On How Users Edit Computer-Generated Visual Stories
Table 1. Average number of tokens with each POS tag per story. The universal part-of-speech tagset provided by NLTK toolkit was used. Δ denoted the differences in average token numbers between between post- and pre-edit stories. The “DET” (determiner, article) tag contributes the most to the reduction of story length, and the “.” (punctuation marks) tag contributes the second.
['[EMPTY]', '[BOLD] ADJ', '[BOLD] ADP', '[BOLD] ADV', '[BOLD] CONJ', '[BOLD] DET', '[BOLD] NOUN', '[BOLD] NUM', '[BOLD] PRT', '[BOLD] PRON', '[BOLD] VERB', '[BOLD] .', '[BOLD] Total']
We also analyzed the parts of speech of the words in each story. We observed that the “DET” (determiner, article) tag contributes the most to the reduction of story length, while the number of “PRON” (pronoun) tags increased the most. In order to understand the possible reasons behind this phenomenon, we observed the stories that had fewer DET tags but more PRON tags after post editing. We found that the nouns with determiners and articles (DET) are often replaced by pronouns (PRON). The following is a typical example, where the replacement texts are highlighted in red.