Using a Machine Learning Methodology to Analyze Reddit Posts regarding Child Feeding Information.

The current research used human-coded Reddit posts categorized by already established food parenting concepts (coercive control, structure, autonomy support, recipes) as a basis for machine learning models, with the objective of providing insight into topics related to feeding children discussed on...

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Publicado en:Journal of Child & Family Studies Vol. 30; no. 5; pp. 1290 - 1299
Autores principales: Donelson, Curtis, Sutter, Carolyn, Pham, Giang V., Narang, Kanika, Wang, Chen, Yun, Joseph T.
Formato: Artículo
Publicado: Springer Nature May2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Using a Machine Learning Methodology to Analyze Reddit Posts regarding Child Feeding Information.
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          Donelson, Curtis
          Sutter, Carolyn
          Pham, Giang V.
          Narang, Kanika
          Wang, Chen
          Yun, Joseph T.
        affil: University of Illinois at Urbana-Champaign, 601 E John St, 61820, Champaign, IL, USA
      su:
        Reddit (Web resource)
        Food habits
        Social media
        Information resources
        Artificial feeding of children
        Machine learning
        Text messages
        Support vector machines
      sug:
        subj:
          Food habits
          Social media
          Information resources
          Wireless Telecommunications Carriers (except Satellite)
          Artificial feeding of children
          Machine learning
          Text messages
          Support vector machines
          Reddit (Web resource)
      keyword:
        Computational methods
        Feeding
        Parenting
        Computational methods
        Feeding
        Parenting
      ab: The current research used human-coded Reddit posts categorized by already established food parenting concepts (coercive control, structure, autonomy support, recipes) as a basis for machine learning models, with the objective of providing insight into topics related to feeding children discussed on social media and to provide a way for future research to use our trained machine-learned model. Reddit posts from specific, parenting-related subreddits were collected and labeled as they related to aspects of child-feeding behavior. Posts were then put through text pre-processing, converted into TF-IDF vectors, and used to train support vector machine binary and multiclass classification models. Other classifiers and text-preprocessing steps were also tested. After training, the binary model was able to classify posts with 86.1% accuracy as being about child feeding or not, up from a baseline accuracy of 57.6%. The multiclass model yielded a 79.1% accuracy to classify posts related to four categories of child feeding concepts (coercive control, autonomy support, structure, recipes), up from a baseline of 51.9%. The comparison models were found to perform less favorably. The best performing binary model is publicly available for use via the Social Media Macroscope and we provide details on how to use this model. Information is presented such that other researchers and professionals interested in examining issues related to feeding children posted on social media could effectively utilize the same approach. Highlights: Machine learning models based on human-coded Reddit posts were developed. The binary model can classify posts as being about child feeding with 86.1% accuracy. The multiclass model can classify child feeding concepts in posts with 79.1% accuracy. The best performing binary model is made available for use with instructions provided.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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