Impact of social media on funding success of startups an Indian perspective

Abstract

Social media brought in the revolution in the way business is run. Start-ups have been the phenomenon of the 21st century and have immensely gained from the revolution in social media. This study attempts to advance the understanding of social media usage by start-ups. The objectives of this study are to study the influence of presence on social media, activity on social media, and content posted on social media on funding achieved by start-ups. This study is based on a unique dataset compiled from Crunchbase-Pro and Twitter. Machine Learning model has been used for text classification of 130K+ tweets. Causal mediation analysis with bootstrapping is carried out for hypothesis testing. The results consistently highlight that social media strategy should be an integral part of the overall strategy of the start-ups looking out for funds. Active usage of Twitter and feedback from other Twitter users has a positive impact on funds raised by the start-up. Tweets addressing quality-related uncertainty are a predictor of the amount of funds raised while Audience response acts as a mediator between tweets focussing on relational orientation and the amount of funds raised. The study also demonstrates the successful use of text classification through Logistic Regression and tree-based algorithms namely, Random Forest and CatBoost classifier. The best results for labelling short texts such as tweets were achieved through logistic regression. newline