@article{BerdicevskisCousseKoplenigetal.2023,
  author    = {Aleksandrs Berdicevskis and Evie Couss{\´e} and Alexander Koplenig and Yvonne Adesam},
  title     = {To drop or not to drop? Predicting the omission of the infinitival marker in a Swedish future construction},
  series   = {Corpus Linguistics and Linguistic Theory},
  volume    = {20},
  number    = {1},
  publisher = {de Gruyter},
  address   = {Berlin/Boston},
  issn      = {1613-7035},
  doi       = {10.1515/cllt-2022-0101},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-117371},
  pages     = {219 -- 261},
  year      = {2023},
  abstract  = {We investigate the optional omission of the infinitival marker in a Swedish future tense construction. During the last two decades the frequency of omission has been rapidly increasing, and this process has received considerable attention in the literature. We test whether the knowledge which has been accumulated can yield accurate predictions of language variation and change. We extracted all occurrences of the construction from a very large collection of corpora. The dataset was automatically annotated with language-internal predictors which have previously been shown or hypothesized to affect the variation. We trained several models in order to make two kinds of predictions: whether the marker will be omitted in a specific utterance and how large the proportion of omissions will be for a given time period. For most of the approaches we tried, we were not able to achieve a better-than-baseline performance. The only exception was predicting the proportion of omissions using autoregressive integrated moving average models for one-step-ahead forecast, and in this case time was the only predictor that mattered. Our data suggest that most of the language-internal predictors do have some effect on the variation, but the effect is not strong enough to yield reliable predictions.},
  language  = {en}
}