NextGov: “Analytics is often touted as a new weapon in the technology arsenal of bleeding-edge organizations willing to spend lots of money to combat problems.
In reality, that’s not the case at all. Certainly, there are complex big data analytics tools that will analyze massive data sets to look for the proverbial needle in a haystack, but analytics 101 also includes smarter ways to look at existing data sets.
In this arena, government is making serious strides, according to Kathryn Stack, advisor for evidence-based innovation at the Office of Management and Budget. Speaking in Washington on Thursday at an analytics conference hosted by IBM, Stack provided an outline for agencies to spur innovation and improve mission by making smarter use of the data they already produce.
Interestingly, the first step has nothing to do with technology and everything to do with people. Get “the right people in the room,” Stack said, and make sure they value learning.
“One thing I have learned in my career is that if you really want transformative change, it’s important to bring the right players together across organizations – from your own department and different parts of government,” Stack said. “Too often, we lose a lot of money when siloed organizations lose sight of what the problem really is and spend a bunch of money, and at the end of the day we have invested in the wrong thing that doesn’t address the problem.”
The Department of Labor provides a great example for how to change a static organizational culture into one that integrates performance management, evaluation- and innovation-based processes. The department, she said, created a chief evaluation office and set up evaluation offices for each of its bureaus. These offices were tasked with focusing on important questions to improve performance, going inside programs to learn what is and isn’t working and identifying barriers that impeded experimentation and learning. At the same time, they helped develop partnerships across the agency – a major importance for any organization looking to make drastic changes.
Don’t overlook experimentation either, Stack said. Citing innovation leaders in the private sector such as Google, which runs 12,000 randomized experiments per year, Stack said agencies should not be afraid to get out and run with ideas. Not all of them will be good – only about 10 percent of Google’s experiments usher in new business changes – but even failures can bring meaningful value to the mission.
Stack used an experiment conducted by the United Kingdom’s Behavioral Insights Team as evidence.
The team continually tweaked language to tax compliance letters sent to individuals delinquent on their taxes. Significant experimentation ushered in lots of data, and the team analyzed it to find that one phrase, “Nine out of ten Britains pay their taxes on time,” improved collected revenue by five percent. That case shows how failures can bring about important successes.
“If you want to succeed, you’ve got to be willing to fail and test things out,” Stack said.
Any successful analytics effort in government is going to employ the right people, the best data – Stack said it’s not a secret that the government collects both useful and not-so-useful, “crappy” data – as well as the right technology and processes, too. For instance, there are numerous ways to measure return on investment, including dollars per customer served or costs per successful outcome.
“What is the total investment you have to make in a certain strategy in order to get a successful outcome?” Stack said. “Think about cost per outcome and how you do those calculations.”…”
Citizen participation and technology
ICTlogy: “The recent, rapid rise in the use of digital technology is changing relationships between citizens, organizations and public institutions, and expanding political participation. But while technology has the potential to amplify citizens’ voices, it must be accompanied by clear political goals and other factors to increase their clout.
Those are among the conclusions of a new NDI study, “Citizen Participation and Technology,” that examines the role digital technologies – such as social media, interactive websites and SMS systems – play in increasing citizen participation and fostering accountability in government. The study was driven by the recognition that better insights are needed into the relationship between new technologies, citizen participation programs and the outcomes they aim to achieve.
Using case studies from countries such as Burma, Mexico and Uganda, the study explores whether the use of technology in citizen participation programs amplifies citizen voices and increases government responsiveness and accountability, and whether the use of digital technology increases the political clout of citizens.
The research shows that while more people are using technology—such as social media for mobile organizing, and interactive websites and text messaging systems that enable direct communication between constituents and elected officials or crowdsourcing election day experiences— the type and quality of their political participation, and therefore its impact on democratization, varies. It also suggests that, in order to leverage technology’s potential, there is a need to focus on non-technological areas such as political organizing, leadership skills and political analysis.
For example, the “2% and More Women in Politics” coalition led by Mexico’s National Institute for Women (INMUJERES) used a social media campaign and an online petition to call successfully for reforms that would allocate two percent of political party funding for women’s leadership training. Technology helped the activists reach a wider audience, but women from the different political parties who made up the coalition might not have come together without NDI’s role as a neutral convener.
The study, which was conducted with support from the National Endowment for Democracy, provides an overview of NDI’s approach to citizen participation, and examines how the integration of technologies affects its programs in order to inform the work of NDI, other democracy assistance practitioners, donors, and civic groups.
Observations:
Key findings:
- Technology can be used to readily create spaces and opportunities for citizens to express their voices, but making these voices politically stronger and the spaces more meaningful is a harder challenge that is political and not technological in nature.
- Technology that was used to purposefully connect citizens’ groups and amplify their voices had more political impact.
- There is a scarcity of data on specific demographic groups’ use of, and barriers to technology for political participation. Programs seeking to close the digital divide as an instrument of narrowing the political divide should be informed by more research into barriers to access to both politics and technology.
- There is a blurring of the meaning between the technologies of open government data and the politics of open government that clouds program strategies and implementation.
- Attempts to simply crowdsource public inputs will not result in users self-organizing into politically influential groups, since citizens lack the opportunities to develop leadership, unity, and commitment around a shared vision necessary for meaningful collective action.
- Political will and the technical capacity to engage citizens in policy making, or providing accurate data on government performance are lacking in many emerging democracies. Technology may have changed institutions’ ability to respond to citizen demands but its mere presence has not fundamentally changed actual government responsiveness.”
Crowdsourcing for public safety
Linking Social, Open, and Enterprise Data
Paper by T Omitola, J Davies, A Duke, H Glaser, N Shadbolt for Proceeding WIMS ’14 (Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics): “The new world of big data, of the LOD cloud, of the app economy, and of social media means that organisations no longer own, much less control, all the data they need to make the best informed business decisions. In this paper, we describe how we built a system using Linked Data principles to bring in data from Web 2.0 sites (LinkedIn, Salesforce), and other external business sites such as OpenCorporates, linking these together with pertinent internal British Telecommunications enterprise data into that enterprise data space. We describe the challenges faced during the implementation, which include sourcing the datasets, finding the appropriate “join points” from the individual datasets, as well as developing the client application used for data publication. We describe our solutions to these challenges and discuss the design decisions made. We conclude by drawing some general principles from this work.”
Online and social media data as a flawed continuous panel survey
Fernando Diaz, Michael Gamon, Jake Hofman, Emre Kıcıman, and David Rothschild from Microsoft Research: “There is a large body of research on utilizing online activity to predict various real world outcomes, ranging from outbreaks of influenza to outcomes of elections. There is considerably less work, however, on using this data to understand topic-specific interest and opinion amongst the general population and specific demographic subgroups, as currently measured by relatively expensive surveys. Here we investigate this possibility by studying a full census of all Twitter activity during the 2012 election cycle along with comprehensive search history of a large panel of internet users during the same period, highlighting the challenges in interpreting online and social media activity as the results of a survey. As noted in existing work, the online population is a non-representative sample of the offline world (e.g., the U.S. voting population). We extend this work to show how demographic skew and user participation is non-stationary and unpredictable over time. In addition, the nature of user contributions varies wildly around important events. Finally, we note subtle problems in mapping what people are sharing or consuming online to specific sentiment or opinion measures around a particular topic. These issues must be addressed before meaningful insight about public interest and opinion can be reliably extracted from online and social media data…”
Data Mining Reddit Posts Reveals How to Ask For a Favor–And Get it
Emerging Technology From the arXiv: “There’s a secret to asking strangers for something and getting it. Now data scientists say they’ve discovered it by studying successful requests on the web
One of the more extraordinary phenomena on the internet is the rise of altruism and of websites designed to enable it. The Random Acts of Pizza section of the Reddit website is a good example.
People leave messages asking for pizza which others fulfil if they find the story compelling. As the site says: “because… who doesn’t like helping out a stranger? The purpose is to have fun, eat pizza and help each other out. Together, we aim to restore faith in humanity, one slice at a time.”
A request might go something like this: “It’s been a long time since my mother and I have had proper food. I’ve been struggling to find any kind of work so I can supplement my mom’s social security… A real pizza would certainly lift our spirits”. Anybody can then fulfil the order which is then marked on the site with a badge saying “got pizza’d”, often with notes of thanks.
That raises an interesting question. What kinds of requests are most successful in getting a response? Today, we get an answer thanks to the work of Tim Althoff at Stanford University and a couple of pals who lift the veil on the previously murky question of how to ask for a favour—and receive it.
…
They analysed how various features might be responsible for the success of a post, such as the politeness of the post; its sentiment, whether positive or negative for example; its length. The team also looked at the similarity of the requester to the benefactor; and also the status of the requester.
Finally, they examined whether the post contained evidence of need in the form of a narrative that described why the requester needed free pizza.
Althoff and co used a standard machine learning algorithm to comb through all the possible correlations in 70 per cent of the data, which they used for training. Having found various correlations, they tested to see whether this had predictive power in the remaining 30 per cent of the data. In other words, can their algorithm predict whether a previously unseen request will be successful or not?
It turns out that their algorithm makes a successful prediction about 70 per cent of the time. That’s far from perfect but much better than random guessing which is right only half the time.
So what kinds of factors are important? Narrative is a key part of many of the posts, so Althoff and co spent some time categorising the types of stories people use.
They divided the narratives into five types, those that mention: money; a job; being a student; family; and a final group that includes mentions of friends, being drunk, celebrating and so on, which Althoff and co call ‘craving’.
Of these, narratives about jobs, family and money increase the probability of success. Student narratives have no effect while craving narratives significantly reduce the chances of success. In other words, narratives that communicate a need are more successful than those that do not.
“We find that clearly communicating need through the narrative is essential,” say Althoff and co. And evidence of reciprocation helps too.
(Given these narrative requirements, it is not surprising that longer requests tend to be more successful than short ones.)
So for example, the following request was successful because it clearly demonstrates both need and evidence of reciprocation.
“My gf and I have hit some hard times with her losing her job and then unemployment as well for being physically unable to perform her job due to various hand injuries as a server in a restaurant. She is currently petitioning to have unemployment reinstated due to medical reasons for being unable to perform her job, but until then things are really tight and ANYTHING would help us out right now.
I’ve been both a giver and receiver in RAOP before and would certainly return the favor again when I am able to reciprocate. It took everything we have to pay rent today and some food would go a long ways towards making our next couple of days go by much better with some food.”
By contrast, the ‘craving’ narrative below demonstrates neither and was not successful.
“My friend is coming in town for the weekend and my friends and i are so excited because we haven’t seen him since junior high. we are going to a high school football game then to the dollar theater after and it would be so nice if someone fed us before we embarked :)”
Althoff and co also say that the status of the requester is an important factor too. “We find that Reddit users with higher status overall (higher karma) or higher status within the subcommunity (previous posts) are significantly more likely to receive help,” they say.
But surprisingly, being polite does not help (except by offering thanks).
That’s interesting work. Until now, psychologists have never understood the factors that make requests successful, largely because it has always been difficult to separate the influence of the request from what is being requested.
The key here is that everybody making requests in this study wants the same thing—pizza. In one swoop, this makes the data significantly easier to tease apart.
An important line of future work will be in using his work to understand altruistic behaviour in other communities too…
Ref: http://arxiv.org/abs/1405.3282 : How to Ask for a Favor: A Case Study on the Success of Altruistic Requests”
Democracy and open data: are the two linked?
Molly Shwartz at R-Street: “Are democracies better at practicing open government than less free societies? To find out, I analyzed the 70 countries profiled in the Open Knowledge Foundation’s Open Data Index and compared the rankings against the 2013 Global Democracy Rankings. As a tenet of open government in the digital age, open data practices serve as one indicator of an open government. Overall, there is a strong relationship between democracy and transparency.
Using data collected in October 2013, the top ten countries for openness include the usual bastion-of-democracy suspects: the United Kingdom, the United States, mainland Scandinavia, the Netherlands, Australia, New Zealand and Canada.
There are, however, some noteworthy exceptions. Germany ranks lower than Russia and China. All three rank well above Lithuania. Egypt, Saudi Arabia and Nepal all beat out Belgium. The chart (below) shows the democracy ranking of these same countries from 2008-2013 and highlights the obvious inconsistencies in the correlation between democracy and open data for many countries.
There are many reasons for such inconsistencies. The implementation of open-government efforts – for instance, opening government data sets – often can be imperfect or even misguided. Drilling down to some of the data behind the Open Data Index scores reveals that even countries that score very well, such as the United States, have room for improvement. For example, the judicial branch generally does not publish data and houses most information behind a pay-wall. The status of legislation and amendments introduced by Congress also often are not available in machine-readable form.
As internationally recognized markers of political freedom and technological innovation, open government initiatives are appealing political tools for politicians looking to gain prominence in the global arena, regardless of whether or not they possess a real commitment to democratic principles. In 2012, Russia made a public push to cultivate open government and open data projects that was enthusiastically endorsed by American institutions. In a June 2012 blog post summarizing a Russian “Open Government Ecosystem” workshop at the World Bank, one World Bank consultant professed the opinion that open government innovations “are happening all over Russia, and are starting to have genuine support from the country’s top leaders.”
Given the Russian government’s penchant for corruption, cronyism, violations of press freedom and increasing restrictions on public access to information, the idea that it was ever committed to government accountability and transparency is dubious at best. This was confirmed by Russia’s May 2013 withdrawal of its letter of intent to join the Open Government Partnership. As explained by John Wonderlich, policy director at the Sunlight Foundation:
While Russia’s initial commitment to OGP was likely a surprising boon for internal champions of reform, its withdrawal will also serve as a demonstration of the difficulty of making a political commitment to openness there.
Which just goes to show that, while a democratic government does not guarantee open government practices, a government that regularly violates democratic principles may be an impossible environment for implementing open government.
A cursory analysis of the ever-evolving international open data landscape reveals three major takeaways:
- Good intentions for government transparency in democratic countries are not always effectively realized.
- Politicians will gladly pay lip-service to the idea of open government without backing up words with actions.
- The transparency we’ve established can go away quickly without vigilant oversight and enforcement.”
Digital Social Innovation
But what do we really mean by the term DSI? Peter Baeck and Alice Casey take a closer look at the tools and platforms you use to help you start your own digital social innovation project or get involved in those that others have already begun.
As part of our DSI research project, we have been looking across Europe, and beyond, to find out more about how people are using digital technology to make a social impact. We’re inviting people involved in creating these new social innovations to map their activities over at our open data community map www.digitalsocial.eu. We hope this will give everyone working on digital social innovation more exposure and help funders and researchers to shape their work to support this exciting field.

Below, we highlight our top 11 DSI trends to watch. Although you can read about each one separately, many of the most exciting innovations come from combining several of these trends to form entirely new systems. We’d love to gather more examples, so please add those you may have to our crowdmap here.
Revolution in the Age of Social Media
Book by Linda Herrera on the “Egyptian Popular Insurrection and the Internet”: “Egypt’s January 25 revolution was triggered by a Facebook page and played out both in virtual spaces and the streets. Social media serves as a space of liberation, but it also functions as an arena where competing forces vie over the minds of the young as they battle over ideas as important as the nature of freedom and the place of the rising generation in the political order. This book provides piercing insights into the ongoing struggles between people and power in the digital age.”
The Golden Record 2.0 Will Crowdsource A Selfie of Human Culture
Helen Thompson in the Smithsonian: “In 1977, the Voyager 1 and 2 spacecraft left our solar system, carrying a “Golden Record”—a gold-plated phonograph record containing analogue images, greetings, and music from Earth. It was meant to be a snapshot of humanity. On the small chance that an alien lifeform encountered Voyager, they could get a sense of who made it.
“This record represents our hope and our determination and our goodwill in a vast and awesome universe,” said Carl Sagan who led the six-member team that created the Golden Record.
No spacecraft has left our solar system since Voyager, but in the next few years, NASA’s New Horizons probe, launched in 2006, will reach Pluto and then pass into the far edges of the solar system and beyond. A new project aims to create a “Golden Record 2.0”. Just like the original record, this new version will represent a sampling of human culture for NASA to transmit to New Horizons just before it soars off into the rest of the universe.
The genesis of the project came from Jon Lomberg, a scientific artist and the designer of the original Golden Record. Over the last year he’s recruited experts in a variety of fields to back the project. To convince NASA of public support, he launched a website and put together a petition, signed by over 10,000 people in 140 countries. When Lomberg presented the idea to NASA earlier this year, the agency was receptive and will be releasing a statement with further details on the project on August 25. In the meantime, he and his colleague Albert Yu-Min Lin, a research scientist at the University of California in San Diego, gave a preview of their plan at Smithsonian’s Future Is Here event in Washington, DC, today.
New Horizons will likely only have a small amount of memory space available for the content, so what should make the cut? Photos of landscapes and animals (including humans), sound bites of great speakers, popular music, or even videos could end up on the digital record. Lin is developing a platform where people will be able to explore and critique the submissions on the site. “We wanted to make this a democratic discussion,” says Lin. “How do we make this not a conversation about cute cats and Justin Beiber?” One can only guess what aliens might make of the Earth’s YouTube video fodder.
What sets this new effort apart from the original is that the content will be crowdsourced. “We thought this time why not let the people of earth speak for themselves,” says Lomberg. “Why not figure out a way to crowd source this message so that people would be able to decide what they wanted to say?” Lomberg has teamed up with Lin, who specializes in crowdsourcing technology, to create a platform where people from all over the world can submit content to be included on the record…”