Perspectives on emotions from evolution theory were initiated in the late 19th century with Charles Darwin's book The Expression of Emotions in Man and Animals. Darwin's original thesis was that emotions evolved via natural selection and therefore have cross-culturally universal counterparts. Furthermore, animals undergo emotions comparable to our own (see emotion in animals). Evidence of universality in the human case has been provided by Paul Ekman's seminal research on facial expression. Other research in this area focuses on physical displays of emotion including body language of animals and humans. The increased potential in neuroimaging has also allowed investigation into evolutionarily ancient parts of the brain. Important neurological advances were made from these perspectives in the 1990s by, for example, Joseph E. LeDoux and Antonio Damasio.
American evolutionary biologist Robert Trivers argues that moral emotions are based on the principle of reciprocal altruism. The notion of group selection is of particular relevance. This theory posits the different emotions have different reciprocal effects. Sympathy prompts a person to offer the first favor, particularly to someone in need for whom the help would go the furthest. Anger protects a person against cheaters who accept a favor without reciprocating, by making him want to punish the ingrate or sever the relationship. Gratitude impels a beneficiary to reward those who helped him in the past. Finally, guilt prompts a cheater who is in danger of being found out, by making them want to repair the relationship by redressing the misdeed. As well, guilty feelings encourage a cheater who has been caught to advertise or promise that he will behave better in the future.
We try to regulate our emotions to fit in with the norms of the situation, based on many—sometimes conflicting—demands upon us which originate from various entities studied by sociology on a micro level—such as social roles and 'feeling rules' the everyday social interactions and situations are shaped by—and, on a macro level, by social institutions, discourses, ideologies etc. For example, (post-) modern marriage is, on one hand, based on the emotion of love and on the other hand the very emotion is to be worked on and regulated by it. The sociology of emotions also focuses on general attitude changes in a population. Emotional appeals are commonly found in advertising, health campaigns and political messages. Recent examples include no-smoking health campaigns and political campaign advertising emphasizing the fear of terrorism.
Depending on the particular school's general emphasis either on cognitive components of emotion, physical energy discharging, or on symbolic movement and facial expression components of emotion, different schools of psychotherapy approach human emotions differently. While, for example, the school of Re-evaluation Counseling proposes that distressing emotions are to be relieved by "discharging" them—hence crying, laughing, sweating, shaking and trembling; other more cognitively oriented schools approach them via their cognitive components, such as rational emotive behavior therapy. Yet others approach emotions via symbolic movement and facial expression components (like in contemporary Gestalt therapy).
In the 2000s, research in computer science, engineering, psychology and neuroscience has been aimed at developing devices that recognize human affect display and model emotions. In computer science, affective computing is a branch of the study and development of artificial intelligence that deals with the design of systems and devices that can recognize, interpret and process human emotions. It is an interdisciplinary field spanning computer sciences, psychology and cognitive science. While the origins of the field may be traced as far back as to early philosophical enquiries into emotion, the more modern branch of computer science originated with Rosalind Picard's 1995 paper on affective computing. Detecting emotional information begins with passive sensors which capture data about the user's physical state or behavior without interpreting the input. The data gathered is analogous to the cues humans use to perceive emotions in others. Another area within affective computing is the design of computational devices proposed to exhibit either innate emotional capabilities or that are capable of convincingly simulating emotions. Emotional speech processing recognizes the user's emotional state by analyzing speech patterns. The detection and processing of facial expression or body gestures is achieved through detectors and sensors.