Scrutinizing Consumer Sentiment on Social Media and Data-Driven Decisions for Business Insights

Author:

Singh Bhupinder1ORCID,Kaunert Christian2ORCID,Malviya Rishabha3,Lal Sahil1ORCID,Arora Manmeet Kaur1ORCID

Affiliation:

1. Sharda University, India

2. Dublin City University, Ireland

3. Galgotias University, India

Abstract

AI tools have the capability to analyze emotions conveyed in substantial text inputs such as customer reviews or feedback. These algorithms categorize sentiment as positive, neutral or negative which offering valuable insights into customers' sentiments. The manual analysis of extensive text data is both impractical and time-consuming. Business Intelligence, a fundamental aspect of data analytics, encompasses the gathering, analysis and presentation of business information to facilitate strategic decision-making. Traditionally, Business Intelligence tools have played a crucial role in organizing and visualizing historical data, offering insights into past performances. Artificial Intelligence driven by advanced algorithms and machine learning, surpasses the constraints of traditional Business Intelligence by unlocking the ability to predict future trends, behaviors and outcomes. This chapter comprehensively explores the diverse arena of AI and BI for fostering sustainable business growth via analyzing the consumer sentiments on social websites.

Publisher

IGI Global

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