Attitude Bias Research Articles

Automatically Distinguishing People’s Explicit and Implicit Attitude Bias by Bridging Psychological Measurements with Sentiment Analysis on Large Corpora

Social psychological studies show that people’s explicit attitude bias in public expression can differ from their implicit attitude bias in mind. However, the current automatic attitude analysis does not distinguish between explicit and implicit attitude bias. Simulating the psychological measurements of explicit and implicit attitude bias, i.e., self-report assessment (SRA) and implicit association test (IAT), we propose an automatic language-based analysis to distinguish explicit and implicit attitude bias in a large population. By connecting the criteria of SRA and IAT with the statements containing patterns of special words, we derive explicit and implicit attitude bias with the sentiment scores of the statements, which are obtained by pre-trained machine-learning methods. Extensive experiments on four English and Chinese corpora and four pairs of concepts show that the attitude biases obtained by our method on a large population are consistent with those of traditional psychological experiments in the costly small-scale experiments. The maximum gap between the sentiment scores of explicit and implicit biases reaches 0.9329. Furthermore, we achieve new findings on the difference between the evolution of explicit and implicit attitude bias. The maximum variance gap of sentiment scores in the dynamic changes between explicit and implicit biases reaches 0.249.

Modified maximum likelihood space registration method for shipborne multi-radar signal processing

Aiming at the spatial registration problem for networking of multi-platform shipborne radars, a modified maximum likelihood (MML) absolute registration algorithm based on singular value decomposition (SVD) is proposed. Firstly, the four major biases (radar detection biases, platform positioning biases, attitude biases, and baseline conversion biases) which affect shipborne radar detection are analyzed, and an equivalent model of shipborne radar detection biases is established to make the bias parameters more efficiently. Secondly, the maximum likelihood registration method is improved. According to the singular value decomposition, the conditional index is used to evaluate the observability in the maximum likelihood registration method in realtime, and the abnormal conditional index is corrected to effectively reduce the fluctuation of the bias estimation. Finally, the simulation results of two different scenarios are conducted, and the results show that the new method has significant improvements in estimation accuracy and algorithm stability compared with the existing algorithms.

Patient and Caregiver Perspectives on Telehealth Use in a Multidisciplinary Huntington's Disease Clinic: A Single-Institution Experience.

The coronavirus pandemic saw technology evolve as outpatient clinics faced restriction of in-person visits. Reliance on telemedicine using two-way audio-video communication significantly increased. Telemedicine was observed to be convenient, cost-effective, reduced no-show rates, and fostered sustained engagement. Enhanced flexibility from short notice scheduling benefitted patients and their caregivers. Greater time value was perceived by patients, and reduced reliance on caregivers. Disadvantages included barriers of access to internet connectivity or equipment. We aimed to retrospectively survey patients with Huntington's disease (HD) seen via telehealth in our HDSA Center for Excellence Multidisciplinary clinic. We evaluated usability, learnability, interface quality, reliability, and future use. This qualitative survey used the 21-item Telehealth Usability Questionnaire. Close-ended responses ranged from strongly disagree to strongly agree scored on Likert scale (1 through 7). Averages were calculated to examine attitudes towards telemedicine. Spearman correlation test was performed to detect attitude biases between patients and caregivers. Respondents were more likely than not to strongly agree with survey statements. Average attitude score of 5.92 (range 2.95-7.00) suggested favorability and improved convenience when telehealth was used in complement to in-person visits, without detriment to patient-provider communication. Spearman correlation coefficient between patient and family/caregiver groups was 0.023, which is below the cutoff of 0.344 for a = 0.05 at N = 24. This suggests there was no bias between patient and caregiver attitudes. This study demonstrated telehealth is favored by caregivers and patients with HD. This population with specific physical, cognitive and psychiatric needs can benefit from adaptive systems that enhance compliance.

Cognitive bias and attitude distortion of a priority decision

The resource saving bias is a cognitive bias describing how resource savings from improvements of high-productivity units are overestimated compared to improvements of less productive units. Motivational reasoning describes how attitudes, here towards private/public health care, distort decisions based on numerical facts. Participants made a choice between two productivity increase options with the goal of saving doctor resources. The options described productivity increases in low-/high-productivity private/public emergency rooms. Jointly, the biases produced 78% incorrect decisions. The cognitive bias was stronger than the motivational bias. Verbal justifications of the decisions revealed elaborations of the problem beyond the information provided, biased integration of quantitative information, change of goal of decision, and motivational attitude biases. Most (83%) of the incorrect decisions were based on (incorrect) mathematical justifications illustrating the resource saving bias. Participants who had better scores on a cognitive test made poorer decisions. Women who gave qualitative justifications to a greater extent than men made more correct decision. After a first decision, participants were informed about the correct decision with a mathematical explanation. Only 6.3% of the participants corrected their decisions after information illustrating facts resistance. This could be explained by psychological sunk cost and coherence theories. Those who made the wrong choice remembered the facts of the problem better than those who made a correct choice.

Practical distributed maneuvering target tracking using delayed information of heterogeneous unregistered sensors

Registration is the most consequential topic to be dealt with in a multi-sensor tracking system. On the other hand, providing satisfactory target acceleration estimation would enhance the performance of a ground-based air defense system encountering a maneuvering target. The main novelty of the present work is addressing a new scheme to solve the registration problem in a distributed network along with estimating accurate target acceleration, simultaneously. The details of coping with three common kinds of measurement, attitude, and location biases are explored concentrating on the effects of attitude bias as the main error source from the practical viewpoint. A modified iterated extended Kalman filter is suggested as the basis to handle the multi-rate fusion problem. The probable performance degradation due to the existence of sensors measurement delay (ignored in all similar studies) is illustrated. An effective scheme that compensates for the delay with a low computation cost is introduced. The formulation is developed for a typical radar-infrared tracking system, accomplished by elucidating the required points for generalization to a desirable number of heterogeneous sensors. Calculating the Cramer-Rao bound of estimation problem, the effectiveness of proposed scheme is deliberately demonstrated through simulation analyses respecting the momentous practical aspects.

How Group Perception Affects What People Share and How People Feel: The Role of Entitativity and Epistemic Trust in the "Saying-Is-Believing" Effect.

This research investigated how interpersonal communication with a large audience can influence communicators’ attitudes. Research on the saying-is-believing effect has shown that when an individual’s attitude is perceived in advance by a communicator, the communicator tunes the message to the person, which biases the communicator’s attitude toward the person’s attitude. In this study, we examined the conditions under which audience tuning and attitude bias can occur with audiences containing more than one individual. We manipulated communicators’ perceived group entity for a large audience and the audience’s prior attitudinal valence and measured the audience’s epistemic trust. The results showed that communicators tuned their messages to the audience’s attitude when they perceived group entitativity and epistemic trust. Furthermore, tuning the message to the audience was found to bias communicators’ subsequent impressions of the topic in a direction closer to the audience’s attitude. These results suggest that perceiving a large audience as a group influences the subsequent impressions of electronic word-of-mouth product or service communicators.

Moving Morality Beyond the In-Group: Liberals and Conservatives Show Differences on Group-Framed Moral Foundations and These Differences Mediate the Relationships to Perceived Bias and Threat.

Moral foundations research suggests that liberals care about moral values related to individual rights such as harm and fairness, while conservatives care about those foundations in addition to caring more about group rights such as loyalty, authority, and purity. However, the question remains about how conservatives and liberals differ in relation to group-level moral principles. We used two versions of the moral foundations questionnaire with the target group being either abstract or specific ingroups or outgroups. Across three studies, we observed that liberals showed more endorsement of Individualizing foundations (Harm and Fairness foundations) with an outgroup target, while conservatives showed more endorsement of Binding foundations (Loyalty, Authority, and Purity foundations) with an ingroup target. This general pattern was found when the framed, target-group was abstract (i.e., ‘ingroups’ and ‘outgroups’ in Study 1) and when target groups were specified about a general British-ingroup and an immigrant-outgroup (Studies 2 and 3). In Studies 2 and 3, both Individualizing-Ingroup Preference and Binding-Ingroup Preference scores predicted more Attitude Bias and more Negative Attitude Bias toward immigrants (Studies 2 and 3), more Implicit Bias (Study 3), and more Perceived Threat from immigrants (Studies 2 and 3). We also demonstrated that increasing liberalism was associated with less Attitude Bias and less Negative Bias toward immigrants (Studies 2 and 3), less Implicit Bias (Study 3), and less Perceived Threat from immigrants (Studies 2 and 3). Outgroup-individualizing foundations and Ingroup-Binding foundations showed different patterns of mediation of these effects.

A Global Interconnected Observer for Attitude and Gyro Bias Estimation with Vector Measurements.

This paper proposes a novel interconnected observer to get good estimates of attitude and gyro bias from high-noise vector measurements. The observer is derived based on the theory of nonlinear and linear cascade systems, and its error dynamics have the properties of global exponential stability and robustness to bounded noise. These properties ensure the convergence and boundedness of the attitude and gyro bias estimation errors. To obtain higher estimation accuracy, an approach to calculate time-varying gains for the proposed auxiliary observer is designed under the premise of considering noise terms in the rate gyro and vector sensors. The simulation results show that when the vector sensors’ outputs contain high-level noise, the proposed observer with time-varying gains yields better performance in both the transient and steady-state phases.

Interregional and intraregional variability of intergroup attitudes predict online hostility

To what extent are intergroup attitudes associated with regional differences in online aggression and hostility? We test whether regional attitude biases towards minorities and their local variability (i.e. intraregional polarization) independently predict verbal hostility on social media. We measure online hostility using large US American samples from Twitter and measure regional attitudes using nationwide survey data from Project Implicit. Average regional biases against Black people, White people, and gay people are associated with regional differences in social media hostility, and this effect is confounded with regional racial and ideological opposition. In addition, intraregional variability in interracial attitudes is also positively associated with online hostility. In other words, there is greater online hostility in regions where residents disagree in their interracial attitudes. This effect is present both for the full resident sample and when restricting the sample to White attitude holders. We find that this relationship is also, in part, confounded with regional proportions of ideological and racial groups (attitudes are more heterogeneous in regions with greater ideological and racial diversity). We discuss potential mechanisms underlying these relationships, as well as the dangers of escalating conflict and hostility when individuals with diverging intergroup attitudes interact. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

Ant Colony Optimization Algorithm for understanding of trade-offs between safety and benefit: a case of Beijing taxi service system

Creating and maintaining a high level of both safety and productivity is a primary objective for many industries, especially those endowed with pursuit of commercial profits which are tightly linked with higher exposure to occupational risks, such as commercial transportation service industry. As a typical case, Beijing taxi service system (BTSS) operates for trade-offs between safety and benefit but under a decentralized and loose control at the sharp-end level, which impels taxi drivers to tackle routine work in a highly cooperative manner, e.g., interacting, communicating and collaborating in local groups. Based on resemblances between the collective behavioral patterns of the driver groups and social insect systems, Ant Colony Optimization Algorithm (ACOA) is used to investigate mechanisms that coordinate the drivers’ individual efforts, e.g., recruit informational support when needed. The ACOA inference is validated subsequently with empirical evidence based on statistical analysis of the drivers’ attitude bias. Experimentation shows that the mathematical model of ACOA is successful in explaining how collective patterns of the drivers’ decisions are generated, as well as instantiates group-level resilience skills, with the drivers’ flexibly changing strategies towards the trade-offs in different scenarios where competition between safety and benefit escalates. The research findings suggest capacities of resilience and self-organization in the current BTSS, contributing to understandings of the safety-benefit trade-off mechanism that functionally integrates individuals at the sharp end of BTSS. The exploratory applications of ACOA to BTSS provide reference of improving risk and performance management in Beijing taxi service industry, as well as promote coherent research on human cognitive and behavioral properties in complex socio-technical systems.

EMLR for multiple radars on a mobile platform

Aiming at the problem of radar sensor registration on a mobile platform, this study uses multiple radars to estimate the biases of the radar under the earth-centred earth-fixed coordinate system, which provides more accurate information for data fusion. Compared to the maximum likelihood registration (MLR) algorithm, which can only estimate radar offset biases, a novel extended MLR (EMLR) algorithm is proposed. The algorithm could estimate radar-offset biases, attitude biases, and the target real location simultaneously. The simulation results verified that the EMLR algorithm can effectively improve the precision of registration.

Relative sensor registration with two‐step method for state estimation

State estimation suffers from some new challenging problems with a multi-platform multi-sensor observation system. An important problem for multisensor integration is that the data from the local sensors needs to be transformed into a common reference frame free of systematic bias or registration. In this study, the relative sensor registration problem is discussed. It aligns measurement from the global sensor with the local sensor under the assumptions that the global sensor is bias free and all biases reside with the local sensor. The traditional methods failed in the condition when attitude bias becomes large because the error caused by linearisation of rotation matrix increases with growing attitude bias. Motivated by this, a two-step method is established. By estimating the measurement bias through augmented extended Kalman filter in local sensor coordinate independent of attitude and location bias, and by introducing the unit quaternion method compute the attitude and location bias, the proposed method can avoid the problem the traditional methods faced. Simulation examples are provided to verify the proposed method by comparing with the existing linear least square algorithm.

Modeling and Calibrating the Ground-Surface Beam Pointing of GEO Satellite

As a promising approach to assist the fifth-generation (5G) communication system, geostationary (GEO) satellite communication technology is expected to be utilized to provide an efficient and reliable coverage for the terrestrial cellular network. Most multi-beam GEO satellites work on the low-inclination GEO orbit. Due to various unexpected factors, e.g., the imperfect satellite orbit, attitude, and antenna deformation, the practical satellite beam pointing on the earth surface will deviate unfortunately from its designed theoretical location. Although the center boresight-to-ground point of the satellite multi-beam antenna can be maintained via the control of attitude bias and track retention, the practical beam pointing center would still experience inevitable deviations, causing unwanted ground coverage drifting in engineering applications. To combat this, in this paper, we first provide a comprehensive calculation approach for the actual beam pointing on the ground of a satellite multi-beam, which is also validated via the theoretical analysis on the measurement from a ground-based calibration station. On this basis, a simple yet effective data-driven model is established to characterize the dynamical deviating trends induced by various unexpected influences. Finally, a novel beam pointing calibration scheme is designed, based on the Kalman filter. By tracking the coupling coefficients between elevation angle and azimuth angle in our simple model, a pre-deformation is added to the designed beam. Our proposed approach for the beam pointing calibration is validated by the numerical simulations. An improvement of 78.26% is achieved in maximum ground-surface pointing deviation distance.

Eye-tracking evidence shows that non-fit messaging impacts attention, attitudes and choice

When patients have strong initial attitudes about a medical intervention, they might not be open to learning new information when choosing whether or not to receive the intervention. We aim to show that non-fit messaging (messages framed in a manner that is incongruent with recipients’ motivational orientation) can increase attention to the message content, thereby de-intensifying an initial attitude bias and reducing the influence of this bias on choice. In this study, 196 students received information about the pros and cons of a vaccine, framed in either a fit or non-fit manner with their motivational orientation. The results show that when information was presented in a non-fit (vs. fit) manner, the strength of participants’ initial attitude was reduced. An eye-tracking procedure indicated that participants read information more thoroughly (measured by the average length of fixation time while reading) in the non-fit condition versus fit condition. This average time of fixation mediated the effect of message framing on the strength of people’s attitudes. A reduction in attitude was associated with participants’ ability to recall the given information correctly and make a choice consistent with the provided information. Non-fit messaging increases individuals’ willingness to process information when individuals’ pre-existing attitude biases might otherwise cause them to make uninformed decisions.

Improved Spatial Registration and Target Tracking Method for Sensors on Multiple Missiles.

Inspired by the problem that the current spatial registration methods are unsuitable for three-dimensional (3-D) sensor on high-dynamic platform, this paper focuses on the estimation for the registration errors of cooperative missiles and motion states of maneuvering target. There are two types of errors being discussed: sensor measurement biases and attitude biases. Firstly, an improved Kalman Filter on Earth-Centered Earth-Fixed (ECEF-KF) coordinate algorithm is proposed to estimate the deviations mentioned above, from which the outcomes are furtherly compensated to the error terms. Secondly, the Pseudo Linear Kalman Filter (PLKF) and the nonlinear scheme the Unscented Kalman Filter (UKF) with modified inputs are employed for target tracking. The convergence of filtering results are monitored by a position-judgement logic, and a low-pass first order filter is selectively introduced before compensation to inhibit the jitter of estimations. In the simulation, the ECEF-KF enhancement is proven to improve the accuracy and robustness of the space alignment, while the conditional-compensation-based PLKF method is demonstrated to be the optimal performance in target tracking.

The ITASAT CubeSat Development and Design

Because they are inexpensive platforms for satellites, CubeSats have become a low-cost way for universities and even developing countries to have access to space technology. This paper presents the ITASAT design, particularly the Attitude Determination and Control Subsystem, the Onboard Software, and the Assembly,Integration and Testing program. The ITASAT is a 6U CubeSat nano-satellite in development at the Instituto Tecnologico de Aeronautica, in Sao Jose dos Campos, Brazil. The platform and its subsystems will be provided by industry while the payloads are being designed and developed by the principal investigators. The ITASAT Attitude Determination and Control Subsystem will rely on a 3-axis magnetometer, 6 analog cosine sun sensors, 3-axis MEMS gyroscopes, 3 magnetic torque coils, and 3 reaction wheels. The Attitude Determination and Control Subsystem operating modes, control laws, and embedded software are under the responsibility of the Instituto Tecnologico de Aeronautica. A Kalman filter shall be employed to estimate the quaternion attitude and gyroscope biases from sensor measurements. The Attitude Determination and Control Subsystem operating modes are the nominal mode, with geocentric pointing attitude control and the stabilization mode, in which only the satellite angular velocity is controlled. The nominal mode will be split into 2 sub-modes: reaction wheel control plus magnetic wheel desaturation and 3-axis magnetic attitude control. Simulation results have shown that the attitude can be controlled with 1-degree accuracy in nominal mode with the reaction wheels, but these errors grow as much as 20 degrees or higher with the 3-axis magnetic control.

The malleability of stigmatizing attitudes: Combining imagined social contact with implicit attitude feedback

ABSTRACTResearch is reported that examines whether imagined social contact combined with implicit attitude feedback may be an effective intervention for inducing changes in attitudes toward mental ill health. The Implicit Relational Assessment Procedure (IRAP) captured participants’ implicit attitudes toward individuals with a mental illness and provided a measure of attitude bias. Forty-eight participants (17 male, 95.8% White British) were randomly assigned to one of four experimental conditions: (1) Imagined social contact with implicit attitude feedback, (2) imagined social contact without feedback, (3) control with feedback, and (4) control without feedback. This resulted in a data set detailing 12,288 implicit responses, with each participant completing 256 IRAP trials. Participants then completed an attitude change assessment 24 hours later. Results revealed that imagined social contact was successful in changing implicit attitudes, with the addition of implicit attitude feedback further strengthen...

GRACE star camera noise

Extending results from previous work by Bandikova et al. (2012) and Inacio et al. (2015), this paper analyzes Gravity Recovery and Climate Experiment (GRACE) star camera attitude measurement noise by processing inter-camera quaternions from 2003 to 2015. We describe a correction to star camera data, which will eliminate a several-arcsec twice-per-rev error with daily modulation, currently visible in the auto-covariance function of the inter-camera quaternion, from future GRACE Level-1B product releases. We also present evidence supporting the argument that thermal conditions/settings affect long-term inter-camera attitude biases by at least tens-of-arcsecs, and that several-to-tens-of-arcsecs per-rev star camera errors depend largely on field-of-view.

Is robustness really robust? How different definitions of robustness impact decision-making under climate change

Robust decision-making is being increasingly used to support environmental resources decisions and policy analysis under changing climate and society. In this context, a robust decision is a decision that is as much as possible insensitive to a large degree of uncertainty and ensures certain performance across multiple plausible futures. Yet, the concept of robustness is neither unique nor static. Multiple robustness metrics, such as maximin, optimism-pessimism, max regret, have been proposed in the literature, reflecting diverse optimistic/pessimistic attitudes by the decision maker. Further, these attitudes can evolve in time as a response to sequences of favorable (or adverse) events, inducing possible dynamic changes in the robustness metrics. In this paper, we explore the impact of alternative definitions of robustness and their evolution in time for a case of water resources system management under changing climate. We study the decisions of the Lake Como operator, who is called to regulate the lake by balancing irrigation supply and flood control, under an ensemble of climate change scenarios. Results show a considerable variability in the system performance across multiple robustness metrics. In fact, the mis-definition of the actual decision maker’s attitude biases the simulation of its future decisions and produces a general underestimation of the system performance. The analysis of the dynamic evolution of the decision maker’s preferences further confirms the potentially strong impact of changing robustness definition on the decision-making outcomes. Climate change impact assessment studies should therefore include the definition of robustness among the uncertain parameters of the problem in order to analyze future human decisions under uncertainty.

Effective of College Students’ Contraceptive Practice on Sexual Knowledge, Sexual Attitude, and Optimistic Bias of Venereal Disease

This study aimed to identify the relationships of college students’ contraceptive practice with their sexual knowledge, sexual attitude, and optimistic bias of venereal disease, and to identify the influencing factors on it. 148 students in a university participated in the study. Contraceptive practice showed positive correlations with sexual knowledge, pleasurable sexual attitude, and responsibility sexual attitude. Stepwise multiple regressions identified sexual knowledge and pleasurable sexual attitude as the influencing factors on contraceptive practice, but with a low testing power of 15.6%. We found that high sexual knowledge and positive sexual attitude lead to better practice for contraception. However, as the degree of influence was low, further research to identify the influencing factor on contraceptive practice is needed. On the other hand, the sexual education of college students needs to provide more concrete methods besides condom for contraceptive practice including the use of various instruments such as emergency contraceptive drug for more effective results.