Analysis of child development facts and myths using text mining techniques and classification models.

ABSTRACT: The rapid dissemination of misinformation on the internet complicates the decision-making process for individuals seeking reliable information, particularly parents researching child development topics. This misinformation can lead to adverse consequences, such as inappropriate treatment of children based on myths. While previous research has utilized text-mining techniques to predict child abuse cases, there has been a gap in the analysis of child development myths and facts. This study addresses this gap by applying text mining techniques and classification models to distinguish between myths and facts about child development, leveraging newly gathered data from publicly available websites. The research methodology involved several stages. First, text mining techniques were employed to p

SUBMITTER: Tajrian M 

PROVIDER: S-EPMC11388728 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature