@inproceedings{moorthy-etal-2018-nike,
    title = "Is {N}ike female? Exploring the role of sound symbolism in predicting brand name gender",
    author = "Moorthy, Sridhar  and
      Pogacar, Ruth  and
      Khan, Samin  and
      Xu, Yang",
    editor = "Riloff, Ellen  and
      Chiang, David  and
      Hockenmaier, Julia  and
      Tsujii, Jun{'}ichi",
    booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
    month = oct # "-" # nov,
    year = "2018",
    address = "Brussels, Belgium",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/D18-1142/",
    doi = "10.18653/v1/D18-1142",
    pages = "1128--1132",
    abstract = "Are brand names such as Nike female or male? Previous research suggests that the sound of a person{'}s first name is associated with the person{'}s gender, but no research has tried to use this knowledge to assess the gender of brand names. We present a simple computational approach that uses sound symbolism to address this open issue. Consistent with previous research, a model trained on various linguistic features of name endings predicts human gender with high accuracy. Applying this model to a data set of over a thousand commercially-traded brands in 17 product categories, our results reveal an overall bias toward male names, cutting across both male-oriented product categories as well as female-oriented categories. In addition, we find variation within categories, suggesting that firms might be seeking to imbue their brands with differentiating characteristics as part of their competitive strategy."
}