IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Sentiment Mining: A Data-Driven Approach for Optimizing Digital Marketing Strategies

Sentiment Mining: A Data-Driven Approach for Optimizing Digital Marketing Strategies
View Sample PDF
Author(s): Anjali Daisy (St. Joseph's Institute of Management, Trichy, India)
Copyright: 2024
Pages: 18
Source title: The Use of Artificial Intelligence in Digital Marketing: Competitive Strategies and Tactics
Source Author(s)/Editor(s): Sandrina Teixeira (Centre for Organizational and Social Studies (CEOS), Porto Accounting and Business School, Polytechnic of Porto, Portugal)and Jorge Remondes (Centre for Organizational and Social Studies (CEOS), Porto Accounting and Business School, Polytechnic of Porto, Portugal)
DOI: 10.4018/978-1-6684-9324-3.ch009

Purchase

View Sentiment Mining: A Data-Driven Approach for Optimizing Digital Marketing Strategies on the publisher's website for pricing and purchasing information.

Abstract

With millions of users active on social media, businesses have the opportunity to reach a vast audience and gain valuable insights into customer preferences and behavior. However, with the increase in social media usage, the challenge for businesses is to effectively analyze and interpret the vast amount of data generated by social media and other digital channels. This is where sentiment mining comes into play. Sentiment mining involves using machine learning algorithms to analyze and classify online content, such as social media posts and reviews, to determine the overall sentiment or tone of the content. The purpose of this chapter is to explore the concept of sentiment mining and its application in optimizing digital marketing strategies. The concept of sentiment mining has gained significant attention in recent years, with businesses recognizing its potential to gain insights into customer sentiment and preferences. This chapter aims to bridge this gap in literature and explore the potential of sentiment mining in optimizing digital marketing strategies.

Related Content

Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava. © 2024. 20 pages.
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima. © 2024. 52 pages.
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira. © 2024. 24 pages.
Fatih Pinarbasi. © 2024. 20 pages.
Stavros Kaperonis. © 2024. 25 pages.
Thomas Rui Mendes, Ana Cristina Antunes. © 2024. 24 pages.
Nuno Geada. © 2024. 12 pages.
Body Bottom