EmpathyEmpathy is the capacity to understand or feel what another person is experiencing from within their frame of reference, that is, the capacity to place oneself in another's position. Definitions of empathy encompass a broad range of social, cognitive, and emotional processes primarily concerned with understanding others (and others' emotions in particular). Types of empathy include cognitive empathy, emotional (or affective) empathy, somatic empathy, and spiritual empathy.
Empathy quotientEmpathy quotient (EQ) is a psychological self-report measure of empathy developed by Simon Baron-Cohen and Sally Wheelwright at the Autism Research Centre at the University of Cambridge. EQ is based on a definition of empathy that includes cognition and affect. According to the authors of the measure, empathy is a combination of the ability to feel an appropriate emotion in response to another's emotion and the ability to understand anothers' emotion (this is associated with the theory of mind).
Factor analysisFactor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it is possible that variations in six observed variables mainly reflect the variations in two unobserved (underlying) variables. Factor analysis searches for such joint variations in response to unobserved latent variables.
Simulation theory of empathyThe simulation theory of empathy holds that humans anticipate and make sense of the behavior of others by activating mental processes that, if they culminated in action, would produce similar behavior. This includes intentional behavior as well as the expression of emotions. The theory says that children use their own emotions to predict what others will do; we project our own mental states onto others. Simulation theory is not primarily a theory about empathy, but rather a theory of how people understand others—that they do so by way of a kind of empathetic response.
Emotional intelligenceEmotional intelligence (EI) is most often defined as the ability to perceive, use, understand, manage, and handle emotions. People with high emotional intelligence can recognize their own emotions and those of others, use emotional information to guide thinking and behavior, discern between different feelings and label them appropriately, and adjust emotions to adapt to environments. Although the term first appeared in 1964, it gained popularity in the 1995 bestselling book Emotional Intelligence by science journalist Daniel Goleman.
Confirmatory factor analysisIn statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social science research. It is used to test whether measures of a construct are consistent with a researcher's understanding of the nature of that construct (or factor). As such, the objective of confirmatory factor analysis is to test whether the data fit a hypothesized measurement model. This hypothesized model is based on theory and/or previous analytic research.
Construct validityConstruct validity concerns how well a set of indicators represent or reflect a concept that is not directly measurable. Construct validation is the accumulation of evidence to support the interpretation of what a measure reflects. Modern validity theory defines construct validity as the overarching concern of validity research, subsuming all other types of validity evidence such as content validity and criterion validity.
Emotional laborEmotional labor is the process of managing feelings and expressions to fulfill the emotional requirements of a job. More specifically, workers are expected to regulate their personas during interactions with customers, co-workers, clients, and managers. This includes analysis and decision-making in terms of the expression of emotion, whether actually felt or not, as well as its opposite: the suppression of emotions that are felt but not expressed.
Affect displayAffect displays are the verbal and non-verbal displays of affect (emotion). These displays can be through facial expressions, gestures and body language, volume and tone of voice, laughing, crying, etc. Affect displays can be altered or faked so one may appear one way, when they feel another (e.g., smiling when sad). Affect can be conscious or non-conscious and can be discreet or obvious. The display of positive emotions, such as smiling, laughing, etc.
Prosocial behaviorProsocial behavior, or intent to benefit others, is a social behavior that "benefit[s] other people or society as a whole", "such as helping, sharing, donating, co-operating, and volunteering". Obeying the rules and conforming to socially accepted behaviors (such as stopping at a "Stop" sign or paying for groceries) are also regarded as prosocial behaviors. These actions may be motivated by empathy and by concern about the welfare and rights of others, as well as for egoistic or practical concerns, such as one's social status or reputation, hope for direct or indirect reciprocity, or adherence to one's perceived system of fairness.
Affect (psychology)Affect, in psychology, refers to the underlying experience of feeling, emotion, attachment, or mood. The modern conception of affect developed in the 19th century with Wilhelm Wundt. The word comes from the German Gefühl, meaning "feeling". A number of experiments have been conducted in the study of social and psychological affective preferences (i.e., what people like or dislike). Specific research has been done on preferences, attitudes, impression formation, and decision-making.
Affective computingAffective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. While some core ideas in the field may be traced as far back as to early philosophical inquiries into emotion, the more modern branch of computer science originated with Rosalind Picard's 1995 paper on affective computing and her book Affective Computing published by MIT Press.
PsychometricsPsychometrics is a field of study within psychology concerned with the theory and technique of measurement. Psychometrics generally refers to specialized fields within psychology and education devoted to testing, measurement, assessment, and related activities. Psychometrics is concerned with the objective measurement of latent constructs that cannot be directly observed. Examples of latent constructs include intelligence, introversion, mental disorders, and educational achievement.
Sampling (statistics)In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population, and thus, it can provide insights in cases where it is infeasible to measure an entire population.
Data analysisData analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
Affective scienceAffective science is the scientific study of emotion or affect. This includes the study of emotion elicitation, emotional experience and the recognition of emotions in others. Of particular relevance are the nature of feeling, mood, emotionally-driven behaviour, decision-making, attention and self-regulation, as well as the underlying physiology and neuroscience of the emotions. An increasing interest in emotion can be seen in the behavioral, biological and social sciences.
Exploratory data analysisIn statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts traditional hypothesis testing. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments.
Moral emotionsMoral emotions are a variety of social emotion that are involved in forming and communicating moral judgments and decisions, and in motivating behavioral responses to one's own and others' moral behavior. As defined by Jonathan Haidt, moral emotions "are linked to the interests or welfare either of a society as a whole or at least of persons other than the judge or agent". A person may not always have clear words to articulate, yet simultaneously, that same person knows it to be true deep down inside.
Social scienceSocial science is one of the branches of science, devoted to the study of societies and the relationships among individuals within those societies. The term was formerly used to refer to the field of sociology, the original "science of society", established in the 19th century. In addition to sociology, it now encompasses a wide array of academic disciplines, including anthropology, archaeology, economics, human geography, linguistics, management science, communication science and political science.
Sampling errorIn statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population. It can produced biased results. Since the sample does not include all members of the population, statistics of the sample (often known as estimators), such as means and quartiles, generally differ from the statistics of the entire population (known as parameters). The difference between the sample statistic and population parameter is considered the sampling error.
