Analysis of Emotional Content in Indian Political Speeches

TL;DR

This paper analyzes the emotional content of Indian political speeches using an Attention CNN+LSTM model, revealing how politicians incorporate emotions to influence voters and examining the relationship between emotional speech content and electoral success.

Contribution

It introduces an attention-based deep learning approach to quantify emotional content in political speeches and explores its impact on election outcomes.

Findings

Politicians use emotional content strategically in speeches.

Emotional speech content correlates with voting share and victory margin.

Deep learning effectively captures emotional nuances in political discourse.

Abstract

Emotions play an essential role in public speaking. The emotional content of speech has the power to influence minds. As such, we present an analysis of the emotional content of politicians speech in the Indian political scenario. We investigate the emotional content present in the speeches of politicians using an Attention based CNN+LSTM network. Experimental evaluations on a dataset of eight Indian politicians shows how politicians incorporate emotions in their speeches to strike a chord with the masses. An analysis of the voting share received along with victory margin and their relation to emotional content in speech of the politicians is also presented.