ABSTRACT
News articles have a strong effect on the readers’ sentiments, which in turn affects stock markets and the way economies of various countries perform. This chapter’s main idea is based on the efficient market hypothesis that highlights the conjunction of news and information with market performance. The work presented in this chapter analyzes the impact of news headlines on markets and how they affect the global economy during the unprecedented COVID-19 pandemic. This chapter proposes to use the lexicon method to calculate the sentiment values of the news headlines. Based on these values, stock index values are predicted using machine learning algorithms. The chapter predicts the effect of Indian news headlines on the Nifty index. This can then be extrapolated to global economies as well. © 2022 Elsevier Inc. All rights reserved.