Knowledge discovery of scholarly publications on misinformation on social media: A text mining approach

Abstract

Social media is a remarkable outcome of Web 2.0 technology, which is very popular among the Internet users. The general public is using social media as a communication media to fulfil their information requirements on various occasions such as disaster communication, health communication, marketing products and services and political campaigns. However, the openness of social media provides a great platform for misinformation sharing which is a very common problem in social media communication. Hence, the main objectives of this study are to analyse the publication year and total citation count of publications on misinformation on social media and to identify the main disciplines of misinformation studies on social media using the text mining technique. The primary data of this study were extracted from the Web of Science database using the keywords; social media, misinformation, disinformation and fake news on 16th April 2020. The WoS provided 62 search results and all 62 articles were considered in this study. The title of the article, journal, published year, total citation, abstract, author keywords, keywords plus, Web of Science categories, and research areas were extracted from WoS database. The text mining was done manually. According to the results, scholarly publications on misinformation on social media were first published in the year 2012. Scholarly publications were categorized into 10 main categories; Information, Media, Medical information, Social Science, Communication, Health information, Computer science, Other Sciences, Engineering and Management and Finance. The medical information subject area is covering vast varieties of research areas than the other main subject areas.

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