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Extract Genuine Healthcare Posts on Social Media
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l2549.1081219
Subject(s) - social media , scope (computer science) , health care , process (computing) , internet privacy , social media analytics , trustworthiness , computer science , business , data science , public relations , knowledge management , advertising , world wide web , political science , law , programming language , operating system
Social media plays an important role in spreading the news. People who search for health online and those who rely on social media for small health issues and diet management are increasing periodically. Nowadays, food habits are greatly influenced by social media. Health-related data such as home remedies, diet management, and beauty tips are mainly focused in this paper. Such data available in social media may be genuine or might be not, just because of business strategy to promote products suggested. There is a huge scope for misleading vital content in this scenario. This paper gives an overview on how to process data using machine learning techniques and/or deep learning techniques available on social media by applying social media analytics and revile trustworthy information at one place. As well as describes how to create a platform for genuine information about health care.

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