A simple self-reflection intervention boosts the detection of targeted advertising

Abstract Online platforms’ data give advertisers the ability to “microtarget” recipients’ personal vulnerabilities by tailoring different messages for the same thing, such as a product or political candidate. One possible response is to raise awareness for and resilience against such manipulative strategies through psychological inoculation. Two online experiments (total $$N= 828$$ N = 828 ) demonstrated that a short, simple intervention prompting participants to reflect on an attribute of their own personality—by completing a short personality questionnaire—boosted their ability to accurately identify ads that were targeted at them by up to 26 percentage points. Accuracy increased even without personalized feedback, but merely providing a description of the targeted personality dimension did not improve accuracy. We argue that such a “boosting approach,” which here aims to improve people’s competence to detect manipulative strategies themselves, should be part of a policy mix aiming to increase platforms’ transparency and user autonomy

Psychological Factors Shaping Public Responses to COVID-19 Digital Contact Tracing Technologies in Germany

The COVID-19 pandemic has seen one of the first large-scale uses of digital contact tracing to track a chain of infection and contain the spread of a virus. The new technology has posed challenges both for governments aiming at high and effective uptake and for citizens weighing its benefits (e.g., protecting others’ health) against the potential risks (e.g., loss of data privacy). Our cross-sectional survey with repeated measures across four samples in Germany ([Formula: see text] ) focused on psychological factors contributing to the public adoption of digital contact tracing. We found that public acceptance of privacy-encroaching measures (e.g., granting the government emergency access to people’s medical records or location tracking data) decreased over the course of the pandemic. Intentions to use contact tracing apps—hypothetical ones or the Corona-Warn-App launched in Germany in June 2020—were high. Users and non-users of the Corona-Warn-App differed in their assessment of its risks and benefits, in their knowledge of the underlying technology, and in their reasons to download or not to download the app. Trust in the app’s perceived security and belief in its effectiveness emerged as psychological factors playing a key role in its adoption. We incorporate our findings into a behavioral framework for digital contact tracing and provide policy recommendations

Young Adults View Smartphone Tracking Technologies for COVID-19 as Acceptable:The Case of Taiwan

Taiwan has been successful in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic; however, without a vaccine the threat of a second outbreak remains. Young adults who show few to no symptoms when infected have been identified in many countries as driving the virus' spread through unidentifiable community transmission. Mobile tracking technologies register nearby contacts of a user and notifies them if one later tests positive to the virus, potentially solving this issue; however, the effectiveness of these technologies depends on their acceptance by the public. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google's Bluetooth exposure notification system) among four samples of young Taiwanese adults (aged 25 years or younger). Using Bayesian methods, we find high acceptance for all three tracking technologies (>75%), with acceptance for each technology surpassing 90% if additional privacy measures were included. We consider the policy implications of these results for Taiwan and similar cultures

The Social Construction of Conspiracy Beliefs: A Q-Methodology Study of How Ordinary People DefineThem and Judge Their Plausibility

Little is known about ordinary people’s understandings of conspiracy beliefs and how these understandings relate to the perspectives of researchers and scholars. Working within a social constructionist epistemological framework, we conducted a Q-methodology study aiming to identify a range of lay perspectives on two key topics: the defining features of conspiracy beliefs; and aspects considered important in judging their plausibility. Fifty-six people (32 men and 24 women), recruited via regional UK Facebook groups, sorted their agreement with a set of statements on each of the two topics. A principal component analysis, followed by varimax rotation, was performed on each data set. Five accounts about the defining features of conspiracy beliefs were identified: that they are false, illogical and harmful; that they are forms of political critique; that there are varied types; that they are entertaining but ineffectual; and that they are held by a self-reinforcing minority. Four accounts about their evaluation were identified: conventional realist criteria; the importance of personal judgement; skeptical realism; and the assessment of critical thinking. The findings are discussed in the context of the literature and limitations of the study are considered. Implications for research and educational and policy interventions are outlined

Computational fact checking from knowledge networks

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation

Information overload for (bounded) rational agents

Bayesian inference offers an optimal means of processing environmental information and so an advantage in natural selection. We consider the apparent, recent trend in increasing dysfunctional disagreement in e.g. political debate. This is puzzling because Bayesian inference benefits from powerful convergence theorems, precluding dysfunctional disagreement. Information overload is a plausible factor limiting the applicability of full Bayesian inference, but what is the link with dysfunctional disagreement? Individuals striving to be Bayesian-rational, but challenged by information overload, might simplify by using Bayesian Networks or the separation of questions into knowledge partitions, the latter formalized with quantum probability theory. We demonstrate the massive simplification afforded by either approach, but also show how they contribute to dysfunctional disagreement

Ideologies and their points of view

© Springer International Publishing Switzerland 2016. It is well known that different arguments appeal to different people. We all process information in ways that are adapted to be consistent with our underlying ideologies. These ideologies can sometimes be framed in terms of particular axes or dimensions, which makes it possible to represent some aspects of an ideology as a region in the kind of vector space that is typical of many generalised quantum models. Such models can then be used to explain and predict, in broad strokes, whether a particular argument or proposal is likely to appeal to an individual with a particular ideology. The choice of suitable arguments to bring about desired actions is traditionally part of the art or science of rhetoric, and today’s highly polarised society means that this skill is becoming more important than ever. This paper presents a basic model for understanding how different goals will appeal to people with different ideologies, and thus how different rhetorical positions can be adopted to promote the same desired outcome. As an example, we consider different narratives and hence actions with respect to the environment and climate change, an important but currently highly controversial topic