blog post

Using Twitter as a data source: An overview of current social media research tools

Curated on July 11, 2015December 11, 2018 by Stefaan Verhulst

Wasim Ahmed at the LSE Impact Blog: “I have a social media research blog where I find and write about tools that can be used to capture and analyse data from social media platforms. My PhD looks at Twitter data for health, such as the Ebola outbreak in West Africa. I am increasingly asked why I am looking at Twitter, and what tools and methods there are of capturing and analysing data from other platforms such as Facebook, or even less traditional platforms such as Amazon book reviews. Brainstorming a couple of responses to this question by talking to members of the New Social Media New Social Science network, there are at least six reasons:

Twitter is a popular platform in terms of the media attention it receives and it therefore attracts more research due to its cultural status
Twitter makes it easier to find and follow conversations (i.e., by both its search feature and by tweets appearing in Google search results)
Twitter has hashtag norms which make it easier gathering, sorting, and expanding searches when collecting data
Twitter data is easy to retrieve as major incidents, news stories and events on Twitter are tend to be centred around a hashtag
The Twitter API is more open and accessible compared to other social media platforms, which makes Twitter more favourable to developers creating tools to access data. This consequently increases the availability of tools to researchers.
Many researchers themselves are using Twitter and because of their favourable personal experiences, they feel more comfortable with researching a familiar platform.

It is probable that a combination of response 1 to 6 have led to more research on Twitter. However, this raises another distinct but closely related question: when research is focused so heavily on Twitter, what (if any) are the implications of this on our methods?

As for the methods that are currently used in analysing Twitter data i.e., sentiment analysis, time series analysis (examining peaks in tweets), network analysis etc., can these be applied to other platforms or are different tools, methods and techniques required? In addition to qualitative methods such as content analysis, I have used the following four methods in analysing Twitter data for the purposes of my PhD, below I consider whether these would work for other social media platforms:

Sentiment analysis works well with Twitter data, as tweets are consistent in length (i.e., <= 140) would sentiment analysis work well with, for example Facebook data where posts may be longer?
Time series analysis is normally used when examining tweets overtime to see when a peak of tweets may occur, would examining time stamps in Facebook posts, or Instagram posts, for example, produce the same results? Or is this only a viable method because of the real-time nature of Twitter data?
Network analysis is used to visualize the connections between people and to better understand the structure of the conversation. Would this work as well on other platforms whereby users may not be connected to each other i.e., public Facebook pages?
Machine learning methods may work well with Twitter data due to the length of tweets (i.e., <= 140) but would these work for longer posts and for platforms that are not text based i.e., Instagram?

It may well be that at least some of these methods can be applied to other platforms, however they may not be the best methods, and may require the formulation of new methods, techniques, and tools.

So, what are some of the tools available to social scientists for social media data? In the table below I provide an overview of some the tools I have been using (which require no programming knowledge and can be used by social scientists):…(More)”

Democratising the Data Revolution

Curated on July 11, 2015August 3, 2018 by Stefaan Verhulst

Jonathan Gray at Open Knowledge: “What will the “data revolution” do? What will it be about? What will it count? What kinds of risks and harms might it bring? Whom and what will it serve? And who will get to decide?

Today we are launching a new discussion paper on “Democratising the Data Revolution”, which is intended to advance thinking and action around civil society engagement with the data revolution. It looks beyond the disclosure of existing information, towards more ambitious and substantive forms of democratic engagement with data infrastructures.¹

It concludes with a series of questions about what practical steps institutions and civil society organisations might take to change what is measured and how, and how these measurements are put to work.

You can download the full PDF report here, or continue to read on in this blog post.

What Counts?

How might civil society actors shape the data revolution? In particular, how might they go beyond the question of what data is disclosed towards looking at what is measured in the first place? To kickstart discussion around this topic, we will look at three kinds of intervention: changing existing forms of measurement, advocating new forms of measurement and undertaking new forms of measurement.

Changing Existing Forms of Measurement

Rather than just focusing on the transparency, disclosure and openness of public information, civil society groups can argue for changing what is measured with existing data infrastructures. One example of this is recent campaigning around company ownership in the UK. Advocacy groups wanted to unpick networks of corporate ownership and control in order to support their campaigning and investigations around tax avoidance, tax evasion and illicit financial flows.

While the UK company register recorded information about “nominal ownership”, it did not include information about so-called “beneficial ownership”, or who ultimately benefits from the ownership and control of companies. Campaigners undertook an extensive programme of activities to advocate for changes and extensions to existing data infrastructures – including via legislation, software systems, and administrative protocols.²

Advocating New Forms of Measurement

As well as changing or recalibrating existing forms of measurement, campaigners and civil society organisations can make the case for the measurement of things which were not previously measured. For example, over the past several decades social and political campaigning has resulted in new indicators about many different issues – such as gender inequality, health, work, disability, pollution or education.³ In such cases activists aimed to establish a given indicator as important and relevant for public institutions, decision makers, and broader publics – in order to, for example, inform policy development or resource allocation.

Undertaking New Forms of Measurement

Historically, many civil society organisations and advocacy groups have collected their own data to make the case for action on issues that they work on – from human rights abuses to endangered species….(More)”

Defining Public Engagement: A four-level approach.

Curated on July 9, 2015August 3, 2018 by Stefaan Verhulst

Della Rucker’s Chapter 2 for an Online Public Engagement Book: “….public engagement typically means presenting information on an project or draft plan and addressing questions or comments. For planners working on long-range issues, such as a comprehensive plan, typical public engagement actions may include feedback questions, such as “what should this area look like?” or “what is your vision for the future of the neighborhood?” Such questions, while inviting participants to take a more active role in the community decision-making than the largely passive viewer/commenter in the first example, still places the resident in a peripheral role: that of an information source, functionally similar to the demographic data and GIS map layers that the professionals use to develop plans.

In a relatively small number of cases, planners and community advocates have found more robust and more direct means of engaging residents in decision -making around the future of their communities. Public engagement specialists, often originating from a community development or academic background, have developed a variety of methods, such as World Cafe and the Fishbowl, that are designed to facilitate more meaningful sharing of information among community residents, often as much with the intent of building connectivity and mutual understanding among residents of different backgrounds as for the purpose of making policy decisions.

Finally, a small but growing number of strategies have begun to emerge that place the work of making community decisions directly in the hands of private residents. Participatory -based budgeting allocates the decision about how to use a portion of a community’s budget to a citizen — based process, and participants work collaboratively through a process that determines what projects or initiatives will be funded in then coming budget cycle. And in the collection of tactics generally known as tactical urbanism or [other names], residents directly intervene in the physical appearance or function of the community by building and placing street furniture, changing parking spaces or driving lanes to pedestrian use, creating and installing new signs, or making other kinds of physical, typically temporary, changes — sometimes with, and sometimes without, the approval of the local government. The purposes of tactical urbanist interventions are twofold: they physically demonstrate the potential impact that more permanent features would have on the community’s transportation and quality of life, and they give residents a concrete and immediate opportunity to impact their environs.

The direct impacts of either participatory budgeting or tactical urbanism intiatives tend to be limited — the amount of budget available for a participatory-based budgeting initiative is usually a fraction of the total budget, and the physical area impacted by a tactical urbanism event is generally limited to a few blocks. Anecdotal evidence from both types of activity, however, seems to indicate an increased understanding of community needs and an increased sense of agency -of having the power to influence one’s community’s future — among participants.

Online public engagement methods have the potential to facilitate a wide variety of public engagement, from making detailed project information more readily available to enabling crowdsourced decision-making around budget and policy choices. However, any discussion of online public engagement methods will soon run up against the same basic challenge: when we use that term, what kind of engagement — what kind of participant experience — are we talking about?

We could divide public participation tasks according to one of several existing organization systems, or taxonomies. The two most commonly used in public engagement theory and practice derive from Sherry R. Arnestein’s 1969 academic paper, “A Ladder of Citizen Participation,” and the International Association of Public Participation’s Public Participation Spectrum.

Although these two taxonomies reflect the same basic idea — that one’s options in selecting public engagement activities range along a spectrum from generally less to more active engagement on the part of the public — they divide and label the classifications differently. …From my perspective, both of these frameworks capture the central issue of recognizing more to less intensive public engagement options, but the number of divisions and the sometimes abstract wording appears to have made it difficult for these insights to find widespread use outside of an academic context. Practitioners who need to think though these options seem to have some tendency to become tangled in the fine-grained differentiations, and the terminology can both make these distinctions harder to think about and lead to mistaken assumption that one is doing higher-level engagement that is actually the case. Among commercial online public engagement platform providers, blog posts claiming that their tool addresses the whole Spectrum appear on a relatively regular basis, even when the tool in questions is designed for feedback, not decision -making.

For these reasons, this book will use the following framework of engagement types, which is detailed enough to demarcate what I think are the most crucial differentiations while at the same time keeping the framework simple enough to use in routine process planning.

The four engagement types we will talk about are: Telling; Asking; Discussing; Deciding…(More)”

Handbook: How to Catalyze Humanitarian Innovation in Computing Research Institutes

Curated on June 17, 2015October 10, 2018 by Stefaan Verhulst

Patrick Meier: “The handbook below provides practical collaboration guidelines for both humanitarian organizations & computing research institutes on how to catalyze humanitarian innovation through successful partnerships. These actionable guidelines are directly applicable now and draw on extensive interviews with leading humanitarian groups and CRI’s including the International Committee of the Red Cross (ICRC), United Nations Office for the Coordination of Humanitarian Affairs (OCHA), United Nations Children’s Fund (UNICEF), United Nations High Commissioner for Refugees (UNHCR), UN Global Pulse, Carnegie Melon University (CMU), International Business Machines (IBM), Microsoft Research, Data Science for Social Good Program at the University of Chicago and others.

This handbook, which is the first of its kind, also draws directly on years of experience and lessons learned from the Qatar Computing Research Institute’s (QCRI) active collaboration and unique partnerships with multiple international humanitarian organizations. The aim of this blog post is to actively solicit feedback on this first, complete working draft, which is available here as an open and editable Google Doc. …(More)”

How Crowdsourcing Can Help Us Fight ISIS

Curated on June 11, 2015July 19, 2019 by Stefaan Verhulst

Dr. Maha Hosain Aziz at the Huffington Post: “There’s no question that ISIS is gaining ground. …So how else can we fight ISIS? By crowdsourcing data – i.e. asking a relevant group of people for their input via text or the Internet on specific ISIS-related issues. In fact, ISIS has been using crowdsourcing to enhance its operations since last year in two significant ways. Why shouldn’t we?

First, ISIS is using its crowd of supporters in Syria, Iraq and elsewhere to help strategize new policies. Last December, the extremist group leveraged its global crowd via social media to brainstorm ideas on how to kill 26-year-old Jordanian coalition fighter pilot Moaz al-Kasasba. ISIS supporters used the hashtag “Suggest a Way to Kill the Jordanian Pilot Pig” and “We All Want to Slaughter Moaz” to make their disturbing suggestions, which included decapitation, running al-Kasasba over with a bulldozer and burning him alive (which was the winner). Yes, this sounds absurd and was partly a publicity stunt to boost ISIS’ image. But the underlying strategy to crowdsource new strategies makes complete sense for ISIS as it continues to evolve – which is what the US government should consider as well.

In fact, in February, the US government tried to crowdsource more counterterrorism strategies. Via its official blog, DipNote, the State Departmentasked the crowd – in this case, US citizens – for their suggestions for solutions to fight violent extremism. This inclusive approach to policymaking was obviously important for strengthening democracy, with more than 180 entries posted over two months from citizens across the US. But did this crowdsourcing exercise actually improve US strategy against ISIS? Not really. What might help is if the US government asked a crowd of experts across varied disciplines and industries about counterterrorism strategies specifically against ISIS, also giving these experts the opportunity to critique each other’s suggestions to reach one optimal strategy. This additional, collaborative, competitive and interdisciplinary expert insight can only help President Obama and his national security team to enhance their anti-ISIS strategy.

Second, ISIS has been using its crowd of supporters to collect intelligence information to better execute its strategies. Since last August, the extremist group has crowdsourced data via a Twitter campaign specifically on Saudi Arabia’s intelligence officials, including names and other personal details. This apparently helped ISIS in its two suicide bombing attacks during prayers at a Shite mosque last month; it also presumably helped ISIS infiltrate a Saudi Arabian border town via Iraq in January. This additional, collaborative approach to intelligence collection can only help President Obama and his national security team to enhance their anti-ISIS strategy.

In fact, last year, the FBI used crowdsourcing to spot individuals who might be travelling abroad to join terrorist groups. But what if we asked the crowd of US citizens and residents to give us information specifically on where they’ve seen individuals get lured by ISIS in the country, as well as on specific recruitment strategies they may have noted? This might also lead to more real-time data points on ISIS defectors returning to the US – who are they, why did they defect and what can they tell us about their experience in Syria or Iraq? Overall, crowdsourcing such data (if verifiable) would quickly create a clearer picture of trends in recruitment and defectors across the country, which can only help the US enhance its anti-ISIS strategies.

This collaborative approach to data collection could also be used in Syria and Iraq with texts and online contributions from locals helping us to map ISIS’ movements….(More)”

Field experimenting in economics: Lessons learned for public policy

Curated on June 4, 2015August 3, 2018 by Stefaan Verhulst

Robert Metcalfe at OUP Blog: “Do neighbourhoods matter to outcomes? Which classroom interventions improve educational attainment? How should we raise money to provide important and valued public goods? Do energy prices affect energy demand? How can we motivate people to become healthier, greener, and more cooperative? These are some of the most challenging questions policy-makers face. Academics have been trying to understand and uncover these important relationships for decades.

Many of the empirical tools available to economists to answer these questions do not allow causal relationships to be detected. Field experiments represent a relatively new methodological approach capable of measuring the causal links between variables. By overlaying carefully designed experimental treatments on real people performing tasks common to their daily lives, economists are able to answer interesting and policy-relevant questions that were previously intractable. Manipulation of market environments allows these economists to uncover the hidden motivations behind economic behaviour more generally. A central tenet of field experiments in the policy world is that governments should understand the actual behavioural responses of their citizens to changes in policies or interventions.

Field experiments represent a departure from laboratory experiments. Traditionally, laboratory experiments create experimental settings with tight control over the decision environment of undergraduate students. While these studies also allow researchers to make causal statements, policy-makers are often concerned subjects in these experiments may behave differently in settings where they know they are being observed or when they are permitted to sort out of the market.

For example, you might expect a college student to contribute more to charity when she is scrutinized in a professor’s lab than when she can avoid the ask altogether. Field experiments allow researchers to make these causal statements in a setting that is more generalizable to the behaviour policy-makers are directly interested in.

To date, policy-makers traditionally gather relevant information and data by using focus groups, qualitative evidence, or observational data without a way to identify causal mechanisms. It is quite easy to elicit people’s intentions about how they behave with respect to a new policy or intervention, but there is increasing evidence that people’s intentions are a poor guide to predicting their behaviour.

However, we are starting to see a small change in how governments seek to answer pertinent questions. For instance, the UK tax office (Her Majesty’s Revenue and Customs) now uses field experiments across some of its services to improve the efficacy of scarce taxpayers money. In the US, there are movements toward gathering more evidence from field experiments.

In the corporate world, experimenting is not new. Many of the current large online companies—such as Amazon, Facebook, Google, and Microsoft—are constantly using field experiments matched with big data to improve their products and deliver better services to their customers. More and more companies will use field experiments over time to help them better set prices, tailor advertising, provide a better customer journey to increase welfare, and employ more productive workers…(More).

Five Headlines from a Big Month for the Data Revolution

Curated on May 4, 2015May 29, 2019 by Stefaan Verhulst

Sarah T. Lucas at Post2015.org: “If the history of the data revolution were written today, it would include three major dates. May 2013, when theHigh Level Panel on the Post-2015 Development Agenda first coined the phrase “data revolution.” November 2014, when the UN Secretary-General’s Independent Expert Advisory Group (IEAG) set a vision for it. And April 2015, when five headliner stories pushed the data revolution from great idea to a concrete roadmap for action.

The April 2015 Data Revolution Headlines

1. The African Data Consensus puts Africa in the lead on bringing the data revolution to the regional level. TheAfrica Data Consensus (ADC) envisions “a profound shift in the way that data is harnessed to impact on development decision-making, with a particular emphasis on building a culture of usage.” The ADC finds consensus across 15 “data communities”—ranging from open data to official statistics to geospatial data, and is endorsed by Africa’s ministers of finance. The ADC gets top billing in my book, as the first contribution that truly reflects a large diversity of voices and creates a political hook for action. (Stay tuned for a blog from my colleague Rachel Quint on the ADC).

2. The Sustainable Development Solutions Network (SDSN) gets our minds (and wallets) around the data needed to measure the SDGs. The SDSN Needs Assessment for SDG Monitoring and Statistical Capacity Development maps the investments needed to improve official statistics. My favorite parts are the clear typology of data (see pg. 12), and that the authors are very open about the methods, assumptions, and leaps of faith they had to take in the costing exercise. They also start an important discussion about how advances in information and communications technology, satellite imagery, and other new technologies have the potential to expand coverage, increase analytic capacity, and reduce the cost of data systems.

3. The Overseas Development Institute (ODI) calls on us to find the “missing millions.” ODI’s The Data Revolution: Finding the Missing Millions presents the stark reality of data gaps and what they mean for understanding and addressing development challenges. The authors highlight that even that most fundamental of measures—of poverty levels—could be understated by as much as a quarter. And that’s just the beginning. The report also pushes us to think beyond the costs of data, and focus on how much good data can save. With examples of data lowering the cost of doing government business, the authors remind us to think about data as an investment with real economic and social returns.

4. Paris21 offers a roadmap for putting national statistic offices (NSOs) at the heart of the data revolution.Paris21’s Roadmap for a Country-Led Data Revolution does not mince words. It calls on the data revolution to “turn a vicious cycle of [NSO] underperformance and inadequate resources into a virtuous one where increased demand leads to improved performance and an increase in resources and capacity.” It makes the case for why NSOs are central and need more support, while also pushing them to modernize, innovate, and open up. The roadmap gets my vote for best design. This ain’t your grandfather’s statistics report!

5. The Cartagena Data Festival features real-live data heroes and fosters new partnerships. The Festival featured data innovators (such as terra-i using satellite data to track deforestation), NSOs on the leading edge of modernization and reform (such as Colombia and the Philippines), traditional actors using old data in new ways (such as the Inter-American Development Bank’s fantastic energy database), groups focused on citizen-generated data (such as The Data Shift and UN My World), private firms working with big data for social good (such asTelefónica), and many others—all reminding us that the data revolution is well underway and will not be stopped. Most importantly, it brought these actors together in one place. You could see the sparks flying as folks learned from each other and hatched plans together. The Festival gets my vote for best conference of a lifetime, with the perfect blend of substantive sessions, intense debate, learning, inspiration, new connections, and a lot of fun. (Stay tuned for a post from my colleague Kristen Stelljes and me for more on Cartagena).

This month full of headlines leaves no room for doubt—momentum is building fast on the data revolution. And just in time.

With the Financing for Development (FFD) conference in Addis Ababa in July, the agreement of Sustainable Development Goals in New York in September, and the Climate Summit in Paris in December, this is a big political year for global development. Data revolutionaries must seize this moment to push past vision, past roadmaps, to actual action and results…..(More)”

21st-Century Public Servants: Using Prizes and Challenges to Spur Innovation

Curated on April 20, 2015July 18, 2019 by Stefaan Verhulst

Jenn Gustetic at the Open Government Initiative Blog: “Thousands of Federal employees across the government are using a variety of modern tools and techniques to deliver services more effectively and efficiently, and to solve problems that relate to the missions of their Agencies. These 21^st-century public servants are accomplishing meaningful results by applying new tools and techniques to their programs and projects, such as prizes and challenges, citizen science and crowdsourcing, open data, and human-centered design.

Prizes and challenges have been a particularly popular tool at Federal agencies. With 397 prizes and challenges posted on challenge.gov since September 2010, there are hundreds of examples of the many different ways these tools can be designed for a variety of goals. For example:

NASA’s Mars Balance Mass Challenge: When NASA’s Curiosity rover pummeled through the Martian atmosphere and came to rest on the surface of Mars in 2012, about 300 kilograms of solid tungsten mass had to be jettisoned to ensure the spacecraft was in a safe orientation for landing. In an effort to seek creative concepts for small science and technology payloads that could potentially replace a portion of such jettisoned mass on future missions, NASA released the Mars Balance Mass Challenge. In only two months, over 200 concepts were submitted by over 2,100 individuals from 43 different countries for NASA to review. Proposed concepts ranged from small drones and 3D printers to radiation detectors and pre-positioning supplies for future human missions to the planet’s surface. NASA awarded the $20,000 prize to Ted Ground of Rising Star, Texas for his idea to use the jettisoned payload to investigate the Mars atmosphere in a way similar to how NASA uses sounding rockets to study Earth’s atmosphere. This was the first time Ted worked with NASA, and NASA was impressed by the novelty and elegance of his proposal: a proposal that NASA likely would not have received through a traditional contract or grant because individuals, as opposed to organizations, are generally not eligible to participate in those types of competitions.
National Institutes of Health (NIH) Breast Cancer Startup Challenge (BCSC): The primary goals of the BCSC were to accelerate the process of bringing emerging breast cancer technologies to market, and to stimulate the creation of start-up businesses around nine federally conceived and owned inventions, and one invention from an Avon Foundation for Women portfolio grantee. While NIH has the capacity to enable collaborative research or to license technology to existing businesses, many technologies are at an early stage and are ideally suited for licensing by startup companies to further develop them into commercial products. This challenge established 11 new startups that have the potential to create new jobs and help promising NIH cancer inventions support the fight against breast cancer. The BCSC turned the traditional business plan competition model on its head to create a new channel to license inventions by crowdsourcing talent to create new startups.

These two examples of challenges are very different, in terms of their purpose and the process used to design and implement them. The success they have demonstrated shouldn’t be taken for granted. It takes access to resources (both information and people), mentoring, and practical experience to both understand how to identify opportunities for innovation tools, like prizes and challenges, to use them to achieve a desired outcome….

Last month, the Challenge.gov program at the General Services Administration (GSA), the Office of Personnel Management (OPM)’s Innovation Lab, the White House Office of Science and Technology Policy (OSTP), and a core team of Federal leaders in the prize-practitioner community began collaborating with the Federal Community of Practice for Challenges and Prizes to develop the other half of the open innovation toolkit, the prizes and challenges toolkit. In developing this toolkit, OSTP and GSA are thinking not only about the information and process resources that would be helpful to empower 21^st-century public servants using these tools, but also how we help connect these people to one another to add another meaningful layer to the learning environment…..

Creating an inventory of skills and knowledge across the 600-person (and growing!) Federal community of practice in prizes and challenges will likely be an important resource in support of a useful toolkit. Prize design and implementation can involve tricky questions, such as:

Do I have the authority to conduct a prize or challenge?
How should I approach problem definition and prize design?
Can agencies own solutions that come out of challenges?
How should I engage the public in developing a prize concept or rules?
What types of incentives work best to motivate participation in challenges?
What legal requirements apply to my prize competition?
Can non-Federal employees be included as judges for my prizes?
How objective do the judging criteria need to be?
Can I partner to conduct a challenge? What’s the right agreement to use in a partnership?
Who can win prize money and who is eligible to compete? …(More)

Solving the obesity crisis: knowledge, nudge or nanny?

Curated on April 15, 2015August 3, 2018 by Stefaan Verhulst

BioMedCentral Blog: ” The 5th Annual Oxford London Lecture (17 March 2015) was delivered by Professor Susan Jebb from Oxford University. The presentation was titled: ‘Knowledge, nudge and nanny: Opportunities to improve the nation’s diet’. In this guest blog Dr Helen Walls, Research Fellow at the London School of Hygiene and Tropical Medicine, covers key themes from this presentation.

“Obesity and related non-communicable disease such as diabetes, heart disease and cancer poses a significant health, social and economic burden in countries worldwide, including the United Kingdom. Whilst the need for action is clear, the nutrition policy response is a highly controversial topic. Professor Jebb raised the question of how best to achieve dietary change: through ‘knowledge, nudge or nanny’?

Education regarding healthy nutrition is an important strategy, but insufficient. People are notoriously bad at putting their knowledge to work. The inclination to overemphasise the importance of knowledge, whilst ignoring the influence of environmental factors on human behaviours, is termed the ‘fundamental attribution error’. Education may also contribute to widening inequities.

Our choices are strongly shaped by the environments in which we live. So if ‘knowledge’ is not enough, what sort of interventions are appropriate? This raises questions regarding individual choice and the role of government. Here, Professor Jebb introduced the Nuffield Intervention Ladder.

The Nuffield Intervention Ladder or what I will refer to as ‘the ladder’ describes intervention types from least to most intrusive on personal choice. With addressing diets and obesity, Professor Jebb believes we need a range of policy types, across the range of rungs on the ladder.

Less intrusive measures on the ladder could include provision of information about healthy and unhealthy foods, and provision of nutritional information on products (which helps knowledge be put into action). More effective than labelling is the signposting of healthier choices.

Taking a few steps up the ladder brings in ‘nudge’, a concept from behavioural economics. A nudge is any aspect of the choice architecture that alters people’s behaviour in a predictable way without forbidding options or significantly changing economic incentives. Nudges are not mandates. Putting fruit at eye level counts as a nudge. Banning junk food does not.

Nudges are not mandates. Putting fruit at eye level counts as a nudge. Banning junk food does not.

The in-store environment has a huge influence over our choices, and many nudge options would fit here. For example, gondalar-end (end of aisle) promotions create a huge up-lift in sales. Removing unhealthy products from this position could make a considerable difference to the contents of supermarket baskets.

Nudge could be used to assist people make better nutritional choices, but it’s also unlikely to be enough. We celebrate the achievement we have made with tobacco control policies and smoking reduction. Here, we use a range of intervention types, including many legislative measures – the ‘nanny’ aspect of the title of this presentation….(More)”