Patient narratives on social networks contain large amounts of objective information, such as
the descriptions of examinations and interventions. Sentiment analysis (SA) models are …

Owing to the quick spread of minute health-related experiences, the distillation of knowledge
from such unstructured narratives is an extremely challenging task. In spite of the success of …

The automatic generation of features without human intervention is the most critical task for
biomedical sentiment analysis. Regarding the high dynamicity of shared patient narrative …

Online review sites and opinion forums contain a wealth of information regarding user
preferences and experiences over multiple product domains. This information can be …

Everyday patients' narratives on social media can reveal crucial public health issues. Mining
those online narratives, which remained so far unconsidered, may mirror further hidden …

User-generated content on healthcare web forums, particularly drug reviews, provides
valuable information on drug benefits, effectiveness, side effects, dosage, condition, cost …

Getting accurate, honest, reliable and credible minute insight is the most crucial objective of
conducting medical and pharmaceutical research on social media. Nowadays, healthcare …

Aspect-based sentiment analysis is a natural language processing task whose aim is to
automatically classify the sentiment associated with a specific aspect of a written text. In this …

Introduction: Exploiting information in health-related social media services is of great interest
for patients, researchers and medical companies. The challenge is, however, to provide …

Online medical services have become increasingly popular, and patient feedback can
significantly influence other patients' medical decision-making. This study utilizes a double …