The Digital Architectures of Social Media: Comparing Political Campaigning on Facebook, Twitter, Instagram, and Snapchat in the 2016 U.S. Election

The present study argues that political communication on social media is mediated by a platform's digital architecture, defined as the technical protocols that enable, constrain, and shape user behavior in a virtual space. A framework for understanding digital architectures is introduced, and four platforms (Facebook, Twitter, Instagram, and Snapchat) are compared along the typology. Using the 2016 US election as a case, interviews with three Republican digital strategists are combined with social media data to qualify the studyies theoretical claim that a platform's network structure, functionality, algorithmic filtering, and datafication model affect political campaign strategy on social media

User Satisfaction with Wearables

This study investigates user satisfaction with wearable technologies. It proposes that the integration of expectation confirmation theory with affordance theory sheds light on the sources of user’s (dis)confirmation when evaluating technology performance experiences and explains the origins of satisfaction ratings. A qualitative and quantitative analysis of online user reviews of a popular fitness wristband supports the research model. Since the band lacks buttons and numeric displays, users need to interact with the companion software to obtain the information they need. Findings indicate that satisfaction depends on the interaction’s quality, the value of digitalizing physical activity, and the extent to which the informational feedback meets users’ needs. Moreover, the results suggest that digitalizing physical activity has different effects for different users. While some appreciate data availability in general regardless of their accuracy, those who look for precision do not find such quantification useful. Thus, their evaluative judgments depend on the wearable system’s actual performance and the influence that the feedback has on their pursuit of their fitness goals. These results provide theoretical and practical contributions to advance our understanding of wearable technologies

Learning the Semantics of Manipulation Action

In this paper we present a formal computational framework for modeling manipulation actions. The introduced formalism leads to semantics of manipulation action and has applications to both observing and understanding human manipulation actions as well as executing them with a robotic mechanism (e.g. a humanoid robot). It is based on a Combinatory Categorial Grammar. The goal of the introduced framework is to: (1) represent manipulation actions with both syntax and semantic parts, where the semantic part employs $\lambda$-calculus; (2) enable a probabilistic semantic parsing schema to learn the $\lambda$-calculus representation of manipulation action from an annotated action corpus of videos; (3) use (1) and (2) to develop a system that visually observes manipulation actions and understands their meaning while it can reason beyond observations using propositional logic and axiom schemata. The experiments conducted on a public available large manipulation action dataset validate the theoretical framework and our implementation

Time well spent”: the ideology of temporal disconnection as a means for digital wellbeing

After facing an intense negative reaction to their accumulation of social, political, and economic power and influence, several tech and social media companies rolled out “digital wellbeing” tools during the second half of 2018. This article examines the technological and discursive construction of “digital wellbeing” as enacted through operating system-based tools (Screen Time and Do Not Disturb— iOS, Digital Wellbeing—Android, My Analytics—Microsoft), and social media platforms application functions (Your Time—Facebook, Time Watched—YouTube, Your Activity—Instagram). While the companies’ discourse deploys an imaginary centered around ethics and a normative experience accentuating the willfulness and empowerment of the user, the socio-material analysis of the interfaces and features shows that they envisage simple, familiar, and limited possibilities of disconnecting. Therefore, agency is limited, and the wellbeing outcomes are indeterminate, restricted to quantifying time or controlling the intentionality of connectivity

Dialectic tensions in the financial markets: a longitudinal study of pre- and post-crisis regulatory technology

This article presents the findings from a longitudinal research study on regulatory technology in the UK financial services industry. The financial crisis with serious corporate and mutual fund scandals raised the profile of compliance as governmental bodies, institutional and private investors introduced a ‘tsunami’ of financial regulations. Adopting a multi-level analysis, this study examines how regulatory technology was used by financial firms to meet their compliance obligations, pre- and post-crisis. Empirical data collected over 12 years examine the deployment of an investment management system in eight financial firms. Interviews with public regulatory bodies, financial institutions and technology providers reveal a culture of compliance with increased transparency, surveillance and accountability. Findings show that dialectic tensions arise as the pursuit of transparency, surveillance and accountability in compliance mandates is simultaneously rationalized, facilitated and obscured by regulatory technology. Responding to these challenges, regulatory bodies continue to impose revised compliance mandates on financial firms to force them to adapt their financial technologies in an ever-changing multi-jurisdictional regulatory landscape

Emergence of Organisms.

Since early cybernetics studies by Wiener, Pask, and Ashby, the properties of living systems are subject to deep investigations. The goals of this endeavour are both understanding and building: abstract models and general principles are sought for describing organisms, their dynamics and their ability to produce adaptive behavior. This research has achieved prominent results in fields such as artificial intelligence and artificial life. For example, today we have robots capable of exploring hostile environments with high level of self-sufficiency, planning capabilities and able to learn. Nevertheless, the discrepancy between the emergence and evolution of life and artificial systems is still huge. In this paper, we identify the fundamental elements that characterize the evolution of the biosphere and open-ended evolution, and we illustrate their implications for the evolution of artificial systems. Subsequently, we discuss the most relevant issues and questions that this viewpoint poses both for biological and artificial systems

Modeling Through

Theorists of justice have long imagined a decision-maker capable of acting wisely in every circumstance. Policymakers seldom live up to this ideal. They face well-understood limits, including an inability to anticipate the societal impacts of state intervention along a range of dimensions and values. Policymakers see around corners or address societal problems at their roots. When it comes to regulation and policy-setting, policymakers are often forced, in the memorable words of political economist Charles Lindblom, to “muddle through” as best they can. Powerful new affordances, from supercomputing to artificial intelligence, have arisen in the decades since Lindblom’s 1959 article that stand to enhance policymaking. Computer-aided modeling holds promise in delivering on the broader goals of forecasting and systems analysis developed in the 1970s, arming policymakers with the means to anticipate the impacts of state intervention along several lines—to model, instead of muddle. A few policymakers have already dipped a toe into these waters, others are being told that the water is warm. The prospect that economic, physical, and even social forces could be modeled by machines confronts policymakers with a paradox. Society may expect policymakers to avail themselves of techniques already usefully deployed in other sectors, especially where statutes or executive orders require the agency to anticipate the impact of new rules on particular values. At the same time, “modeling through” holds novel perils that policymakers may be ill equipped to address. Concerns include privacy, brittleness, and automation bias, all of which law and technology scholars are keenly aware. They also include the extension and deepening of the quantifying turn in governance, a process that obscures normative judgments and recognizes only that which the machines can see. The water may be warm, but there are sharks in it. These tensions are not new. And there is danger in hewing to the status quo. As modeling through gains traction, however, policymakers, constituents, and academic critics must remain vigilant. This being early days, American society is uniquely positioned to shape the transition from muddling to modeling