Impact of social media sentiments in stock market predictions: A bibliometric analysis

Abstract

The main objective of the paper is to anticipate a bibliometric analysis of the research on stock market prediction using social media sentiments. The study has taken out a total of 1450 documents from the year Jan 2010 to Dec 2020. This study attempts to identify a significant journal that has maximum documents, most prolific author, most cited papers, countries, institutions, co-authorship network analysis map, inter-country co-authorship network analysis map, and keyword occurrences. The study has used the Scopus database for analyzing the large set of data of research papers that are counted in the study. And the VOSviewer software is used for generating the maps such as co-authorship analysis network map and keyword occurrence network.