Tweets Are Not Created Equal:investigating Twitter's client ecosystem

This article offers an investigation into the developer ecosystem of platforms drawing on the specific case of Twitter and explores how third-party clients enable different “ways of being” on Twitter. It suggests that researchers need to consider digital data as traces of distributed accomplishments between platforms, users, interfaces, and developers. The argument follows three main steps: We discuss how Twitter’s bounded openness enables and structures distributed data production through grammatization of action. We then suggest ways to explore and qualify sources by drawing on a weeklong data set of nearly 32 million tweets, retrieved from Twitter’s 1% random sample. We explore how clients show considerable differences in tweet characteristics and degrees of automation, and outline methodological steps to deploy the source variable to further investigate the heterogeneous practices common metrics risk flattening into singular counts. We conclude by returning to the question about the measures of the medium, suggesting how they might be revisited in the context of increasingly distributed platform ecosystems, and how platform data challenge key ideas of digital methods research

Social infomediation of news on Twitter: a French case study

Social infomediation is an emerging phenomenon that sees growing numbers of Internet users share and comment on news items on Facebook and Twitter. This study analyses a large sample of French-speaking Twitter users over a period of two months. First, we study some general characteristics of our sample’s usage of Twitter, such as timescale, productivity, hashtag, and URL distribution. We then compare the French online media agenda to the most shared and discussed news items in our sample in order to highlight similarities and differences. Our findings show that even though they depend on mainstream media coverage, Twitter user preferences often push political and technological stories that have been overlooked or even ignored to the forefront

MLS: Airplane system modeling

Analysis, modeling, and simulations were conducted as part of a multiyear investigation of the more important airplane-system-related items of the microwave landing system (MLS). Particular emphasis was placed upon the airplane RF system, including the antenna radiation distribution, the cabling options from the antenna to the receiver, and the overall impact of the airborne system gains and losses upon the direct-path signal structure. In addition, effort was expended toward determining the impact of the MLS upon the airplane flight management system and developing the initial stages of a fast-time MLS automatic control system simulation model. Results ot these studies are presented

On mapping values in AI Governance

We propose here a conceptual framework by which to analyze legal-regulatory problematics of algorithmic decision-making systems, focusing on mechanisms of value production in their design and deployment. An aim of our intervention is to develop an investigative model for application to algorithmic decision systems with regulatory effects, including predictive artificial intelligence applications and recommender systems that filter data and suggest courses of action. Technical systems that integrate complex algorithmic techniques perform critical and sensitive functions that are both object and instrument of regulatory governance, functions such as predicting behavior, steering information flows, assessing risk, etc. These functions, however, are not simple or static phenomena, but rather contextual, partial performances of complex socio-technical dynamics. One of our interests is to discern what is valorized in this new regulatory ecology. Accordingly, we are sketching a framework to target terms and tokens of value as they are produced, reproduced, incorporated, and translated among design processes, legal practices and background conditions structuring their use. Rather than asking which values AI should satisfy in contested governance contexts, we address conceptually prior questions concerning how values manifest and ‘map’ among context-sensitive computational and social processes in the first place. Furthermore, current research often takes for granted that an AI application is produced against the backdrop of a stable and pre-defined set of values and legal practices. Existing research does not yet adequately account for the ways in which laws and values as produced in and through the ecology of the AI application differ from idealized presuppositions assumed to preexist development of the latter. For the purpose, our contribution engages three broad lines of inquiry: one, we take forward calls for a materialized study of law, such as put forward broadly by Alain Pottage, and as put forward more recently and specifically with respect to computational technologies by Mireille Hildebrandt, among others; two, we contribute to the elaboration of a critical practice for AI, in the tradition of Philip Agre; and three, our attention to assemblages potentially contributes to debates over techno-regulation or regulation by design