The literary genre of poetry is inherently related to the expression and elicitation of emotion via both content and form. To explore the nature of this affective impact at an extremely basic textual level, we collected ratings on eight different general affective meaning scales—valence, arousal, friendliness, sadness, spitefulness, poeticity, onomatopoeia, and liking—for 57 German poems (“die verteidigung der wölfe”) which the contemporary author H. M. Enzensberger had labeled as either “friendly,” “sad,” or “spiteful.” Following Jakobson's (1960) view on the vivid interplay of hierarchical text levels, we used multiple regression analyses to explore the specific influences of affective features from three different text levels (sublexical, lexical, and inter-lexical) on the perceived general affective meaning of the poems using three types of predictors: (1) Lexical predictor variables capturing the mean valence and arousal potential of words; (2) Inter-lexical predictors quantifying peaks, ranges, and dynamic changes within the lexical affective content; (3) Sublexical measures of basic affective tone according to sound-meaning correspondences at the sublexical level (see Aryani et al., 2016). We find the lexical predictors to account for a major amount of up to 50% of the variance in affective ratings. Moreover, inter-lexical and sublexical predictors account for a large portion of additional variance in the perceived general affective meaning. Together, the affective properties of all used textual features account for 43–70% of the variance in the affective ratings and still for 23–48% of the variance in the more abstract aesthetic ratings. In sum, our approach represents a novel method that successfully relates a prominent part of variance in perceived general affective meaning in this corpus of German poems to quantitative estimates of affective properties of textual components at the sublexical, lexical, and inter-lexical level.
