The dataset was created by using the Facebook app to gather comments from users. These comments were sourced from various posts on pages about medical topics, as well as news, economy, education, and sports. These comments, which are short pieces of text, were categorized as either positive (medical) or negative (non-medical) for the purpose of text classification. The negative comments make up 55% of the dataset, while the positive comments make up 45%.
The dataset was created by using the Facebook app to gather comments from users. These comments were sourced from various posts on pages about medical topics, as well as news, economy, education, and sports. These comments, which are short pieces of text, were categorized as either positive (medical) or negative (non-medical) for the purpose of text classification. The negative comments make up 55% of the dataset, while the positive comments make up 45%.
The dataset was created by using the Facebook app to gather comments from users. These comments were sourced from various posts on pages about medical topics, as well as news, economy, education, and sports. These comments, which are short pieces of text, were categorized as either positive (medical) or negative (non-medical) for the purpose of text classification. The negative comments make up 55% of the dataset, while the positive comments make up 45%.
