Journal Press India^®

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This research investigates the potential influence of social media investor sentiment on short-term abnormal stock returns for NIFTY 100 companies when earnings reports are released. The paper merges an event-study approach with a sentiment-text analysis of social media reports mentioning the companies. Public social media (Twitter/X, etc.) are collated over a specified event window for each company’s quarterly earnings release. A sentiment score is derived from a finance-oriented lexicon utilized within a machine learning Natural Language Processing (NLP) framework. The market model is used to estimate abnormal returns; with robustness checks performed using the Fama–French 3-factor model. The study offers evidence of the informational role social media plays for earnings announcements specific to India centered on the micro-level investor sentiment surrounding large, liquid equities. The research design is tailored to be practically executable within a three-month timeframe, using a limited but statistically significant sample of 40–60 earnings announcement events.

Keywords

Social media sentiment; Abnormal returns; Earnings announcements; Event study

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