Emotional Words – The Relationship of Self- and Other-Annotation of Affect in Written Text

AbstractFor human and automatic text annotation of emotions, it is assumed that affect can be traced in language on (combinations of) individual words, text fragments, or other linguistic patterns, which can be identified and labelled correctly. For example, many sentiment analysis systems consider isolated words affectively meaningful units, whose proportions in a given text reveal its overall affective meaning. However, whether these words and their combinations as identified either by humans or algorithms also match the actual feelings of the authors remains unclear. Potential discrepancies between affect expression and perception in text have received surprisingly little scholarly attention, although a number of studies has already identified disparities between self- and other-annotation in affect detection for speech and audio-visual data. Therefore, we ask whether a similar difference shows in annotations of emotions in text.

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