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Machine Learning approach for detecting mental health on Twitter using chrome extension
3rd IEEE Global Conference for Advancement in Technology, GCAT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2191779
ABSTRACT
Social media is used by people to communicate with friends and to share information, such as their feelings and moods. This enables companies to better understand how people think, feel, and act when communicating on various online platforms by analysing emotional data from social networks. People don't seek expert assistance because they are unwilling to do so. Additionally, many people who were kept inside their houses due of the Covid 19 pandemic decided to vent themselves on social media. We intend to create and develop a Chrome plugin that will instantly evaluate the user's tweet in order to solve this issue. Our technology would assess their posts using a machine learning model, then query them. The system will decide whether a user needs professional help based on how they respond to the questions. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd IEEE Global Conference for Advancement in Technology, GCAT 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd IEEE Global Conference for Advancement in Technology, GCAT 2022 Year: 2022 Document Type: Article