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Feb 08, 2013

Social sciences get into the Cloud

Scientific disciplines are usually classified in two broad categories: natural sciences and social sciences. Natural sciences investigate the physical, chemical and biological aspects of Earth, the Universe and the life forms that inhabit it. Social sciences (also defined human sciences) focus on the origin and development of human beings, societies, institutions, social relationships etc.

Natural sciences are often regarded as “hard” research disciplines, because they are based on precise numeric predictions about experimental data. Social sciences, on the other hand, are seen as “soft” because they tend to rely on more descriptive approaches to understand their object of study.

So, for example, while it has been possible to predict the existence and properties of the Higgs boson from the Standard Model of particle physics, it is not possible to predict the existence and properties of a psychological effect or phenomenon, at least with the same level of precision.

However, the most important difference between natural and social sciences is not in their final objective (since in both fields, hypotheses must be tested by empirical approaches), but in the methods and tools that they use to pursue that objective. Galileo Galilei argued that we cannot understand the universe “(…) if we do not first learn the language and grasp the symbols, in which it is written. This book is written in the mathematical language, and the symbols are triangles, circles and other geometrical figures, without whose help it is impossible to comprehend a single word of it; without which one wanders in vain through a dark labyrinth.”


But unlike astronomy, physics and chemistry, which are able to read the “book of nature” using increasingly sophisticated glasses (such as microscopes, telescopes, etc.), social sciences have no such tools to investigate social and mental processes within their natural contexts. To understand these phenomena, researchers can either focus on macroscopic aggregates of behaviors (i.e. sociology) or analyse microscopic aspects within controlled settings (i.e. psychology).

Despite these limitations, there is no doubt that social sciences have produced interesting findings: today we know much more about the human being than we did a century ago. But at the same time, advances in natural sciences have been far more impressive and groundbreaking. From the discovery of atomic energy to the sequencing of human genome, natural sciences have changed our life and could do it even more in the next decades.

However, thanks to the explosive growth of information and communication technologies, this state of things may change soon and lead to a paradigm shift in the way social phenomena are investigated. Actually, thanks to the pervasive diffusion of Internet and mobile computing devices, most of our daily activities leave a digital footprint, which provide data on what we have done and with whom.

Every single hour of our life produces an observable trace, which can be translated into numbers and aggregated to identify specific patterns or trends that would be otherwise impossible to quantify.

Thanks to the emergence of cloud computing, we are now able to collect these digital footprints in large online databases, which can be accessed by researchers for scientific purposes. These databases represent for social scientists the “book written in the mathematical language”, which they can eventually read. An enormous amount of data is already available - embedded in online social networks, organizations digital archives, or saved in the internal memory of our smartphones/tablets/PCs – although it is not always accessible (because within the domain of private companies and government agencies).


Social scientists are starting to realize that the advent of “big data” is offering unprecedented opportunities for advancing their disciplines. For example, Lazer and coll. recently published on Science (2009, 323:5915, pp. 721-723) a sort of “manifesto” of Computational Social Science, in which they explain the potential of this approach in collecting and analyzing data at a scale that may reveal patterns of individual and group behaviors.

However, in order to exploit this potential, social scientists have to open their minds to learn new tools, methods and approaches. Actually, the ability to analyse and make sense of huge quantities of data that change over time require mathematics and informatics skills that are usually not included in the training of the average social scientist. But acquiring new mathematical competences may not be enough. The majority of research psychologists, for example, is not familiar with using new technologies such as mobile computing tools, sensors or virtual environments. However, these tools may become the equivalent in psychology to what microscopes are for biology or telescopes are for astronomy.

If social scientists will open their minds to this new horizon, their impact on society could be at least as revolutionary as the one that natural scientists have produced in the last two centuries. The emergence of computational social science will not only allow scientists to predict many social phenomena, but also to unify levels of analysis that have been until now separately addressed, e.g. the neuro-psychological and the psycho-social levels. 

At the same time, the transformative potential of this emerging science requires also a careful reflection on its ethical implications for the protection of privacy of participants.   

18:29 Posted in Research tools | Permalink | Comments (0)

IEEE Special Issue: Technologies for Affect and Wellbeing

Technologies for Affect and Wellbeing- Special Issue of theIEEE Transaction on Affective Computing.

Guest Editors

  • Rafael A. Calvo (The University of Sydney)
  • Giuseppe Riva (ICE-NET Lab- Universitta Catolica del Sacro Cuore, Milan Italy)
  • Christine Lisetti (Florida International University)

Background and Motivation
There is an increased interest in using computer interaction to detect and support users’ physical and psychological wellbeing.  Computers can afford multiple forms of transformational experiences. Some of these experiences can be purposely designed to, for example, detect and regulate students’ affective states to improve aspects of their learning experiences. They can also be used in computer-based psychological interventions that treat psychological illness or that preventively promote wellbeing, healthy lifestyles, and mental health.
The application domain, so far referred to as ‘positive computing’, ‘positive technologies’, and ‘positive design’, draws on ideas from positive psychology, particularly the extensive research on developing human strengths and wellbeing. It is closely linked to the HCI work on personal informatics, and the development of tools that help people learn more about themselves through reflection.
This special issue will focus on ideas, methods and case studies for how affective computing can contribute to this goal. Articles should discuss how information that computers collect about our behaviour, cognition – and particularly affect can be used in the further understanding, nurturing or development of wellbeing and human strengths: e.g. self-understanding, empathy, intrinsic motivation toward wellbeing healthy lifestyles.

Topics include, but are not limited to:

  • Systems to detect or support positive emotions and human strengths for example Reflection, Empathy, Happiness, Gratitude, Self-understanding/ interpersonal skills, Emotional intelligence/ emotion regulation, Social intelligence/ intrapersonal skills, Motivation.
  • Using affect and motivation for physical and psychological health.
  • Cyberpsychology for positive psychology and wellbeing
  • HCI design strategies for support of wellbeing and human strengths
  • Virtual Reality for support of wellbeing or human strengths
  • Positive personal health informatics for health promotion
  • Patient-centered technologies for healthy behaviour change
  • Empathic intelligent virtual agents for lifestyle monitoring and behaviour change
  • Mobile applications of affective computing for health and wellbeing
  • Informatics technologies for patient empowerment


  • Call for Papers out: Feb 2013
  • Submission Deadline:  July 1st, 2013
  • Notification of Acceptance:  October 1st, 2013
  • Final Manuscripts Due:  December 1st, 2013
  • Date of Publication: March or July 2014

Review process

The Transactions on Affective Computing Special Issue on “Affect and wellbeing” will consist of papers on techniques, methods, case studies and their evaluation. Some papers may survey various aspects of the topic, particularly in ways that bring the psychological, health and wellbeing, and technical literature together. The balance between these will be adjusted to maximize the impact of the special issue. All articles are expected to follow the standard review procedures for the IEEE TAC.

The Human Brain Project awarded $1.6 billion by the EU

At the end of January, the European Commission has officially announced the selection of the Human Brain Project (HBP) as one of its two FET Flagship projects. Federating more than 80 European and international research institutions, the Human Brain Project is planned to last ten years (2013-2023). The cost is estimated at 1.19 billion euros.


The project is the first attempt to “reconstruct the brain piece by piece and building a virtual brain in a supercomputer”. Lead by neuroscientist Henry Markram, the project was launched in 2005 as a joint research initiative between the Brain Mind Institute at the École Polytechnique Fédérale de Lausanne (EPFL) and the information technology giant IBM.


Using the impressive processing power of IBM’s Blue Gene/L supercomputer, the project reached its first milestone in December 2006, simulating a rat cortical column. As of July 2012, Henry Markram’s team has achieved the simulation of mesocircuits containing approximately 1 million neurons and 1 billion synapses (which is comparable with the number of nerve cells present in a honey bee brain). The next step, planned in 2014, will be the modelling of a cellular rat brain, with 100 mesocircuits totalling a hundred million cells. Finally, the team plans to simulate a full human brain (86 billion neurons) by the year 2023

Watch the video overview of the Human Brain Project