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Popularity Prediction of Online Social Media Content: A Bibliometric Analysis

  • Garima Anand,
  • Shilpa Srivastava,
  • Anish Shandilya,
  • Aprna Tipathi

摘要

An online social network is a platform that enables individuals to interact with others who have similar backgrounds, preferences, activities, and associations. The number of features available and the format of each online social network range widely. Users of online social networks, such as Twitter, Instagram, Flicker, and Pinterest, have increased dramatically in recent years. Content sharing is the most popular feature of online social networks, used by both specific users and big enterprises. This study has used bibliometric methods to analyze the growth of the social media popularity prediction on online social network content from 2013 to 2022. The publications have been extracted from the dimensions database, and the VOS viewer software was used to visualize research patterns. The finding provides valuable information on the publication year, authors, author’s country, author’s organizational affiliations, publishing journals, etc. Based on the findings of this analysis, researchers will be able to design their studies better and add more insights into their empirical studies.