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Americans' trust in news is declining, and authenticity and transparency challenges in digital publishing contexts pose unique challenges to the ability to effectively gratify their information-seeking needs via online media. Cryptographic technologies and web-based provenance indicators have the potential to enhance the trustworthiness and transparency of digital communication, but better understandings of news consumers practices and needs are required to develop practical tools. Through a representative online survey of 400 digital news consumers and 19 follow-up interviews, we investigate how users authenticate and assign trust to news content, and identify specific needs pertaining to news transparency and authentication that could be met by digital news authentication tools. While many users currently rely on political ideology to assess news trustworthiness, we find that users of all political orientations see value in independent provenance and authentication tools for digital news. 

This study analyzes and compares how the digital semantic infrastructure of U.S. based digital news varies according to certain characteristics of the media outlet, including the community it serves, the content management system (CMS) it uses, and its institutional affiliation (or lack thereof). Through a multi-stage analysis of the actual markup found on news outlets’ online text articles, we reveal how multiple factors may be limiting the discoverability and reach of online media organizations focused on serving specific communities. Conceptually, we identify markup and metadata as aspects of the semantic infrastructure underpinning platforms’ mechanisms of distributing online news. Given the significant role that these platforms play in shaping the broader visibility of news content, we further contend that this markup therefore constitutes a kind of infrastructure of visibility by which news sources and voices are rendered accessible—or, conversely—invisible in the wider platform economy of journalism. We accomplish our analysis by first identifying key forms of digital markup whose structured data is designed to make online news articles more readily discoverable by search engines and social media platforms. We then analyze 2,226 digital news stories gathered from the main pages of 742 national, local, Black, and other identity-based news organizations in mid-2021, and analyze each for the presence of specific tags reflecting the Schema.org, OpenGraph, and Twitter metadata structures. We then evaluate the relationship between audience focus and the robustness of this digital semantic infrastructure. While we find only a weak relationship between the markup and the community served, additional analysis revealed a much stronger association between these metadata tags and content management system (CMS), in which 80% of the attributes appearing on an article were the same for a given CMS, regardless of publisher, market, or audience focus. Based on this finding, we identify the organizational characteristics that may influence the specific CMS used for digital publishing, and, therefore, the robustness of the digital semantic infrastructure deployed by the organization. Finally, we reflect on the potential implications of the highly disparate tag use we observe, particularly with respect to the broader visibility of online news designed to serve particular US communities. 

Tracking changes in digital texts is a longstanding interface challenge, as early digital technologies left no recorded traces of alterations. Currently, two key categories of tools track text changes: code editing and word processing tools. Each has implemented different interface patterns to accomplish several goals: attributing change authorship, tracking the time of change, recording the change action taken, and specifying the location and content of the change. While some visual characteristics of change tracking are consistent across all tools, there are significant differences in change representation divided along the tool-type line, that may reflect their specific cultures of use. Overall, however, there is a limited range of visual methods for representing changes to digital text over time. 

To combat declining trust in news in the United States, numerous tools have been created to increase transparency by providing contextual information around news content, but they have largely been developed without regard for usability. We examine 59 such tools to identify the type(s) of transparency (disclosure, participatory, or ambient) information each tool aims to provide. We then conduct a heuristic usability analysis of a subset of these transparency tools and identify common usability barriers. 

This position paper describes our research project to improve middle school students’ use of security “best-practices” in their day-to-day online activities, while enhancing their fundamental understanding of the underlying security principles and math concepts that drive AI and cybersecurity technologies. The project involves the design and implementation of a time- and teacher-friendly learning module that can be readily integrated into existing middle school math curricula. We plan to deploy this module at a high-needs, rural-identifying middle school in South Carolina that serves underrepresented students