Verifying the Medical Specialty from User Profile of Online Community for Health-Related Advices

TL;DR

This paper presents a novel computer-linguistic method to verify users' medical specialties in online health communities, aiming to improve information reliability and prevent misinformation.

Contribution

It introduces a new algorithm and indicator system for accurately determining medical specialties from user profiles using linguistic analysis and training samples.

Findings

The method effectively verifies medical specialties in online communities.

The indicator system accurately classifies user expertise.

The approach enhances trustworthiness of health advice online.

Abstract

The paper describes the verifying methods of medical specialty from user profile of online community for health-related advices. To avoid critical situations with the proliferation of unverified and inaccurate information in medical online community, it is necessary to develop a comprehensive software solution for verifying the user medical specialty of online community for health-related advices. The algorithm for forming the information profile of a medical online community user is designed. The scheme systems of formation of indicators of user specialization in the profession based on a training sample is presented. The method of forming the user information profile of online community for healthrelated advices by computer-linguistic analysis of the information content is suggested. The system of indicators based on a training sample of users in medical online communities is formed. The matrix of medical specialties indicators and method of determining weight coefficients these indicators is investigated. The proposed method of verifying the medical specialty from user profile is tested in online medical community.