This book brings together the theory and practice of managing public trust. It examines the current state of public trust, including a comprehensive global overview of both the research and practical applications of managing public trust by presenting research from seven countries (Brazil, Finland, Poland, Hungary, Portugal, Taiwan, Turkey) from three continents. The book is divided into five parts, covering the meaning of trust, types, dimension and the role of trust in management; the organizational challenges in relation to public trust; the impact of social media on the development of public trust; the dynamics of public trust in business; and public trust in different cultural contexts….(More)”.
Social media and Government
Introduction to Special Issue of First Monday by Rodrigo Sandoval-Almazan and Andrea L. Kavanaugh: “The use of social media by public administration has been growing steadily, and fostering important transformations in organization, costs, citizen interaction and efficiency. Citizens are increasingly more informed about government activities, performance, and claims solutions. Citiizens and non-profit organizations are in greater communication with each other about government planning and response to complex and collective problems. Social media, such as Facebook, Twitter, You Tube and WhatsApp, as well as related tools, such as commenting, liking, tagging and rating, change the distribution of information, power and resources. The growing maturity of public officials in the use of these tools not only creates new opportunities, but also engenders problems. Many politicians, public officials and public servants are seeking ways to adapt their daily operations and practices to make effective use of social media for interaction with non-governmental organizations and with citizens and to provide information and services more efficiently. The papers in this special issue on social media and government capture the current state of some of these opportunities and problems…
Engaging a community through social media-based topics and interactions by Andrea L. Kavanaugh, Ziqian Song
Public employees in social media communities: Exploring factors for internal collaboration using social network analysis by J. Ignacio Criado, Julián Villodre
Citizens’ use of microblogging and government communication during emergencies: A case study on water contamination in Shanghai by Qianli Yuan, Mila Gascó
Hacktivism and distributed hashtag spoiling on Twitter: Tales of the #IranTalks by Mahdi M. Najafabadi, Robert J. Domanski
Information strategies and affective reactions: How citizens interact with government social media content by Nic DePaula, Ersin Dincelli
Towards an understanding of Twitter networks: The case of the state of Mexico by Rodrigo Sandoval-Almazán, David Valle-Cruz”
TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications
Paper by Daniel G. Costa et al in Sensors: “Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve.
In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter, and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events….(More)”.
On Digital Passages and Borders: Refugees and the New Infrastructure for Movement and Control
Paper by Mark Latonero and Paula Kift: “Since 2014, millions of refugees and migrants have arrived at the borders of Europe. This article argues that, in making their way to safe spaces, refugees rely not only on a physical but increasingly also digital infrastructure of movement. Social media, mobile devices, and similar digitally networked technologies comprise this infrastructure of “digital passages”—sociotechnical spaces of flows in which refugees, smugglers, governments, and corporations interact with each other and with new technologies. At the same time, a digital infrastructure for movement can just as easily be leveraged for surveillance and control. European border policies, in particular, instantiate digital controls over refugee movement and identity. We review the actors, technologies, and policies of movement and control in the EU context and argue that scholars, policymakers, and the tech community alike should pay heed to the ethics of the use of new technologies in refugee and migration flows….(More)”.
How Democracy Can Survive Big Data
Colin Koopman in The New York Times: “…The challenge of designing ethics into data technologies is formidable. This is in part because it requires overcoming a century-long ethos of data science: Develop first, question later. Datafication first, regulation afterward. A glimpse at the history of data science shows as much.
The techniques that Cambridge Analytica uses to produce its psychometric profiles are the cutting edge of data-driven methodologies first devised 100 years ago. The science of personality research was born in 1917. That year, in the midst of America’s fevered entry into war, Robert Sessions Woodworth of Columbia University created the Personal Data Sheet, a questionnaire that promised to assess the personalities of Army recruits. The war ended before Woodworth’s psychological instrument was ready for deployment, but the Army had envisioned its use according to the precedent set by the intelligence tests it had been administering to new recruits under the direction of Robert Yerkes, a professor of psychology at Harvard at the time. The data these tests could produce would help decide who should go to the fronts, who was fit to lead and who should stay well behind the lines.
The stakes of those wartime decisions were particularly stark, but the aftermath of those psychometric instruments is even more unsettling. As the century progressed, such tests — I.Q. tests, college placement exams, predictive behavioral assessments — would affect the lives of millions of Americans. Schoolchildren who may have once or twice acted out in such a way as to prompt a psychometric evaluation could find themselves labeled, setting them on an inescapable track through the education system.
Researchers like Woodworth and Yerkes (or their Stanford colleague Lewis Terman, who formalized the first SAT) did not anticipate the deep consequences of their work; they were too busy pursuing the great intellectual challenges of their day, much like Mr. Zuckerberg in his pursuit of the next great social media platform. Or like Cambridge Analytica’s Christopher Wylie, the twentysomething data scientist who helped build psychometric profiles of two-thirds of all Americans by leveraging personal information gained through uninformed consent. All of these researchers were, quite understandably, obsessed with the great data science challenges of their generation. Their failure to consider the consequences of their pursuits, however, is not so much their fault as it is our collective failing.
For the past 100 years we have been chasing visions of data with a singular passion. Many of the best minds of each new generation have devoted themselves to delivering on the inspired data science promises of their day: intelligence testing, building the computer, cracking the genetic code, creating the internet, and now this. We have in the course of a single century built an entire society, economy and culture that runs on information. Yet we have hardly begun to engineer data ethics appropriate for our extraordinary information carnival. If we do not do so soon, data will drive democracy, and we may well lose our chance to do anything about it….(More)”.
How the government will operate in 2030
Darrell West at the Hill: “Imagine it is 2030 and you are a U.S. government employee working from home. With the assistance of the latest technology, you participate in video calls with clients and colleagues, augment your job activities through artificial intelligence and a personal digital assistant, work through collaboration software, and regularly get rated on a one-to-five scale by clients regarding your helpfulness, follow-through, and task completion.
How did you — and the government — get here? The sharing economy that unfolded in 2018 has revolutionized the public-sector workforce. The days when federal employees were subject to a centrally directed Office of Personnel and Management that oversaw permanent, full-time workers sitting in downtown office buildings are long gone. In their place is a remote workforce staffed by a mix of short- and long-term employees. This has dramatically improved worker productivity and satisfaction.
In the new digital world that has emerged, the goal is to use technology to make employees accountable. Gone are 20- or 30-year careers in the federal bureaucracy. Political leaders have always preached the virtue of running government like a business, and the success of Uber, Airbnb, and WeWork has persuaded them to focus on accountability and performance.
Companies such as Facebook demonstrated they could run large and complex organizations with less than 20,000 employees, and the federal government followed suit in the late 2020s. Now, workers deploy the latest tools of artificial intelligence, virtual reality, data analytics, robots, driverless cars, and digital assistants to improve the government. Unlike the widespread mistrust and cynicism that had poisoned attitudes in the decades before, the general public now sees government as a force for achieving positive results.
Many parts of the federal government are decentralized and mid-level employees are given greater authority to make decisions — but are subject to digital ratings that keep them accountable for their performance. The U.S. government borrowed this technique from China, where airport authorities in 2018 installed digital devices that allowed visitors to rate the performance of individual passport officers after every encounter. The reams of data have enabled Chinese authorities to fire poor performers and make sure foreign visitors see a friendly and competent face at the Beijing International Airport.
Alexa-like devices are given to all federal employees. The devices are used to keep track of leave time, file reimbursement requests, request time off, and complete a range of routine tasks that used to take employees hours. Through voice-activated commands, they navigate these mundane tasks quickly and efficiently. No one can believe the mountains of paperwork required just a decade ago….(More)”.
The People vs. Democracy: Why Our Freedom Is in Danger and How to Save It
Book by Yascha Mounk: “The world is in turmoil. From India to Turkey and from Poland to the United States, authoritarian populists have seized power. As a result, Yascha Mounk shows, democracy itself may now be at risk.
Two core components of liberal democracy—individual rights and the popular will—are increasingly at war with each other. As the role of money in politics soared and important issues were taken out of public contestation, a system of “rights without democracy” took hold. Populists who rail against this say they want to return power to the people. But in practice they create something just as bad: a system of “democracy without rights.”
The consequence, Mounk shows in The People vs. Democracy, is that trust in politics is dwindling. Citizens are falling out of love with their political system. Democracy is wilting away. Drawing on vivid stories and original research, Mounk identifies three key drivers of voters’ discontent: stagnating living standards, fears of multiethnic democracy, and the rise of social media. To reverse the trend, politicians need to enact radical reforms that benefit the many, not the few.
The People vs. Democracy is the first book to go beyond a mere description of the rise of populism. In plain language, it describes both how we got here and where we need to go. For those unwilling to give up on either individual rights or the popular will, Mounk shows, there is little time to waste: this may be our last chance to save democracy….(More)”
Can Social Media Help Build Communities?
Paper by Eric Forbush and Nicol Turner-Lee: “In June 2017, Mark Zuckerberg proclaimed a new mission for Facebook, which was to “[g]ive people the power to build community and bring the world closer together” during the company’s first Community Summit. Yet, his declaration comes in the backdrop of a politically polarized America. While research has indicated that ideological polarization (the alignment and divergence of ideologies) has remained relatively unchanged, affective polarization (the degree to which Democrats and Republicans dislike each other) has skyrocketed (Gentzkow, 2016; Lelkes, 2016). This dislike for members of the opposite party may be amplified on social media platforms.
Social media have been accused of making our social networks increasingly insular, resulting in “echo chambers,” wherein individuals select information and friends who support their already held beliefs (Quattrociocchi, Scala, and Sunstein, 2016; Williams, McMurray, Kurz, and Lambert, 2015). However, the implicit message in Zuckerberg’s comments, and other leaders in this space, is that social media can provide users with a means for brokering relationships with other users that hold different values and beliefs from them. However, little is known on the extent to which social media platforms enable these opportunities.
Theories of prejudice reduction (Paluck and Green, 2009) partially explain an idealistic outcome of improved online relationships. In his seminal contact theory, Gordon Allport (1954) argued that under certain optimal conditions, all that is needed to reduce prejudice is for members of different groups to spend more time interacting with each other. However, contemporary social media platforms may not be doing enough to increase intergroup engagements, especially between politically polarized communities on issues of importance.
In this paper, we use Twitter data collected over a 20-day period, following the Day of Action for Net Neutrality on July 12, 2017. In support of a highly polarized regulatory issue, the Day of Action was organized by advocacy groups and corporations in support of an open internet, which does not discriminate against online users when accessing their preferred content. Analyzing 81,316 tweets about #netneutrality from 40,502 distinct users, we use social network analysis to develop network visualizations and conduct discrete content analysis of central tweets. Our research also divides the content by those in support and those opposed to any type of repeal of net neutrality rules by the FCC.
Our analysis of this particular issue reveals that social media is merely replicating, and potentially strengthening polarization on issues by party affiliations and online associations. Consequently, the appearance of mediators who are able to bridge online conversations or beliefs on charged issues appear to be nonexistent on both sides of the issue. Consequently, our findings suggest that social media companies may not be doing enough to bring communities together through meaningful conversations on their platforms….(More)”.
Lessons from Cambridge Analytica: one way to protect your data
Julia Apostle in the Financial Times: “The unsettling revelations about how data firm Cambridge Analytica surreptitiously exploited the personal information of Facebook users is yet another demoralising reminder of how much data has been amassed about us, and of how little control we have over it.
Unfortunately, the General Data Protection Regulation privacy laws that are coming into force across Europe — with more demanding consent, transparency and accountability requirements, backed by huge fines — may improve practices, but they will not change the governing paradigm: the law labels those who gather our data as “controllers”. We are merely “subjects”.
But if the past 20 years have taught us anything, it is that when business and legislators have been too slow to adapt to public demand — for goods and services that we did not even know we needed, such as Amazon, Uber and bitcoin — computer scientists have stepped in to fill the void. And so it appears that the realms of data privacy and security are deserving of some disruption. This might come in the form of “self-sovereign identity” systems.
The theory behind self-sovereign identity is that individuals should control the data elements that form the basis of their digital identities, and not centralised authorities such as governments and private companies. In the current online environment, we all have multiple log-ins, usernames, customer IDs and personal data spread across countless platforms and stored in myriad repositories.
Instead of this scattered approach, we should each possess the digital equivalent of a wallet that contains verified pieces of our identities. We can then choose which identification to share, with whom, and when. Self-sovereign identity systems are currently being developed.
They involve the creation of a unique and persistent identifier attributed to an individual (called a decentralised identity), which cannot be taken away. The systems use public/private key cryptography, which enables a user with a private key (a string of numbers) to share information with unlimited recipients who can access the encrypted data if they possess a corresponding public key.
The systems also rely on decentralised ledger applications like blockchain. While key cryptography has been around for a long time, it is the development of decentralised ledger technology, which also supports the trading of cryptocurrencies without the involvement of intermediaries, that will allow self-sovereign identity systems to take off. The potential uses for decentralised identity are legion and small-scale implementation is already happening. The Swiss municipality of Zug started using a decentralised identity system called uPort last year, to allow residents access to certain government services. The municipality announced it will also use the system for voting this spring….
Decentralised identity is more difficult to access and therefore there is less financial incentive for hackers to try. Self-sovereign identity systems could eliminate many of our data privacy concerns while empowering individuals in the online world and turning the established data order on its head. But the success of the technology depends on its widespread adoption….(More)“
Psychographics: the behavioural analysis that helped Cambridge Analytica know voters’ minds
Michael Wade at The Conversation: “Much of the discussion has been on how Cambridge Analytica was able to obtain data on more than 50m Facebook users – and how it allegedly failed to delete this data when told to do so. But there is also the matter of what Cambridge Analytica actually did with the data. In fact the data crunching company’s approach represents a step change in how analytics can today be used as a tool to generate insights – and to exert influence.
For example, pollsters have long used segmentation to target particular groups of voters, such as through categorising audiences by gender, age, income, education and family size. Segments can also be created around political affiliation or purchase preferences. The data analytics machine that presidential candidate Hillary Clinton used in her 2016 campaign – named Ada after the 19th-century mathematician and early computing pioneer – used state-of-the-art segmentation techniques to target groups of eligible voters in the same way that Barack Obama had done four years previously.
Cambridge Analytica was contracted to the Trump campaign and provided an entirely new weapon for the election machine. While it also used demographic segments to identify groups of voters, as Clinton’s campaign had, Cambridge Analytica also segmented using psychographics. As definitions of class, education, employment, age and so on, demographics are informational. Psychographics are behavioural – a means to segment by personality.
This makes a lot of sense. It’s obvious that two people with the same demographic profile (for example, white, middle-aged, employed, married men) can have markedly different personalities and opinions. We also know that adapting a message to a person’s personality – whether they are open, introverted, argumentative, and so on – goes a long way to help getting that message across….
There have traditionally been two routes to ascertaining someone’s personality. You can either get to know them really well – usually over an extended time. Or you can get them to take a personality test and ask them to share it with you. Neither of these methods is realistically open to pollsters. Cambridge Analytica found a third way, with the assistance of two University of Cambridge academics.
The first, Aleksandr Kogan, sold them access to 270,000 personality tests completed by Facebook users through an online app he had created for research purposes. Providing the data to Cambridge Analytica was, it seems, against Facebook’s internal code of conduct, but only now in March 2018 has Kogan been banned by Facebook from the platform. In addition, Kogan’s data also came with a bonus: he had reportedly collected Facebook data from the test-takers’ friends – and, at an average of 200 friends per person, that added up to some 50m people.
However, these 50m people had not all taken personality tests. This is where the second Cambridge academic, Michal Kosinski, came in. Kosinski – who is said to believe that micro-targeting based on online data could strengthen democracy – had figured out a way to reverse engineer a personality profile from Facebook activity such as likes. Whether you choose to like pictures of sunsets, puppies or people apparently says a lot about your personality. So much, in fact, that on the basis of 300 likes, Kosinski’s model is able to predict someone’s personality profile with the same accuracy as a spouse….(More)”