Network science and marketing: A virus’ tale

By Matthias Wildemeersch,  IIASA Advanced Systems Analysis and Ecosystems Services and Management Programs

FotoQuest Austria is a citizen science campaign initiated by the IIASA Ecosystems Services & Management Program that aims to involve the general public in mapping land use in Austria. Understanding the evolution of urban sprawl is important to estimate the risk of flooding, while the preservation of wetlands has important implications for climate change.

But how can we engage people in environmental monitoring, in particular when they are growing increasingly resistant to traditional forms of advertising? Viral marketing makes use of social networks to spread messages, and takes advantage of the trust that we have in the recommendation coming from a friend rather than from a stranger or a company.

Network science and the formal description of spreading phenomena can shed light on the propagation of messages through communities and can be applied to inform and design viral marketing campaigns.

Viral spreading © kittitee550 | Dollar Photo Club

Viral spreading © kittitee550 | Dollar Photo Club

Network science is a multi-disciplinary field of research that draws on graph theory, statistical mechanics, inference, and other theories to study the behavior of agents in various networks. The spreading phenomena in viral marketing show similarities with well-studied spreading processes over biological, social, physical, and financial networks. For instance, we can think about epidemics,which are well understood and allow for the design of optimal strategies to contain viruses. Another example is opinion dynamics, which received renewed research attention over the last years in the context of social media.  In contrast to diseases or computer viruses, which we aim to contain and stop, the goal of viral marketing is to spread widely, reaching the largest possible fraction of a community.

What makes viral marketing unique?
But some aspects of viral marketing are very different from what we see in other spreading phenomena. First of all, there are many platforms that can be used to spread information at the same time, and the interaction between these platforms is not always transparent. Human psychology is a crucial factor in social networks, as repeated interaction and saturation can decrease the willingness to further spread viral content. Marketing campaigns have a limited budget, and therefore it is meaningful to understand how we can use incentives and how efficient they are. This also means that it is essential to find the group of most influential people that can be used as seeds for the viral campaign.

Network science has addressed to a great extent all these individual questions, mostly under the assumption of full knowledge of the connections between the agents and their influence. Currently, so-called multiplexes are an active research field that studies the behavior of multi-layer networks. This research unveils the relationships between the dynamics of viral marketing, the connection pattern, and strength between the network layers. Although viral spreading may be unachievable in a single layer, for example a social network like Facebook, the critical threshold may be exceeded by joining different platforms. Within a given platform, people alike can be clustered using community detection algorithms. Once the communities are identified, influence maximization algorithms have been established to select these persons that maximize the spread of viral content. Although this discrete optimization problem is computationally difficult—or NP-hard—mathematicians have proposed algorithms that can efficiently predict who to target to give a campaign the best chance of going viral. On top of that, optimal pricing strategies have been developed to reward recommenders.

The FotoQuest Austria app aims to engage citizen scientists in their campaign - network theory may help them go "viral." © IIASA

The FotoQuest Austria app aims to engage citizen scientists in their campaign – network theory may help them go “viral.” © IIASA

Although the literature is extensive, the nature of the results is often theoretical and involves mathematically complex models and algorithms. Considering that only partial information on the network is usually available, it is not straightforward to bring this knowledge back to a practical marketing campaign. So researchers in this field are trying to bridge the gap between theoretical results and practical problems. The generic, powerful methods of network science are sufficiently versatile to capture the specifics of real-world applications. As such, network science can provide guidelines that can bring great value for the design of heuristic methods in marketing strategies.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Black swan sandwich: From one risk to layered risks

By Leena Ilmola-Sheppard, IIASA Advanced Systems Analysis (ASA) Program

Crisis management problems are getting more complex and complicated, but at the same time, governments have less and less resources for their management. How can research help decision makers plan for the unplannable?

Last week in Geneva,  I took part in a crisis management workshop for national decision makers organized by the OECD High Level Risk Forum and the Swiss Federation Chancellor  While the meeting was very specific to national security and crisis management, I found some takeaway messages that are relevant to us researchers as well, especially for those of us that hope that to help decision makers make better decisions through modeling.

leena-pics

Mads Ecklon, Head of the Centre for Preparedness Planning and Crisis Management of the Danish Emergency Management Agency, used the figure above as a framework to explain crisis management. His message can also be applied to the development of any social system.  Picture 1 describes the standard starting point of the modeling exercise. We are modeling one behavior and then analyze how the system performance develops in a controlled situation. Ecklon explained that potential futures are not so predictable: the crisis in hand can either be solved, solved only partially, not solved at all, or in the worst case the problem may escalate (you never know how a social system will react in the crisis situation—a small incident can turn into a massive riot).  The challenge for both national level crisis managers and modelers is same; you have to take all of these potential developments into a consideration.

But what happens if a new, unexpected crisis pops up while all attention is focused on the initial problem?  Such hard-to-predict events are often referred to as “black swan events.” Eclon said that their team has more frequently been seeing situations where, when attention is focused on the current crisis, a new, different or related, crisis develops and no one notices it.  For example, in the UK in 2007, just when all the crisis management resources were invested in flooding crisis, foot and mouth disease broke out among cattle.  The new phenomenon, Ecklon  claimed, is that these crises are piling up and even if they are independent from each other, the joint impact can be disastrous.

Leena5

Modeling black swan events
I think that this message is important for modelers as well.  We may be very happy to model all the four windows of our comic strip. But how can we include new surprises and crises into an ongoing model?   We should develop models that include different development trajectories triggered by a change in one of our variables, but simultaneously we should be able to account for several overlapping surprises.

In the meeting, national risk managers spoke about ”unknown unknowns,” low probability high impact risks–strange unforeseen animals like a black swan that jump on the plate just when we think that the situation is in some kind of control.

This kind of modeling challenge is fascinating from an academic perspective, but researchers’ intellectual hunger should not be the only reason to develop methods for these kinds of situations.  From decision makers’ perspective, this is exactly the case where useful models are needed. The multiple simultaneous developments of the complex systems are difficult to capture even for the brightest of the crisis teams, but a model could manage a job very well.

Most of the IIASA models are large, integrated models that cover global systems. These models are not designed for digesting black swan sandwiches.  The Danish crisis management team has a solution worth for benchmarking for this problem as well. They have a specific small team that is called a Pandora’s Cell.  Pandora’s Cell is dedicated to anticipating, imagining, and scanning for potential not-so-obvious developments that should be taken into consideration in decision making. This dedicated team is needed because all the other resources available have been focused on the obvious events, as described in the square one of our comic strip.

dreamstime_xl_47204013

Black swan events refer to those that are unpredictable and difficult to plan for. © Wrangel | Dreamstime.com – Black Swan Photo

What do our models really represent?

By Dan Jessie, IIASA Research Scholar, Advanced Systems Analysis Program

As policymakers turn to the scientific community to inform their decisions on topics such as climate change, public health, and energy policy, scientists and mathematicians face the challenge of providing reliable information regarding trade-offs and outcomes for various courses of action. To generate this information, scientists use a variety of complex models and methods. However, how can we know whether the output of these models is valid?

This question was the focus of a recent conference I attended, arranged by IIASA Council Chair Donald G. Saari and the Institute for Mathematical Behavioral Sciences at the University of California, Irvine. The conference featured a number of talks by leading mathematicians and scientists who research complex systems, including Carl Simon, the founding Director of the University of Michigan’s Center for the Study of Complex Systems, and Simon Levin, Director of the Center for BioComplexity at Princeton University. All talks focused on answering the question, “Validation. What is it?”

To get a feel for how difficult this topic is, consider that during the lunch discussions,  each speaker professed to know less than everybody else! In spite of this self-claimed ignorance, each talk presented challenging new ideas regarding both specifics of how validation can be carried out for a given model, as well as formulations of general guidelines for what is necessary for validation.

How closely does a model need to mirror reality? © Mopic | Dreamstime.com - Binary Background Photo

How closely does a model need to mirror reality? © Mopic | Dreamstime.com – Binary Background Photo

For example, one talk discussed the necessity of understanding the connecting information between the pieces of a system. While it may seem obvious that, to understand a system built from many different components, one needs to understand both the pieces and how the pieces fit together, this talk contained a surprising twist: oftentimes, the methodology we use to model a problem unknowingly ignores this connecting information. By using examples from a variety of fields, such as social choice, nanotechnology, and astrophysics, the speaker showed how many current research problems can be understood in this light. This talk presented a big challenge to the research community to develop the appropriate tools for building valid models of complex systems.

Overall, the atmosphere of the conference was one of debate, and it seemed that no two speakers agreed completely on what validation required, or even meant. Some recurring questions in the arguments were how closely does a model need to mirror reality, and how do we assess predictions given that every model fails in some predictions? What role do funding agencies and peer review play in validation? The arguments generated by the talks weren’t limited to the conference schedule, either, and carried into the dinners and beyond.

I left the conference with a sense of excitement at seeing so many new ideas that challenge the current methods and models. This is still a new and growing topic, but one where advances will have wide-ranging impacts in terms of how we approach and answer scientific questions.

IIASA Council Chair Don Saari: Validation: What is it?

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

How can research help achieve resilience?

By Elisabeth Suwandschieff, Research Scholar, IIASA Ecosystems Services and Management Program

IMG_3114

Vienna, Austria

We live in a world that is fluid and diverse. Yet policymakers have to find solutions to problems that are definitive and effective, able to adapt to uncertain, changing, and challenging environments. How can research help policymakers to achieve such resilience?

At last week’s 4th Viennese Talks on Resilience and Networks, I listened to a number of talks on this topic from prominent figures in politics, military, research, and the private sector who came together to discuss future potential pathways for Austria. Speakers from politics emphasized the importance of social solutions such as greater investment in education. Meanwhile researchers from IIASA and other institutions brought perspective from systems analysis methods and explained how research on dynamic systems can inform policy making.

System dynamics view
From the research perspective, IIASA’s Brian Fath and others brought a systems analytical view of complex systems and their dynamics. They explained that complex systems such as organizations, businesses, and cities go through different stages in their “ecocycle.” Understanding the cycle and process is key to influencing its development.

FAS.research Director Harald Katzmair argued that life, as a complex system, can be seen as a process of growth, stagnation, destructurization and reorganization. In a recent research project, Katzmair found that the main factor in achieving resilience was the ability of the system to remain flexible through improvisation, collaboration, behavioral change and openness. If we apply this to our understanding of the world it becomes necessary to rethink our approach to leadership in every aspect.

“Our world is not a closed system; it does not consist of one choice, one idea, one currency,” said Katzmair.

Fath said that resilience is achieved by successfully managing each stage of the life cycle, explaining that even collapse can be seen as a key feature of system dynamics, because it results in developmental opportunities. Through disturbance and adaptive change in the landscape, new landscapes can be shaped.

Applying research to resilience
Many of the research talks were mathematical and complex. How can such research help in achieving resilience on a practical level? The issue for policymakers is that they have to provide definitive solutions when actually we live in a world that is fluid and diverse – therefore we need a diversified portfolio of problem solving. That is, solutions must be broad without losing focus. They must be effective, but remain flexible and open.

Research can bring different experiences together, provide a platform and a common language that can be shared. Systems thinking is a powerful way to condense the different ways of thinking and produce a portfolio of options rather than provide rigid solutions.

The adaptive cycle (Burkhard et al. 2011)

The adaptive cycle (Burkhard et al. 2011)

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Interview: Aquatic invaders and ecological networks

Danielle Haak, who recently completed her PhD from the Nebraska Cooperative Fish and Wildlife Research Unit and the School of Natural Resources at the University of Nebraska-Lincoln, has won the annual Peccei Award for her outstanding research as part of the 2014 Young Scientists Summer Program (YSSP) in IIASA’s Advanced Systems Analysis research program.

Haak_postYSSP_IcelandCould you tell me a bit about yourself? Where are you from and what do you study?
I grew up in Milwaukee, Wisconsin (USA), and it was there I fell in love with the natural world. As a kid, my family and I spent weekends boating on Lake Michigan, and I’ve always been fascinated by lakes and the hidden world beneath the water’s surface. As an undergraduate, I spent a few summers in northern Wisconsin at a limnology research station, and this is where I realized I could actually make a career out of this fascination! I went on to get a BSc in Wildlife Ecology, a MSc in Biological Sciences, and I recently defended my PhD dissertation that focused on the energetics and habitat requirements of the invasive freshwater Chinese mystery snail. In general, I’m interested in aquatic invasive species and how their introduction affects ecosystem structure, functioning, and resilience.

How did you get interested in this subject?
I was drawn to aquatic invasive species during my undergraduate research. My first independent research project was on invasive crayfish in a northern Wisconsin lake; in addition to out-competing the native crayfish population, the invasive species suffered from a fungal disease outbreak, and we wanted to understand its prevalence throughout the lake. I also worked as a technician on a whole-lake study researching the efficacy of manual removal of an invasive crayfish species from another lake. It was a long-term project that successfully reduced the invasive rusty crayfish population enough that the native crayfish population was able to recover, and the entire lake underwent a drastic physical change as a result. These large-scale dynamics have always been appealing to me, and I knew it was something I wanted to pursue in my career. When I started my PhD at the University of Nebraska-Lincoln, our research group had just started a number of side projects on the Chinese mystery snail, and there was an obvious gap in our scientific understanding of the species; thus, it made sense to take advantage of this opportunity!

What was the question you were trying to answer in your YSSP research project?
My YSSP project built upon my dissertation topic but went in a slightly different direction. My YSSP supervisor, Dr. Brian Fath, and I wanted to utilize the already-established methods of social and ecological network analyses, but in a way that hadn’t been done before. Ultimately, we had two main questions. First, we wanted to investigate how the social dynamics of ecosystems can be integrated into ecological network analysis. And second, we wanted to use network analysis to analyze the ecological effects and movement of the Chinese mystery snail in the southeast region of Nebraska.

What did you find?
Because there were a few parts to this research, we had a number of different results. First, we were able to create directed networks of how anglers and boaters moved among a network of flood-control reservoirs. We also developed ecological networks specific to each of the 19 reservoirs included in our study. Both of these findings were relevant by themselves, but the cool part was how we combined them. We adapted the framework of infectious disease network modeling to simulate what would happen within the first 25 years after a hypothetical introduction. The human movements connecting reservoirs were equivalent to a disease’s transmission rate, and the individual population growth of the snail within each reservoir after an introduction was like a disease’s incubation time leading up to a threshold where that reservoir then became contagious. We started with 5 infected and contagious reservoirs, and after 25 years only 5 of the 19 reservoirs did not have the Chinese mystery snail in it. Finally, we identified three of the already-infected reservoirs where preventing snails from being transported out of them would be most critical as well as two susceptible reservoirs where preventing introduction of the snails would be most beneficial.

Chinese Mystery Snail. Photo: Wisconsin Department of Natural Resources, Doug Jensen

Chinese Mystery Snail. Photo: Wisconsin Department of Natural Resources, Doug Jensen

Why is this research important for policy or society?
Our preliminary results demonstrated that social and ecological network models can be used in tandem, which has the potential to address a number of complex policy and management issues. Additionally, being able to prioritize reservoirs based on how effective prevention efforts would be allows managers to focus their limited resources in places they would get the best return on their investment. I believe there is also a great deal of potential in using this combined model approach to assess the spread of other aquatic invasive species of concern as well as other types of disturbances.  

How are you planning to continue this research when you return to IIASA?
I would like to work with Dr. Fath on refining some of my individual ecological network models, and possibly incorporating some of the additional social data that’s available to us. We also discussed possibly using the approach to look at other questions related to aquatic invasive species, but in different geographical regions and possibly with different software. One of the best parts of this project was coming up with so many questions on where we could go next, and I really enjoyed working with Dr. Fath and gaining a new perspective on the questions that interest me.

How did your time at IIASA affect your PhD research?
My time at IIASA refreshed my love of the scientific process, and I loved the flexibility in adjusting my project as I learned more and developed new questions. Ultimately, I ended up with an additional chapter for my dissertation and came home with a mostly-completed draft.

What was your favorite aspect of the YSSP and IIASA?
I loved so much about YSSP and working at IIASA, but the best part was probably the ability to meet other brilliant scientists and students from around the world. In addition to thought-provoking discussions on science and research, we also had some incredible discussions on life in other countries with drastically different cultures. The other students made the entire summer even better, and I’m so happy I was able to participate in such an incredible experience. IIASA has a truly unique work environment, and everyone made us feel right at home. It really was a dream come true, and I’m so excited about the opportunity to return and pick up where I left off. The only thing missing will be my fellow YSSPers! I wish we could all come back every summer!

What was your favorite moment of the summer?
I think my favorite experience was the end of summer workshop and dinner and dance that followed. I was so impressed during the initial presentations and it was great to hear about all the progress that was made in the short three months. Celebrating this progress with a night of dancing and dining was just the perfect ending to a great summer. It was a bittersweet farewell, but I think it cemented our friendships and was a great capstone to an already dreamlike experience!

Photo credit: Danielle Haak

Danielle Haak (right) and fellow YSSPer Adriana Reyes, at the end-of-summer awards ceremony.

Note: This article gives the views of the interviewee, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.