Expresar coherencia en el momento preciso beneficia a la impre-sión causada.

An analysis was conducted on the modulating role that the emotional coherence between verbal and non-verbal information plays on the formation of impressions. The study involved 301 subjects who made inferences on a woman’s personality based on verbal information on her life (positive, negative), the emotional coherence between verbal and non-verbal information (coherent, neutral, incoherent), and the type of coding, referring to the moment when the verbal and non-verbal information was presented to them (simultaneously, separately). The results showed that when the information is positive, coherent and the coding has been made separately, the person is perceived to be more stable, pleasant and sociable. The results are discussed, along with their implications for the adaptive processes present in natural contexts.Se analizó el papel modulador de la coherencia emocional entre la información verbal y no verbal en la formación de impresiones. Participaron 301 sujetos que realizaron inferencias sobre la personalidad de una mujer a partir de información verbal sobre su vida (positiva, negativa), la coherencia emocional entre la información verbal y no verbal (coherente, neutral, incoherente) y el tipo de codificación, referida al momento en el que se les presentó la información verbal y no verbal (simultánea, separada). Los resultados mostraron que cuando la información es positiva, coherente y la codificación se ha realizado por separado, se considera más estable, amable y sociable a la persona percibida. Se discuten los resultados y su implicación en los procesos adaptativos presentes en los contextos naturalesSe analizó el papel modulador de la coherencia emocional entre la información verbal y no verbal en la formación de impresiones. Participaron 301 sujetos que realizaron inferencias sobre la personalidad de una mujer a partir de información verbal sobre su vida (positiva, negativa), la coherencia emocional entre la información verbal y no verbal (coherente, neutral, incoherente) y el tipo de codificación, referida al momento en el que se les presentó la información verbal y no verbal (simultánea, separada). Los resultados mostraron que cuando la información es positiva, coherente y la codificación se ha realizado por separado, se considera más estable, amable y sociable a la persona percibida. Se discuten los resultados y su implicación en los procesos adaptativos presentes en los contextos naturale

Who's Who with Big-Five: Analyzing and Classifying Personality Traits with Smartphones

In this paper, we investigate the relationship between behavioral characteristics derived from rich smartphone data and self-reported personality traits. Our data stems from smartphones of a set of 83 individuals collected over a continuous period of 8 months. From the analysis, we show that aggregated features obtained from smartphone usage data can be indicators of the Big-Five personality traits. Additionally, we develop an automatic method to infer the personality type of a user based on cellphone usage using supervised learning. We show that our method performs significantly above chance and up to 75.9% accuracy. To our knowledge, this constitutes the first study on the analysis and classification of personality traits using smartphone data

Mining Crowdsourced First Impressions in Online Social Video

While multimedia and social computing research have used crowdsourcing techniques to annotate objects, actions, and scenes in social video sites like YouTube, little work has ad- dressed the crowdsourcing of personal and social traits in online social video or social media content in general. In this paper, we address the problems of (1) crowdsourcing the annotation of first impressions of video bloggers (vloggers) personal and social traits in conversational YouTube videos, and (2) mining the impressions with the goal of modeling the interplay of different vlogger facets. First, we design a human annotation task to crowdsource impressions of vloggers that extends a tradition of studies of personality impressions with the addition of attractiveness and mood impressions. Second, we propose a probabilistic framework using Topic Models to discover prototypical impressions that are data driven, and that combine multiple facets of vloggers. Finally, we address the task of automatically predicting topic impressions using nonverbal and verbal content extracted from videos and comments. Our study of 442 YouTube vlogs and 2,210 annotations collected in Mechanical Turk supports recent literature showing the feasibility to crowdsource interpersonal human impression with comparable quality to what is reported in social psychology research, and provides insights on the interplay among human first impressions. We also show that topic models are useful to discover meaningful prototypical impressions that can be validated by humans, and that different topics can be predicted using different sources of information from vloggers’ nonverbal and verbal content, as well as comments from the audience

Leveraging contextual-cognitive relationships into mobile commerce systems

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyMobile smart devices are becoming increasingly important within the on-line purchasing cycle. Thus the requirement for mobile commerce systems to become truly context-aware remains paramount if they are to be effective within the varied situations that mobile users encounter. Where traditionally a recommender system will focus upon the user – item relationship, i.e. what to recommend, in this thesis it is proposed that due to the complexity of mobile user situational profiles the how and when must also be considered for recommendations to be effective. Though non-trivial, it should be, through the understanding of a user’s ability to complete certain cognitive processes, possible to determine the likelihood of engagement and therefore the success of the recommendation. This research undertakes an investigation into physical and modal contexts and presents findings as to their relationships with cognitive processes. Through the introduction of the novel concept, disruptive contexts, situational contexts, including noise, distractions and user activity, are identified as having significant effects upon the relationship between user affective state and cognitive capability. Experimental results demonstrate that by understanding specific cognitive capabilities, e.g. a user’s perception of advert content and user levels of purchase-decision involvement, a system can determine potential user engagement and therefore improve the effectiveness of recommender systems’ performance. A quantitative approach is followed with a reliance upon statistical measures to inform the development, and subsequent validation, of a contextual-cognitive model that was implemented as part of a context-aware system. The development of SiDISense (Situational Decision Involvement Sensing system) demonstrated, through the use of smart-phone sensors and machine learning, that is was viable to classify subjectively rated contexts to then infer levels of cognitive capability and therefore likelihood of positive user engagement. Through this success in furthering the understanding of contextual-cognitive relationships there are novel and significant advances that are now viable within the area of m-commerce

Spontaneous Inference of Personality Traits and Effects on Memory for Online Profiles

As users navigate online social spaces, they encounter numerous personal profiles, each displaying a unique constellation of attributes. How do users make sense of this information? In our first study, we provide evidence that users spontaneously make personality trait inferences about people from profiles they encounter online, and for certain profiles, preferentially remember this inferred trait content over actual profile content. Study 2 uses several measures of profile coherence to assess how the coherence of user profiles interacts with trait inferences to influence memory for profiles. Findings provide a better understanding of specific profile content that makes profiles memorable and the social-cognitive process utilized when extracting information from profiles

Individual differences and romantic compatibility: the relationship between personality traits, eligibility and ideal partner preference

This thesis explores the relationship between personality traits and ideal partner preference. It presents a review of the topic’s salient literature, specifically, research on: theories of romantic attraction; individual differences in ideal partner preference; online and offline platforms for partner selection; personality factors, relationship initiation, maintenance and satisfaction; and tools to assess compatibility. Eight empirical studies of the relationship between the Big Five personality traits, two Dark Triad traits (psychopathy and Machiavellianism), eligibility and expressed preference for an ideal partner are presented. The thesis incorporates development, piloting and validation of a novel, forced-choice instrument for measuring the trade-offs that occur in partner selection. Studies 1 and 2 test a pilot version of the Ideal Partner Questionnaire (IPQ) instrument, to identify the latent constructs that underpin decisions about ideal partner preference and test their relationship with self- and objectively-rated eligibility and personality traits. Study 3 builds on this by testing the IPQ domains with a larger sample, to refine the tool further and explore Big Five personality and gender differences in expressed preference. Study 4 tests the relationship between ideal partner preference, as measured by the IPQ, eligibility and the dark traits Machiavellianism and subclinical psychopathy. Study 5 tests the relationship between ideal partner preference, as measured by the IPQ, eligibility and emotional intelligence. Studies 6 and 7 test whether romantic beliefs and qualitatively expressed preferences predict ideal partner preference, as measured by the IPQ. Study 8 uses data gathered from couples to determine the extent to which ideal preference correlates to personality and relationship satisfaction in established relationships, rather than in the abstract. Lastly, the potential utility of the IPQ, implications for future research and limitations are discusse