Analyzing Wrap-Up Effects through an Information-Theoretic Lens

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Numerous analyses of reading time (RT) data have been undertaken in the effort to learn more about the internal processes that occur during reading comprehension. However, data measured on words at the end of a sentence–or even clause–is often omitted due to the confounding factors introduced by so-called “wrap-up effects,” which manifests as a skewed distribution of RTs for these words. Consequently, the understanding of the cognitive processes that might be involved in these effects is limited. In this work, we attempt to learn more about these processes by looking for the existence–or absence–of a link between wrap-up effects and information theoretic quantities, such as word and context information content. We find that the information distribution of prior context is often predictive of sentence- and clause-final RTs (while not of sentence-medial RTs), which lends support to several prior hypotheses about the processes involved in wrap-up effects.

@inproceedings{meister-et-al-2022-analyzing,
    author = {
        Clara Meister and
        Tiago Pimentel and
        Thomas Clark and
        Ryan Cotterell and
        Roger Levy
    },
    booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
    title = {Analyzing Wrap-Up Effects through an Information-Theoretic Lens},
    year = {2022},
    doi = {10.18653/v1/2022.acl-short.3},
    url = {https://aclanthology.org/2022.acl-short.3/},
    pages = {20--28},
}