108,908 research outputs found

    'I think you understand me' : studying the associations between actual, assumed, and perceived understanding within couples

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    The current study examined the associations between actual, assumed, and perceived understanding and partners' levels of dyadic adjustment. One hundred fifty-two couples provided questionnaire data (assumed and perceived understanding), participated in a videotaped conflict interaction, and in a video-review task to assess actual understanding (empathic accuracy). The data were analyzed by means of the Actor-Partner Interdependence Model. The results suggest that (a) some aspects of how well someone assumes that (s)he has understood the partner during a preceding conflict interaction were positively associated with his/her own objective level of understanding (actor effect), (b) that someone's perception of how understood (s)he feels was not associated with the partner's objective level of understanding (partner effect), and (c) perceived understanding, but not actual understanding, was positively associated with dyadic adjustment

    Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles

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    In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who think differently have not worked well. In this paper, we hypothesize, first, that previous approaches have not worked because they have been direct -- they have tried to explicitly connect people with those having opposing views on sensitive issues. Second, that neither recommendation or presentation of information by themselves are enough to encourage behavioral change. We propose a platform that mixes a recommender algorithm and a visualization-based user interface to explore recommendations. It recommends politically diverse profiles in terms of distance of latent topics, and displays those recommendations in a visual representation of each user's personal content. We performed an "in the wild" evaluation of this platform, and found that people explored more recommendations when using a biased algorithm instead of ours. In line with our hypothesis, we also found that the mixture of our recommender algorithm and our user interface, allowed politically interested users to exhibit an unbiased exploration of the recommended profiles. Finally, our results contribute insights in two aspects: first, which individual differences are important when designing platforms aimed at behavioral change; and second, which algorithms and user interfaces should be mixed to help users avoid cognitive mechanisms that lead to biased behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User Interfaces 201

    A habituation account of change detection in same/different judgments

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    We investigated the basis of change detection in a short-term priming task. In two experiments, participants were asked to indicate whether or not a target word was the same as a previously presented cue. Data from an experiment measuring magnetoencephalography failed to find different patterns for “same” and “different” responses, consistent with the claim that both arise from a common neural source, with response magnitude defining the difference between immediate novelty versus familiarity. In a behavioral experiment, we tested and confirmed the predictions of a habituation account of these judgments by comparing conditions in which the target, the cue, or neither was primed by its presentation in the previous trial. As predicted, cue-primed trials had faster response times, and target-primed trials had slower response times relative to the neither-primed baseline. These results were obtained irrespective of response repetition and stimulus–response contingencies. The behavioral and brain activity data support the view that detection of change drives performance in these tasks and that the underlying mechanism is neuronal habituation
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