Research pick: Online healthcheck for medical info - "Intelligent model to improve the efficacy of healthcare content marketing by auto-tagging and exploring the veracity of content using opinion mining"

Research in the International Journal of Electronic Marketing and Retailing introduces a new model aimed at assessing the credibility and relevance of online healthcare information. With the proliferation of online health advice, the challenge of distinguishing trustworthy sources from false information has become increasingly important for patients and their carers.

S. Sri Hari of the Illinois Institute of Technology in Chicago, USA, S. Porkodi and R. Saranya of the University of Technology and Applied Sciences, and N. Vijayakumar of the Technical Administrative Training Institute in Muscat, Oman have developed a model that uses sentiment analysis on reader comments to gauge the reliability of digital healthcare content. Using content relevance analysis, word scoring using a lexicon analyzer, and classification via a maximum entropy model, the model generates what the team refers to as a veracity score, which can help users make a better-informed decision about the information they find online.

The researchers tested their model using healthcare content and found it to work effectively in evaluating the veracity of information. The new model could have significant implications for content marketing efforts within the healthcare sector, providing users with tailored recommendations while enhancing the credibility of digital healthcare information. The model’s ability to identify and highlight trustworthy content benefits patients and carers as consumers.

The model’s impact could affect all age groups, youngsters, the middle-aged, and an ageing population. The identification of reliable healthcare information among the vast number of online medical and health resources is critical. The model could allow better-informed decision-making and mitigate the problems that might arise through the spread of misinformation.

Future work will expand the model’s capabilities by developing tools to analyse multimedia content and incorporate additional mechanisms to identify misinformation and disinformation.

Hari, S.S., Porkodi, S., Saranya, R. and Vijayakumar, N. (2024) ‘Intelligent model to improve the efficacy of healthcare content marketing by auto-tagging and exploring the veracity of content using opinion mining’, Int. J. Electronic Marketing and Retailing, Vol. 15, No. 2, pp.240–260.