social media

The move toward 'crowdsourcing' public safety

Curated on October 11, 2013August 3, 2018 by Stefaan Verhulst

PhysOrg: “Earlier this year, Martin Dias, assistant professor in the D’Amore-McKim School of Business, presented research for the National Law Enforcement Telecommunications System in which he examined Nlets’ network and how its governance and technology helped enable inter-agency information sharing. This work builds on his research aimed at understanding design principles for this public safety “social networks” and other collaborative networks. We asked Dias to discuss how information sharing around public safety has evolved in recent years and the benefits and challenges of what he describes as “crowdsourcing public safety.” …

What is “crowdsourcing public safety” and why are public safety agencies moving toward this trend?
Crowdsourcing—the term coined by our own assistant professor of journalism Jeff Howe—involves taking a task or job traditionally performed by a distinct agent, or employee, and having that activity be executed by an “undefined, generally large group of people in an open call.” Crowdsourcing public safety involves engaging and enabling private citizens to assist public safety professionals in addressing natural disasters, terror attacks, organized crime incidents, and large-scale industrial accidents.
Public safety agencies have long recognized the need for citizen involvement. Tip lines and missing persons bulletins have been used to engage citizens for years, but with advances in mobile applications and big data analytics, the ability of public safety agencies to receive, process, and make use of high volume, tips, and leads makes crowdsourcing searches and investigations more feasible. You saw this in the FBI Boston Marathon Bombing web-based Tip Line. You see it in the “See Something Say Something” initiatives throughout the country. You see it in AMBER alerts or even remote search and rescue efforts. You even see it in more routine instances like Washington State’s HERO program to reduce traffic violations.
Have these efforts been successful, and what challenges remain?
There are a number of issues to overcome with regard to crowdsourcing public safety—such as maintaining privacy rights, ensuring data quality, and improving trust between citizens and law enforcement officers. Controversies over the National Security Agency’s surveillance program and neighborhood watch programs – particularly the shooting death of teenager Trayvon Martin by neighborhood watch captain George Zimmerman, reflect some of these challenges. It is not clear yet from research the precise set of success criteria, but those efforts that appear successful at the moment have tended to be centered around a particular crisis incident—such as a specific attack or missing person. But as more crowdsourcing public safety mobile applications are developed, adoption and use is likely to increase. One trend to watch is whether national public safety programs are able to tap into the existing social networks of community-based responders like American Red Cross volunteers, Community Emergency Response Teams, and United Way mentors.
The move toward crowdsourcing public safety is part of an overall trend toward improving community resilience, which refers to a system’s ability to bounce back after a crisis or disturbance. Stephen Flynn and his colleagues at Northeastern’s George J. Kostas Research Institute for Homeland Security are playing a key role in driving a national conversation in this area. Community resilience is inherently multi-disciplinary, so you see research being done regarding transportation infrastructure, social media use after a crisis event, and designing sustainable urban environments. Northeastern is a place where use-inspired research is addressing real-world problems. It will take a village to improve community resilience capabilities, and our institution is a vital part of thought leadership for that village.”

Twitter Datastream Used to Predict Flu Outbreaks

Curated on October 10, 2013August 3, 2018 by Stefaan Verhulst

arXivBlog: “The rate at which people post flu-related tweets could become a powerful tool in the battle to spot epidemics earlier, say computer scientists.

Back in 2008, Google launched its now famous flu trends website. It works on the hypothesis that people make more flu-related search queries when they are suffering from the illness than when they are healthy. So counting the number of flu-related search queries in a given country gives a good indication of how the virus is spreading.
The predictions are pretty good. The data generally closely matches that produced by government organisations such as the Centers for Disease Control and Prevention (CDC) in the US. Indeed, in some cases, it has been able to spot an incipient epidemic more than a week before the CDC.
That’s been hugely important. An early indication that the disease is spreading in a population gives governments a welcome headstart in planning its response.
So an interesting question is whether other online services, in particular social media, can make similar or even better predictions. Today, we have an answer thanks to the work of Jiwei Li at Carnegie Mellon University in Pittsburgh, and Claire Cardie at Cornell University in New York State, who have been able to detect the early stages of an influenza outbreak using Twitter.
Their approach is in many ways similar to Google’s. They simply filter the Twitter datastream for flu-related tweets that are also geotagged. That allows them to create a map showing the distribution of these tweets and how it varies over time.
They also model the dynamics of the disease with some interesting subtleties. In the new model, a flu epidemic can be in one of four phases: non-epidemic phase, a rising phase where numbers are increasing, a stationary phase and a declining phase where numbers are falling.
The new approach uses an algorithm that attempts to spot the switch from one phase to another as early as possible. Indeed, Li and Cardie test the effectiveness of their approach using a Twitter dataset of 3.6 million flu-related tweets from about 1 million people in the US between June 2008 and June 2010…
Ref: arxiv.org/abs/1309.7340: Early Stage Influenza Detection from Twitter”

AskThem

Curated on October 9, 2013August 15, 2018 by Stefaan Verhulst

“AskThem is a project of the Participatory Politics Foundation, a 501(c)3 non-profit organization with a mission to increase civic engagement. AskThem is supported by a charitable grant from the Knight Foundation’s Tech For Engagement initiative.
AskThem is a free & open-source website for questions-and-answers with public figures. It’s a not-for-profit tool for a stronger democracy, with open data for informed and engaged communities.
AskThem allows you to:

Find and ask questions to over 142,000 elected officials nationwide: federal, state and city levels of government.
Get signatures for your question or petition, have it delivered over email or Twitter, and push for a public response.
See questions from people near you, sign-on to questions you care about, and review answers from public figures.

It’s like a version of “We The People” for every elected official, from local city council members all the way up to U.S. senators. Enter your email above to be the first to ask a question when we launch and see previews of the site this Fall.
Elected officials: enter your email above and we’ll send you more information about signing up to answer questions on AskThem. It’s a free and non-partisan service to respond to your constituents in an open public forum and update them over email about your work. Or, be a leader in open-government and sign up now.
Issue-based organizations and media: sign up to help promote questions to government from people in your area. We’re working to launch with partnerships that build greater public accountability.
Previously known as the OpenGovernment.org project, AskThem is open-source and uses open government data – our code is available on GitHub – contributions welcome. For more development updates & discussion, join our low-traffic Google Group.
We’re a small non-profit organization actively seeking charitable funding support – help us launch this powerful new tool for public dialogue! Email us for a copy of our non-profit funding prospectus. If you can make a tax-exempt gift to support our work, please donate to PPF via OpenCongress. More background on the project is available on our Knight NewsChallenge proposal from March 2013.
Questions, feedback, ideas? Email David Moore, Executive Director of PPF – david at ppolitics.org, Twitter: @ppolitics; like our page on Facebook & follow @AskThemPPF on Twitter. Stay tuned!”

Using Big Data to Ask Big Questions

Curated on October 6, 2013October 9, 2018 by Stefaan Verhulst

Chase Davis in the SOURCE: “First, let’s dispense with the buzzwords. Big Data isn’t what you think it is: Every federal campaign contribution over the last 30-plus years amounts to several tens of millions of records. That’s not Big. Neither is a dataset of 50 million Medicare records. Or even 260 gigabytes of files related to offshore tax havens—at least not when Google counts its data in exabytes. No, the stuff we analyze in pursuit of journalism and app-building is downright tiny by comparison.
But you know what? That’s ok. Because while super-smart Silicon Valley PhDs are busy helping Facebook crunch through petabytes of user data, they’re also throwing off intellectual exhaust that we can benefit from in the journalism and civic data communities. Most notably: the ability to ask Big Questions.
Most of us who analyze public data for fun and profit are familiar with small questions. They’re focused, incisive, and often have the kind of black-and-white, definitive answers that end up in news stories: How much money did Barack Obama raise in 2012? Is the murder rate in my town going up or down?
Big Questions, on the other hand, are speculative, exploratory, and systemic. As the name implies, they are also answered at scale: Rather than distilling a small slice of a dataset into a concrete answer, Big Questions look at entire datasets and reveal small questions you wouldn’t have thought to ask.
Can we track individual campaign donor behavior over decades, and what does that tell us about their influence in politics? Which neighborhoods in my city are experiencing spikes in crime this week, and are police changing patrols accordingly?
Or, by way of example, how often do interest groups propose cookie-cutter bills in state legislatures?

Looking at Legislation

Even if you don’t follow politics, you probably won’t be shocked to learn that lawmakers don’t always write their own bills. In fact, interest groups sometimes write them word-for-word.
Sometimes those groups even try to push their bills in multiple states. The conservative American Legislative Exchange Council has gotten some press, but liberal groups, social and business interests, and even sororities and fraternities have done it too.
On its face, something about elected officials signing their names to cookie-cutter bills runs head-first against people’s ideal of deliberative Democracy—hence, it tends to make news. Those can be great stories, but they’re often limited in scope to a particular bill, politician, or interest group. They’re based on small questions.
Data science lets us expand our scope. Rather than focusing on one bill, or one interest group, or one state, why not ask: How many model bills were introduced in all 50 states, period, by anyone, during the last legislative session? No matter what they’re about. No matter who introduced them. No matter where they were introduced.
Now that’s a Big Question. And with some basic data science, it’s not particularly hard to answer—at least at a superficial level.

Analyze All the Things!

Just for kicks, I tried building a system to answer this question earlier this year. It was intended as an example, so I tried to choose methods that would make intuitive sense. But it also makes liberal use of techniques applied often to Big Data analysis: k-means clustering, matrices, graphs, and the like.
If you want to follow along, the code is here….
To make exploration a little easier, my code represents similar bills in graph space, shown at the top of this article. Each dot (known as a node) represents a bill. And a line connecting two bills (known as an edge) means they were sufficiently similar, according to my criteria (a cosine similarity of 0.75 or above). Thrown into a visualization software like Gephi, it’s easy to click around the clusters and see what pops out. So what do we find?
There are 375 clusters in total. Because of the limitations of our data, many of them represent vague, subject-specific bills that just happen to have similar titles even though the legislation itself is probably very different (think things like “Budget Bill” and “Campaign Finance Reform”). This is where having full bill text would come handy.
But mixed in with those bills are a handful of interesting nuggets. Several bills that appear to be modeled after legislation by the National Conference of Insurance Legislators appear in multiple states, among them: a bill related to limited lines travel insurance; another related to unclaimed insurance benefits; and one related to certificates of insurance.”

The Science Behind Using Online Communities To Change Behavior

Curated on October 4, 2013August 15, 2018 by Stefaan Verhulst

Sean D. Young in TechCrunch: “Although social media and online communities might have been developed for people to connect and share information, recent research shows that these technologies are really helpful in changing behaviors. My colleagues and I in the medical school, for instance, created online communities designed to improve health by getting people to do things, such as test for HIV, stop using methamphetamines, and just de-stress and relax. We don’t handpick people to join because we think they’ll love the technology; that’s not how science works. We invite them because the technology is relevant to them — they’re engaging in drugs, sex and other behaviors that might put themselves and others at risk. It’s our job to create the communities in a way that engages them enough to want to stay and participate. Yes, we do offer to pay them $30 to complete an hour-long survey, but then they are free to collect their money and never talk to us again. But for some reason, they stay in the group and decide to be actively engaged with strangers.
So how do we create online communities that keep people engaged and change their behaviors? Our starting point is to understand and address their psychological needs….
Throughout our research, we find that newly created online communities can change people’s behaviors by addressing the following psychological needs:
The Need to Trust. Sharing our thoughts, experiences, and difficulties with others makes us feel closer to others and increases our trust. When we trust people, we’re more open-minded, more willing to learn, and more willing to change our behavior. In our studies, we found that sharing personal information (even something as small as describing what you did today) can help increase trust and change behavior.
The Need to Fit In. Most of us inherently strive to fit in. Social norms, or other people’s attitudes and behaviors, heavily influence our own attitudes and behaviors. Each time a new online community or group forms, it creates its own set of social norms and expectations for how people should behave. Most people are willing to change their attitudes and/or behavior to fit these group norms and fit in with the community.
The Need for Self-Worth. When people feel good about themselves, they are more open to change and feel empowered to be able to change their behavior. When an online community is designed to have people support and care for each other, they can help to increase self-esteem.
The Need to Be Rewarded for Good Behavior. Anyone who has trained a puppy knows that you can get him to keep sitting as long as you keep the treats flowing to reward him, but if you want to wean him off the treats and really train him then you’ll need to begin spacing out the treats to make them less predictable. Well, people aren’t that different from animals in that way and can be trained with reinforcements too. For example, “liking” people’s communications when they immediately join a network, and then progressively spacing out the time that their posts are liked (psychologists call this variable reinforcement) can be incorporated onto social network platforms to encourage them to keep posting content. Eventually, these behaviors become habits.
The Need to Feel Empowered. While increasing self-esteem makes people feel good about themselves, increasing empowerment helps them know they have the ability to change. Creating a sense of empowerment is one of the most powerful predictors of whether people will change their behavior. Belonging to a network of people who are changing their own behaviors, support our needs, and are confident in our changing our behavior empowers us and gives us the ability to change our behavior.”

User-Generated Content Is Here to Stay

Curated on October 3, 2013August 3, 2018 by Stefaan Verhulst

Azeem Khan in the Huffington Post: “The way media are transmitted has changed dramatically over the last 10 years. User-generated content (UGC) has completely changed the landscape of social interaction, media outreach, consumer understanding, and everything in between. Today, UGC is media generated by the consumer instead of the traditional journalists and reporters. This is a movement defying and redefining traditional norms at the same time. Current events are largely publicized on Twitter and Facebook by the average person, and not by a photojournalist hired by a news organization. In the past, these large news corporations dominated the headlines — literally — and owned the monopoly on public media. Yet with the advent of smartphones and spread of social media, everything has changed. The entire industry has been replaced; smartphones have supplanted how information is collected, packaged, edited, and conveyed for mass distribution. UGC allows for raw and unfiltered movement of content at lightening speed. With the way that the world works today, it is the most reliable way to get information out. One thing that is for certain is that UGC is here to stay whether we like it or not, and it is driving much more of modern journalistic content than the average person realizes.
Think about recent natural disasters where images are captured by citizen journalists using their iPhones. During Hurricane Sandy, 800,000 photos uploaded onto Instagram with “#Sandy.” Time magazine even hired five iPhoneographers to photograph the wreckage for its Instagram page. During the May 2013 Oklahoma City tornadoes, the first photo released was actually captured by a smartphone. This real-time footage brings environmental chaos to your doorstep in a chillingly personal way, especially considering the photographer of the first tornado photos ultimately died because of the tornado. UGC has been monumental for criminal investigations and man-made catastrophes. Most notably, the Boston Marathon bombing was covered by UGC in the most unforgettable way. Dozens of images poured in identifying possible Boston bombers, to both the detriment and benefit of public officials and investigators. Though these images inflicted considerable damage to innocent bystanders sporting suspicious backpacks, ultimately it was also smartphone images that highlighted the presence of the Tsarnaev brothers. This phenomenon isn’t limited to America. Would the so-called Arab Spring have happened without social media and UGC? Syrians, Egyptians, and citizens from numerous nations facing protests can easily publicize controversial images and statements to be shared worldwide….
This trend is not temporary but will only expand. The first iPhone launched in 2007, and the world has never been the same. New smartphones are released each month with better cameras and faster processors than computers had even just a few years ago….”