• Exploring quantitative modelling of semantic factors for content marketing 

      Xavier, Kevin (Master thesis; Mastergradsoppgave, 2023-05-31)
      Developments in business analytics as well as an increased availability of data has allowed digital marketers to better understand and capitalize on consumer behavior to maximize the engagement with marketing materials. However, because most previous studies in this field have focused on consumer behavior theory, they have been largely limited in scope due to small datasets and reliance on human-labeled ...
    • From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’ 

      Nesset, Tore; Xavier, Kevin (Journal article; Tidsskriftartikkel; Peer reviewed, 2023)
      The present study reports on a machine learning experiment concerning mobile vowels in the Russian preposition v ‘in(to)’. It is shown that a neural network is able to predict mobile vowels in 97.4% of the cases in our dataset, and a decision tree is used to extract a set of three rules that a language learner can use to achieve nearly the same level of accuracy. We argue that these rules are ...