Shoot First, Ask Later: Constitutional Rights at the Border after \u3cem\u3eBoumediene\u3c/em\u3e

Adopting Boumediene\u27s functional approach in analyzing extraterritorial application of the United States Constitution at the U.S.-Mexico border will promote uniformity and provide guidance to courts and officials. Currently, courts are applying Verdugo-Urquidez\u27s sufficient connections test, and different variations thereof permitting courts to arbitrarily decide who is entitled to constitutional protection in the absence of uniform precedent. Adopting Boumediene as the guiding test will not automatically trigger constitutional protection, instead, constitutional protection will only be granted if extending protection to an alien at the U.S.-Mexico border is justified based on the three-prong test

Do smartphone usage scales predict behavior?

Understanding how people use technology remains important, particularly when measuring the impact this might have on individuals and society. However, despite a growing body of resources that can quantify smartphone use, research within psychology and social science overwhelmingly relies on self-reported assessments. These have yet to convincingly demonstrate an ability to predict objective behavior. Here, and for the first time, we compare a variety of smartphone use and ‘addiction’ scales with objective behaviors derived from Apple’s Screen Time application. While correlations between psychometric scales and objective behavior are generally poor, single estimates and measures that attempt to frame technology use as habitual rather than ‘addictive’ correlate more favorably with subsequent behavior. We conclude that existing self-report instruments are unlikely to be sensitive enough to accurately predict basic technology use related behaviors. As a result, conclusions regarding the psychological impact of technology are unreliable when relying solely on these measures to quantify typical usage

Sentiment Analysis in Digital Spaces: An Overview of Reviews

Sentiment analysis (SA) is commonly applied to digital textual data, revealing insight into opinions and feelings. Many systematic reviews have summarized existing work, but often overlook discussions of validity and scientific practices. Here, we present an overview of reviews, synthesizing 38 systematic reviews, containing 2,275 primary studies. We devise a bespoke quality assessment framework designed to assess the rigor and quality of systematic review methodologies and reporting standards. Our findings show diverse applications and methods, limited reporting rigor, and challenges over time. We discuss how future research and practitioners can address these issues and highlight their importance across numerous applications.Comment: 44 pages, 4 figures, 6 tables, 3 appendice

Social media addiction:technological déjà vu

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Spreading the Word:Exploring a Network of Mobilizing Messages in a Telegram Conspiracy Group

Telegram's design prioritizes user security and minimal content moderation, making it appealing for communities banned from mainstream platforms, such as conspiracy influencers or far-right movements. We examine the bi-directional behavior of users in a conspiratorial Telegram group chat during the COVID-19 pandemic from 2020-2023. We find that the network structure of this community evolved throughout the pandemic, where the network grew both in the number of active users, as well as in the number of interactions. This increased interconnectivity coincided with surges in planning discussions for associated offline protests.</p

Spreading the Word:Exploring a Network of Mobilizing Messages in a Telegram Conspiracy Group

Telegram's design prioritizes user security and minimal content moderation, making it appealing for communities banned from mainstream platforms, such as conspiracy influencers or far-right movements. We examine the bi-directional behavior of users in a conspiratorial Telegram group chat during the COVID-19 pandemic from 2020-2023. We find that the network structure of this community evolved throughout the pandemic, where the network grew both in the number of active users, as well as in the number of interactions. This increased interconnectivity coincided with surges in planning discussions for associated offline protests.</p

The evolution of online ideological communities

Online communities are virtual spaces for users to share interests, support others, and to exchange knowledge and information. Understanding user behavior is valuable to organizations and has applications from marketing to security, for instance, identifying leaders within a community or predicting future behavior. In the present research, we seek to understand the various roles that users adopt in online communities-for instance, who leads the conversation? Who are the supporters? We examine user role changes over time and the pathways that users follow. This allows us to explore the differences between users who progress to leadership positions and users who fail to develop influence. We also reflect on how user role proportions impact the overall health of the community. Here, we examine two online ideological communities, RevLeft and Islamic Awakening (N = 1631; N = 849), and provide a novel approach to identify various types of users. Finally, we study user role trajectories over time and identify community "leaders" from meta-data alone. Study One examined both communities using K-MEANS cluster analysis of behavioral meta-data, which revealed seven user roles. We then mapped these roles against Preece and Schneiderman's (2009) Reader-to-Leader Framework (RtLF). Both communities aligned with the RtLF, where most users were "contributors", many were "collaborators", and few were "leaders". Study Two looked at one community over a two-year period and found that, despite a high churn rate of users, roles were stable over time. We built a model of user role transitions over the two years. This can be used to predict user role changes in the future, which will have implications for community managers and security focused contexts (e.g., analyzing behavioral meta-data from forums and websites known to be associated with illicit activity)

Oral hygiene effects verbal and nonverbal displays of confidence

Although oral hygiene is known to impact self-confidence and self-esteem, little is known about how it influences our interpersonal behavior. Using a wearable, multi-sensor device, we examined differences in consumers’ individual and interpersonal confidence after they had or had not brushed their teeth. Students (N = 140) completed nine one-to-one, 3-minute “speed dating” interactions while wearing a device that records verbal, nonverbal, and mimicry behavior. Half of the participants brushed their teeth using Close-Up toothpaste (Unilever) prior to the interactions, whilst the other half abstained from brushing that morning. Compared to those who had not brushed their teeth, participants who had brushed were more verbally confident (i.e., spoke louder, over-talked more), showed less nonverbal nervousness (i.e., fidgeted less), and were more often perceived as being “someone similar to me.” These effects were moderated by attractiveness but not by self-esteem or self-monitoring

Quantifying Smartphone “Use”: Choice of Measurement Impacts Relationships Between “Usage” and Health

Problematic smartphone scales and duration estimates of use dominate research that considers the impact of smartphones on people and society. However, issues with conceptualization and subsequent measurement can obscure genuine associations between technology use and health. Here, we consider whether different ways of measuring “smartphone use,” notably through problematic smartphone use (PSU) scales, subjective estimates, or objective logs, lead to contrasting associations between mental and physical health. Across two samples including iPhone (n = 199) and Android (n = 46) users, we observed that measuring smartphone interactions with PSU scales produced larger associations between mental health when compared with subjective estimates or objective logs. Notably, the size of the relationship was fourfold in Study 1, and almost three times as large in Study 2, when relying on a PSU scale that measured smartphone “addiction” instead of objective use. Further, in regression models, only smartphone “addiction” scores predicted mental health outcomes, whereas objective logs or estimates were not significant predictors. We conclude that addressing people’s appraisals including worries about their technology usage is likely to have greater mental health benefits than reducing their overall smartphone use. Reducing general smartphone use should therefore not be a priority for public health interventions at this time