Affective multimedia databases – state of the art (2)

Apart from databases in the table, two more important sources of affective text corpora exist: WordNet-Affect and SemEval.

These two databases are not specifically designed for emotion elicitation experiments although they can be indi-rectly used in this domain. WordNet-Affect is taxonomy of over two hundred emo-tions and emotion-related terms. It is aligned with WordNet concepts and could be used to classify text labels in semantic and affective domains. SemEval is a set of different lexicons for word sense disambiguation semantic analysis and senti-ment evaluation, which were collaboratively developed by different researchers dur-ing a series of yearly evaluation workshops.

Some SemEval data such as SemCor and the previously mentioned SemEval can be used to support emotion elicitation with annotated multimedia. It should be noted that the advanced sentiment analysis is concerned with extraction of discrete emotion states such as “happiness”, “sadness” or “anger” from text documents. Therefore, sentiment classification could also be considered as a subtype of emotion classification.

As mentioned before multimedia stimuli are described with at least one of the two emotion theories: categorical or dimensional. The dimensional theories of emotion propose that affective meaning can be well characterized by a small number of dimensions. Dimensions are chosen on their ability to statistically characterize subjective emotional ratings with the least number of dimensions possible. These dimensions generally include one bipolar or two unipolar dimensions that represent positivity and negativity and have been labeled in various ways, such as valence or pleasure. Also usually included is a dimension that captures intensity, arousal, or energy level. In contrast to the dimensional theories, categorical theories claim that the dimensional models, particularly those using only two or three dimensions, do not accurately reflect the neural systems underlying emotional responses. Instead, supporters of these theories propose that there are a number of emotions that are universal across cultures and have an evolutionary and biological basis. Which discrete emotions are included in these theories is a point of contention, as is the choice of which dimensions to include in the dimensional models. Most supporters of discrete emotion theories agree that at least the five primary emotions of happiness, sadness, anger, fear and disgust should be included.

Dimensional and categorical theories of affect can both effectively describe emotion in digital systems but are not mutually exclusive. Many researchers who predominately use the dimensional model regard the positive and negative valence systems as appetitive and defensive systems, with arousal representing the intensity of activation within each system. It has been experimentally proved that visual stimuli from the IAPS produce different responses in skin conductance, startle reflex and heart rate depending on emotion category. Also, some categorical approaches already incorporate intensity or arousal into their models. With these empirical overlaps in theories of emotion, visual stimuli previously only characterized according to a single theory have now been characterized according to the complimentary emotion theory, including IAPS, IADS and ANEW. Annotations according to both theories of affect are useful for several reasons, predominantly because they providing a more complete characterization of stimuli affect. Additionally, apart from theories of emotion based on discrete categories or dimensions, numerous other paradigms exist for description of sentiments, appraisals, action tendencies and categorization of emotion states.