says.
According to the study’s results, Twitter-based KDE analysis yielded improvements in predictive accuracy over traditional KDE for stalking, criminal damage, and gambling. Arson, kidnapping, and intimidation, on the other hand, showed a decrease in accuracy from traditional KDE analysis. It’s not clear why these crimes are harder to predict using Twitter, but the study notes that the issue may lie with the kind of language used on Twitter, which is characterized by shorthand and informal language that can be difficult for algorithms to parse.
This kind of approach to high-tech crime prevention brings up the familiar debate over privacy and the use of users’ date for purposes they didn’t explicitly agree to. The case becomes especially sensitive when data will be used by police to track down criminals. On this point, though he acknowledges post-Snowden societal skepticism regarding data harvesting for state purposes, Greber is indifferent. “People sign up to have their tweets GPS tagged. It’s an opt-in thing, and if you don’t do it, your tweets won’t be collected in this way,” he says. “Twitter is a public service, and I think people are pretty aware of that.”…