Information gathered by the robot (from the websites, e-mails or via auditory modules) can be affectively assessed to extract their emotional meaning. All necessary functions to achieve this goal, are implemented by UANEW, USentiWordNet and UWordNet modules. The first one utilizes ANEW (Affective Norms for English Words) project, which is a database containing emotional ratings for a large number of English words. It can be used for evaluating a word or a set of words in terms of feelings they are associated with. USentiWordNet is based on a project similar to ANEW - SentiWordNet. It is a lexical resource for opinion mining, assigning ratings to groups of semantic synonyms (synsets). UWordNet plays a different role than the two previous modules. It is an interface to WordNet - a large lexical database of English words, in which nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets), each expressing a distinct concept. When the word cannot be assessed by previous modules, UWordNet is used as a synonyms dictionary to find the basic form of a word.
// appraise given text by both systems ANEW and SentiWordNet robot.appraisal.Evaluate("text to appraise");
This part of appraisal structure is based of UANEW module - emotional content analysis of the text. ANEW (Affective Norms for English Words) is a database containing valence (pleasure), arousal and dominance ratings for a large number of English words. It can be used for evaluating a word or a set of words in terms of feelings it is associated with by a computer.
// number of founded words in the database robot.appraisal.anew.count; // mean value of pleasure for given text robot.appraisal.anew.pleasure; // mean value of arousal for given text robot.appraisal.anew.arousal; // mean value of dominance for given text robot.appraisal.anew.dominance;
This part of appraisal structure is based of USentiWordNet module - emotional content analysis of the text. SentiWordNet is a lexical resource for opinion mining. SentiWordNet assigns to each synset of WordNet three sentiment scores: positivity, negativity, objectivity.
// number of founded words in the database robot.appraisal.sentiwordnet.count; // mean value of positive score for given text robot.appraisal.sentiwordnet.positive; // mean value of negative score for given text robot.appraisal.sentiwordnet.negative; // mean value of objective score for given text robot.appraisal.sentiwordnet.objective;