Genre Matters: How Text Types Interact with Decoding Strategies and Lexical Predictors in Shaping Reading Behavior

This repository contains the code to reproduce the experiments of the paper "Genre Matters: How Text Types Interact with Decoding Strategies and Lexical Predictors in Shaping Reading Behavior".

Download the data and set path names

• download the EMTeC eye-tracking data via https://github.com/DiLi-Lab/EMTeC with the get_et_data.py script
• make sure the eye-tracking data files are in a directory called data:

├── data
    ├── stimuli.csv
    ├── reading_measures_corrected.csv

Run the analyses

Our analyses are implemented in R:

Run the analysis script:

Rscript src/analyses.R

To run the BoxCox analysis, run:

Rscript src/boxcox_analysis.R 

Citation

@inproceedings{bolliger2025genre,
    title = "Genre Matters: How Text Types Interact with Decoding Strategies and Lexical Predictors in Shaping Reading Behavior",
    author = {Bolliger, Lena Sophia  and
      J{\"a}ger, Lena Ann},
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.emnlp-main.379/",
    pages = "7470--7487",
    ISBN = "979-8-89176-332-6"
}