Computational Propaganda and Political Big Data: Moving Toward a More Critical Research Agenda

Curated on Posted on by Stefaan Verhulst

Gillian Bolsover and Philip Howard in the Journal Big Data: “Computational propaganda has recently exploded into public consciousness. The U.S. presidential campaign of 2016 was marred by evidence, which continues to emerge, of targeted political propaganda and the use of bots to distribute political messages on social media. This computational propaganda is both a social and technical phenomenon. Technical knowledge is necessary to work with the massive databases used for audience targeting; it is necessary to create the bots and algorithms that distribute propaganda; it is necessary to monitor and evaluate the results of these efforts in agile campaigning. Thus, a technical knowledge comparable to those who create and distribute this propaganda is necessary to investigate the phenomenon.

However, viewing computational propaganda only from a technical perspective—as a set of variables, models, codes, and algorithms—plays into the hands of those who create it, the platforms that serve it, and the firms that profit from it. The very act of making something technical and impartial makes it seem inevitable and unbiased. This undermines the opportunities to argue for change in the social value and meaning of this content and the structures in which it exists. Big-data research is necessary to understand the socio-technical issue of computational propaganda and the influence of technology in politics. However, big data researchers must maintain a critical stance toward the data being used and analyzed so as to ensure that we are critiquing as we go about describing, predicting, or recommending changes. If research studies of computational propaganda and political big data do not engage with the forms of power and knowledge that produce it, then the very possibility for improving the role of social-media platforms in public life evaporates.

Definitionally, computational propaganda has two important parts: the technical and the social. Focusing on the technical, Woolley and Howard define computational propaganda as the assemblage of social-media platforms, autonomous agents, and big data tasked with the manipulation of public opinion. In contrast, the social definition of computational propaganda derives from the definition of propaganda—communications that deliberately misrepresent symbols, appealing to emotions and prejudices and bypassing rational thought, to achieve a specific goal of its creators—with computational propaganda understood as propaganda created or disseminated using computational (technical) means…(More) (Full Text HTML; Full Text PDF)

From #Resistance to #Reimagining governance

Curated on Posted on by Stefaan Verhulst

Stefaan G. Verhulst in Open Democracy: “…There is no doubt that #Resistance (and its associated movements) holds genuine transformative potential. But for the change it brings to be meaningful (and positive), we need to ask the question: What kind of government do we really want?

Working to maintain the status quo or simply returning to, for instance, a pre-Trump reality cannot provide for the change we need to counter the decline in trust, the rise of populism and the complex social, economic and cultural problems we face. We need a clear articulation of alternatives.  Without such an articulation, there is a danger of a certain hollowness and dispersion of energies. The call for #Resistance requires a more concrete –and ultimately more productive – program that is concerned not just with rejecting or tearing down, but with building up new institutions and governance processes. What’s needed, in short, is not simply #Resistance.

Below, I suggest six shifts that can help us reimagine governance for the twenty-first century. Several of these shifts are enabled by recent technological changes (e.g., the advent of big data, blockchain and collective intelligence) as well as other emerging methods such as design thinking, behavioral economics, and agile development.

Some of the shifts I suggest have been experimented with, but they have often been developed in an ad hoc manner without a full understanding of how they could make a more systemic impact. Part of the purpose of this paper is to begin the process of a more systematic enquiry; the following amounts to a preliminary outline or blueprint for reimagined governance for the twenty-first century.

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  • Shift 1: from gatekeeper to platform…
  • Shift 2: from inward to user-and-problem orientation…
  • Shift 3: from closed to open…
  • Shift 4: from deliberation to collaboration and co-creation…
  • Shift 5: from ideology to evidence-based…
  • Shift 6: from centralized to distributed… (More)

Code and Clay, Data and Dirt: Five Thousand Years of Urban Media

Curated on Posted on by Stefaan Verhulst

Book by Shannon Mattern: “For years, pundits have trumpeted the earthshattering changes that big data and smart networks will soon bring to our cities. But what if cities have long been built for intelligence, maybe for millennia? In Code and Clay, Data and Dirt Shannon Mattern advances the provocative argument that our urban spaces have been “smart” and mediated for thousands of years.

Offering powerful new ways of thinking about our cities, Code and Clay, Data and Dirt goes far beyond the standard historical concepts of origins, development, revolutions, and the accomplishments of an elite few. Mattern shows that in their architecture, laws, street layouts, and civic knowledge—and through technologies including the telephone, telegraph, radio, printing, writing, and even the human voice—cities have long negotiated a rich exchange between analog and digital, code and clay, data and dirt, ether and ore.

Mattern’s vivid prose takes readers through a historically and geographically broad range of stories, scenes, and locations, synthesizing a new narrative for our urban spaces. Taking media archaeology to the city’s streets, Code and Clay, Data and Dirt reveals new ways to write our urban, media, and cultural histories….(More)”.

Business Models For Sustainable Research Data Repositories

Curated on Posted on by Stefaan Verhulst

OECD Report: “In 2007, the OECD Principles and Guidelines for Access to Research Data from Public Funding were published and in the intervening period there has been an increasing emphasis on open science. At the same time, the quantity and breadth of research data has massively expanded. So called “Big Data” is no longer limited to areas such as particle physics and astronomy, but is ubiquitous across almost all fields of research. This is generating exciting new opportunities, but also challenges.

The promise of open research data is that they will not only accelerate scientific discovery and improve reproducibility, but they will also speed up innovation and improve citizen engagement with research. In short, they will benefit society as a whole. However, for the benefits of open science and open research data to be realised, these data need to be carefully and sustainably managed so that they can be understood and used by both present and future generations of researchers.

Data repositories – based in local and national research institutions and international bodies – are where the long-term stewardship of research data takes place and hence they are the foundation of open science. Yet good data stewardship is costly and research budgets are limited. So, the development of sustainable business models for research data repositories needs to be a high priority in all countries. Surprisingly, perhaps, little systematic analysis has been done on income streams, costs, value propositions, and business models for data repositories, and that is the gap this report attempts to address, from a science policy perspective…..

This project was designed to take up the challenge and to contribute to a better understanding of how research data repositories are funded, and what developments are occurring in their funding. Central questions included:

  • How are data repositories currently funded, and what are the key revenue sources?
  • What innovative revenue sources are available to data repositories?
  • How do revenue sources fit together into sustainable business models?
  • What incentives for, and means of, optimising costs are available?
  • What revenue sources and business models are most acceptable to key stakeholders?…(More)”

Big data in social and psychological science: theoretical and methodological issues

Curated on Posted on by Stefaan Verhulst

Paper by Lin Qiu, Sarah Hian May Chan and David Chan in the Journal of Computational Social Science: “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)”.

A New City O/S: The Power of Open, Collaborative, and Distributed Governance

Curated on Posted on by Stefaan Verhulst

Book by Stephen Goldsmith and Neil Kleiman: “At a time when trust is dropping precipitously and American government at the national level has fallen into a state of long-term, partisan-based gridlock, local government can still be effective—indeed more effective and even more responsive to the needs of its citizens. Based on decades of direct experience and years studying successful models around the world, the authors of this intriguing book propose a new operating system (O/S) for cities. Former mayor and Harvard professor Stephen Goldsmith and New York University professor Neil Kleiman suggest building on the giant leaps that have been made in technology, social engagement, and big data.

Calling their approach “distributed governance,” Goldsmith and Kleiman offer a model that allows public officials to mobilize new resources, surface ideas from unconventional sources, and arm employees with the information they need to become pre-emptive problem solvers. This book highlights lessons from the many innovations taking place in today’s cities to show how a new O/S can create systemic transformation.

For students of government, A New City O/S: The Power of Distributed Governance presents a groundbreaking strategy for rethinking the governance of cities, marking an important evolution of the current bureaucratic authority-based model dating from the 1920s. More important, the book is designed for practitioners, starting with public-sector executives, managers, and frontline workers. By weaving real-life examples into a coherent model, the authors have created a step-by-step guide for all those who would put the needs of citizens front and center. Nothing will do more to restore trust in government than solutions that work. A New City O/S: The Power of Distributed Governanceputs those solutions within reach of those public officials responsible for their delivery….(More)”.

‘Big Data’ Tells Thailand More About Jobs Than Low Unemployment

Curated on Posted on by Stefaan Verhulst

Suttinee Yuvejwattana at Bloomberg: “Thailand has one of the lowest unemployment rates in the world, which doesn’t always fit the picture of an emerging-market economy that’s struggling to get growth going.

 To get a fuller picture of what’s happening in the labor market — as well as in other under-reported industries in the economy, like the property market — the central bank is increasingly turning to “big data” sources drawn from social media and online stores to supplement official figures.

The Bank of Thailand is building its own employment index based on data from online jobs-search portals and is also creating a property indicator to give it a better sense of supply and demand in the housing market.

“We want to do evidence-based policy so big data is useful,” Jaturong Jantarangs, an assistant governor at the Bank of Thailand, said in an interview in Bangkok. “It’s not only a benefit to monetary policy but financial policy as well.”…

“Official data can’t capture the whole picture of the economy,” said Somprawin Manprasert, Bangkok-based head of research at Bank of Ayudhya Pcl. “We have a big informal sector. Many people are self-employed. This leads to a low unemployment rate.”

“The big data can show all aspects, so it can help us to solve the problems where they are,” he said…

Thailand’s military administration is also trying to harness big data to improve policy decisions, Digital Economy and Society Minister Pichet Durongkaveroj said in an interview last month. Pichet said he’s been tasked to look into digitizing, integrating and analyzing information across more than 200 government departments.

Santitarn Sathirathai, head of emerging Asia economics at Credit Suisse Group AG in Singapore, said big data analytics can be used to better target policy responses as well as allow timely evaluation of past programs. At the same time, he called on authorities to make their data more readily available to the public.

“The government should not just view big data analytics as being solely about it using richer data but also about creating a more open data environment,” he said. That’s to ensure “people can have better access to many government non-sensitive datasets and help conduct analysis that could complement the policy makers,” he said….(More)”.

What Are Data? A Categorization of the Data Sensitivity Spectrum

Curated on Posted on by Stefaan Verhulst

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)”.

Democracy is dead: long live democracy!

Curated on Posted on by Stefaan Verhulst

Helen Margetts in OpenDemocracy: “In the course of the World Forum for Democracy 2017, and in political commentary more generally, social media are blamed for almost everything that is wrong with democracy. They are held responsible for pollution of the democratic environment through fake news, junk science, computational propaganda and aggressive micro-targeting. In turn, these phenomena have been blamed for the rise of populism, political polarization, far-right extremism and radicalisation, waves of hate against women and minorities, post-truth, the end of representative democracy, fake democracy and ultimately, the death of democracy. It feels like the tirade of relatives of the deceased at the trial of the murderer. It is extraordinary how much of this litany is taken almost as given, the most gloomy prognoses as certain visions of the future.

Yet actually we know rather little about the relationship between social media and democracy. Because ten years of the internet and social media have challenged everything we thought we knew.  They have injected volatility and instability into political systems, bringing a continual cast of unpredictable events. They bring into question normative models of democracy – by which we might understand the macro-level shifts at work  – seeming to make possible the highest hopes and worst fears of republicanism and pluralism.

They have transformed the ecology of interest groups and mobilizations. They have challenged élites and ruling institutions, bringing regulatory decay and policy sclerosis. They create undercurrents of political life that burst to the surface in seemingly random ways, making fools of opinion polls and pollsters. And although the platforms themselves generate new sources of real-time transactional data that might be used to understand and shape this changed environment, most of this data is proprietary and inaccessible to researchers, meaning that the revolution in big data and data science has passed by democracy research.

What do we know? The value of tiny acts

Certainly digital media are entwined with every democratic institution and the daily lives of citizens. When deciding whether to vote, to support, to campaign, to demonstrate, to complain – digital media are with us at every step, shaping our information environment and extending our social networks by creating hundreds or thousands of ‘weak ties’, particularly for users of social media platforms such as Facebook or Instagram….(More)”.

Technopolitics in the Age of Big Data

Curated on Posted on by Stefaan Verhulst

Chapter by Stefania Milan and Miren Gutierrez in the book on Networks, Movements and Technopolitics in Latin America: ‘Big data’ offer novel opportunities for civic engagement and foster the emergence of data activism, a form of technopolitics from the ground–up that assumes people’s active engagement with data for empowerment. Proactive data activism, in particular, sees citizens taking advantage of the possibilities offered by data for advocacy and social change. This chapter combines social movement studies and media studies to analyze the emergence of proactive data activism in the Latin American continent. Analyzing the case of InfoAmazonia—a project blending citizen participation and data analysis to generate news about the endangered Amazon region—this chapter adds to our understanding of technopolitics as a way to reinterpret reality, empower people, facilitate collective action, and challenge the establish social norms embedded in our understanding of technology and social change. Furthermore, it contributes to the understanding of how data can restructure social reality, and in particular civil society action….(More) (Other chapters)”.