1,721,086 research outputs found
OhSupplementalMaterial – Supplemental material for Revealing Hidden Gender Biases in Competence Impressions of Faces
No full textSupplemental material, OhSupplementalMaterial for Revealing Hidden Gender Biases in Competence Impressions of Faces by DongWon Oh, Elinor A. Buck and Alexander Todorov in Psychological Science</p
OhOpenPracticesDisclosure – Supplemental material for Revealing Hidden Gender Biases in Competence Impressions of Faces
No full textSupplemental material, OhOpenPracticesDisclosure for Revealing Hidden Gender Biases in Competence Impressions of Faces by DongWon Oh, Elinor A. Buck and Alexander Todorov in Psychological Science</p
sj-pdf-1-pec-10.1177_03010066231178489 - Supplemental material for Trustworthiness judgments without the halo effect: A data-driven computational modeling approach
No full textSupplemental material, sj-pdf-1-pec-10.1177_03010066231178489 for Trustworthiness judgments without the halo effect:
A data-driven computational modeling approach by DongWon Oh, Nicole Wedel, Brandon Labbree and Alexander Todorov in Perception</p
Alexander Todorov, Face Value: The Irresistible Influence of First Impressions (Princeton, NJ: Princeton University Press). 336 pages. ISBN: 9781400885725. Hardcover $32.95. Book Review.
No full textIn Face Value, Alexander Todorov provides scientific insights regarding a very intuitive and irresistible human inclination: the formation of first impressions. With only a single, split-second glance at someone’s face, people unconsciously form judgements about someone’s character. According to Todorov, these judgements have significant consequences in our everyday life. For example, politicians that look more competent are more likely to get elected. Face Value provides an overview of research into the consequences, origins, and accuracy of first impressions from the face, summarized and examined in this book review
Person Information Facilitates Memory for Face Identity
No full textWe tested whether episodic information about people facilitates memory for
their faces (Experiment 1) and whether this effect is specific for face identity
(Experiment 2). Participants were presented with faces paired with behavioral
descriptions (positive, neutral, or negative) and faces displayed alone. In both
experiments, participants were more likely to recognize faces paired with
behavioral descriptions, and after 1week
delay, their memory was better for
faces paired with descriptions of salient behavior (i.e., with positive and
negative valence) than faces paired with neutral behaviors or faces presented
without information. To examine whether these effects are about memory for
face identity rather than face image memory, in Experiment 2, we presented
different facial images (varying in facial angle) of the same people at the
encoding and at the recognition test. Although this manipulation decreased the
overall recognition, the findings of Experiment 1 were fully replicated. The
findings suggest that minimal affective information is sufficient to facilitate
memory for face identity
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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