Big data presents unprecedented opportunities to understand human behavior on a large scale. It has been increasingly used in social and psychological research to reveal individual differences and group dynamics. There are a few theoretical and methodological challenges in big data research that require attention. In this paper, we highlight four issues, namely data-driven versus theory-driven approaches, measurement validity, multi-level longitudinal analysis, and data integration. They represent common problems that social scientists often face in using big data. We present examples of these problems and propose possible solutions….(More)”.
Analyzing the Role of the Internet-of-Things in Business and Technologically-Smart Cities
Paper by A. Shinn, K. Nakatani, and W. Rodriguez in the International Journal of Internet of Things: “This research analyzes and theorizes on the role that the Internet-of-Things will play in the expansion of business and technologically-smart cities. This study examines: a) the underlying technology, referred to as the Internet of Things that forms the foundation for smart cities; b) what businesses and government must do to successfully transition to a technologically-smart city; and c) how the proliferation of the Internet of Things through the emerging cities will affect local citizens. As machine-to-machine communication becomes increasingly common, new use cases are continually created, as is the case with the use of the Internet of Things in technologically-smart cities. Technology businesses are keeping a close pulse on end-users’ needs in order to identify and create technologies and systems to cater to new use cases. A number of the international smart city-specific use cases will be discussed in this paper along with the technology that aligns to those use cases….(More)”.
Blockchain: Unpacking the disruptive potential of blockchain technology for human development.
IDRC white paper: “In the scramble to harness new technologies to propel innovation around the world, artificial intelligence, robotics, machine learning, and blockchain technologies are being explored and deployed in a wide variety of contexts globally.
Although blockchain is one of the most hyped of these new technologies, it is also perhaps the least understood. Blockchain is the distributed ledger — a database that is shared across multiple sites or institutions to furnish a secure and transparent record of events occurring during the provision of a service or contract — that supports cryptocurrencies (digital assets designed to work as mediums of exchange).
Blockchain is now underpinning applications such as land registries and identity services, but as its popularity grows, its relevance in addressing socio-economic gaps and supporting development targets like the globally-recognized UN Sustainable Development Goals is critical to unpack. Moreover, for countries in the global South that want to be more than just end users or consumers, the complex infrastructure requirements and operating costs of blockchain could prove challenging. For the purposes of real development, we need to not only understand how blockchain is workable, but also who is able to harness it to foster social inclusion and promote democratic governance.
This white paper explores the potential of blockchain technology to support human development. It provides a non-technical overview, illustrates a range of applications, and offers a series of conclusions and recommendations for additional research and potential development programming….(More)”.
Decoding Data Use: What evidence do world leaders want to achieve their goals?
Paper by Samantha Custer, Takaaki Masaki, and Carolyn Iwicki: “Information is “never the hero”, but it plays a supporting role in how leaders allocate scarce resources and accelerate development in their communities. Even in low- and middle-income countries, decision-makers have ample choices in sourcing evidence from a growing field of domestic and international data providers. However, more information is not necessarily better if it misses the mark for what leaders need to monitor their country’s progress. Claims that information is the “world’s most valuable resource” and calls for a “data revolution” will ring hollow if we can’t decode what leaders actually use — and why.
In a new report, Decoding Data Use: How leaders source data and use it to accelerate development, AidData reveals what 3500 leaders from 126 countries have to say about the types of data or analysis they use, from what sources, and for which purposes in the context of their work. We analyze responses to AidData’s 2017 Listening to Leaders (LTL) Survey to offer insights to help funders, producers, advocates, and infomediaries of development data understand how to position themselves for greater impact….(more)”.
The social preferences of local citizens and spontaneous volunteerism during disaster relief operations
Paper by Samuel Roscoe et al: “Existing studies on disaster relief operations (DRO) pay limited attention to acts of spontaneous volunteerism by local citizens in the aftermath of disasters. The purpose of this paper is to explore how social preferences motivate citizens to help during post-disaster situations; above and beyond their own self-regarding interests. The paper begins by synthesizing the literature on social preferences from the field of behavioral economics and social psychology with the discourse surrounding behavioral operations management and humanitarian operations management (HOM). By doing so, we identify the motivators, enablers and barriers of local citizen response during disaster relief operations. These factors inform a theoretical framework of the social preferences motivating spontaneous volunteerism in post-disaster situations. We evidence facets of the framework using archival and unstructured data retrieved from Twitter feeds generated by local citizens during the floods that hit Chennai, India in 2015. Our model highlights the importance of individual level action during disaster relief operations and the enabling role of social media as a coordination mechanism for such efforts….(More)”.
Democracy in the digital age: digital agora or dystopia
Paper by Peter Parycek, Bettina Rinnerbauer, and Judith Schossböck in the International Journal of Electronic Governance: “Information and communication technologies (ICTs) affect democracy and the rule of law. Digitalisation has been perceived as a stimulus towards a more participative society or as support to decision making, but not without criticism. Authors draw on a legal review, case studies and quantitative survey data about citizens’ view on transparency and participation in the German-speaking region to summarise selected discourses of democratisation via ICTs and the dominant critique. The paper concludes with an outlook on contemporary questions of digital democracy between the dialectic of protecting citizens’ rights and citizen control. It is proposed that prospective e-participation projects will concentrate on processes of innovation and creativity as opposed to participation rates. Future investigations should evaluate the contexts in which a more data-driven, automated form of decision making could be supported and collect indicators for where to draw the line between the protection and control of citizens, including research on specific tools…(More).
Stewardship in the “Age of Algorithms”
Clifford Lynch at First Monday: “This paper explores pragmatic approaches that might be employed to document the behavior of large, complex socio-technical systems (often today shorthanded as “algorithms”) that centrally involve some mixture of personalization, opaque rules, and machine learning components. Thinking rooted in traditional archival methodology — focusing on the preservation of physical and digital objects, and perhaps the accompanying preservation of their environments to permit subsequent interpretation or performance of the objects — has been a total failure for many reasons, and we must address this problem.
The approaches presented here are clearly imperfect, unproven, labor-intensive, and sensitive to the often hidden factors that the target systems use for decision-making (including personalization of results, where relevant); but they are a place to begin, and their limitations are at least outlined.
Numerous research questions must be explored before we can fully understand the strengths and limitations of what is proposed here. But it represents a way forward. This is essentially the first paper I am aware of which tries to effectively make progress on the stewardship challenges facing our society in the so-called “Age of Algorithms;” the paper concludes with some discussion of the failure to address these challenges to date, and the implications for the roles of archivists as opposed to other players in the broader enterprise of stewardship — that is, the capture of a record of the present and the transmission of this record, and the records bequeathed by the past, into the future. It may well be that we see the emergence of a new group of creators of documentation, perhaps predominantly social scientists and humanists, taking the front lines in dealing with the “Age of Algorithms,” with their materials then destined for our memory organizations to be cared for into the future…(More)”.
What Are Data? A Categorization of the Data Sensitivity Spectrum
Paper by John M.M. Rumbold and Barbara K. Pierscionek in Big Data Research: “The definition of data might at first glance seem prosaic, but formulating a definitive and useful definition is surprisingly difficult. This question is important because of the protection given to data in law and ethics. Healthcare data are universally considered sensitive (and confidential), so it might seem that the categorisation of less sensitive data is relatively unimportant for medical data research. This paper will explore the arguments that this is not necessarily the case and the relevance of recognizing this.
The categorization of data and information requires re-evaluation in the age of Big Data in order to ensure that the appropriate protections are given to different types of data. The aggregation of large amounts of data requires an assessment of the harms and benefits that pertain to large datasets linked together, rather than simply assessing each datum or dataset in isolation. Big Data produce new data via inferences, and this must be recognized in ethical assessments. We propose a schema for a granular assessment of data categories. The use of schemata such as this will assist decision-making by providing research ethics committees and information governance bodies with guidance about the relative sensitivities of data. This will ensure that appropriate and proportionate safeguards are provided for data research subjects and reduce inconsistency in decision making…(More)”.
Crowdsourcing: a new tool for policy-making?
Paper byCrowdsourcing is rapidly evolving and applied in situations where ideas, labour, opinion or expertise of large groups of people is used. Crowdsourcing is now used in various policy-making initiatives; however, this use has usually focused on open collaboration platforms and specific stages of the policy process, such as agenda-setting and policy evaluations. Other forms of crowdsourcing have been neglected in policy-making, with a few exceptions. This article examines crowdsourcing as a tool for policy-making and explores the nuances of the technology and its use and implications for different stages of the policy process. The article addresses questions surrounding the role of crowdsourcing and whether it can be considered as a policy tool or as a technological enabler and investigates the current trends and future directions of crowdsourcing….(More)”
Influenzanet: Citizens Among 10 Countries Collaborating to Monitor Influenza in Europe
Paper by Carl E Koppeschaar et al in the Special Issue of JMIR Public Health and Surveillance on Participatory Disease Surveillance: “The wide availability of the Internet and the growth of digital communication technologies have become an important tool for epidemiological studies and health surveillance. Influenzanet is a participatory surveillance system monitoring the incidence of influenza-like illness (ILI) in Europe since 2003. It is based on data provided by volunteers who self-report their symptoms via the Internet throughout the influenza season and currently involves 10 countries.
Objective: In this paper, we describe the Influenzanet system and provide an overview of results from several analyses that have been performed with the collected data, which include participant representativeness analyses, data validation (comparing ILI incidence rates between Influenzanet and sentinel medical practice networks), identification of ILI risk factors, and influenza vaccine effectiveness (VE) studies previously published. Additionally, we present new VE analyses for the Netherlands, stratified by age and chronic illness and offer suggestions for further work and considerations on the continuity and sustainability of the participatory system.
Methods: Influenzanet comprises country-specific websites where residents can register to become volunteers to support influenza surveillance and have access to influenza-related information. Participants are recruited through different communication channels. Following registration, volunteers submit an intake questionnaire with their postal code and sociodemographic and medical characteristics, after which they are invited to report their symptoms via a weekly electronic newsletter reminder. Several thousands of participants have been engaged yearly in Influenzanet, with over 36,000 volunteers in the 2015-16 season alone.
Results: In summary, for some traits and in some countries (eg, influenza vaccination rates in the Netherlands), Influenzanet participants were representative of the general population. However, for other traits, they were not (eg, participants underrepresent the youngest and oldest age groups in 7 countries). The incidence of ILI in Influenzanet was found to be closely correlated although quantitatively higher than that obtained by the sentinel medical practice networks. Various risk factors for acquiring an ILI infection were identified. The VE studies performed with Influenzanet data suggest that this surveillance system could develop into a complementary tool to measure the effectiveness of the influenza vaccine, eventually in real time.
Conclusions: Results from these analyses illustrate that Influenzanet has developed into a fast and flexible monitoring system that can complement the traditional influenza surveillance performed by sentinel medical practices. The uniformity of Influenzanet allows for direct comparison of ILI rates between countries. It also has the important advantage of yielding individual data, which can be used to identify risk factors. The way in which the Influenzanet system is constructed allows the collection of data that could be extended beyond those of ILI cases to monitor pandemic influenza and other common or emerging diseases….(More)”. (see also https://www.influenzanet.eu/)