Harnessing Machine Learning toOptimize Social Media Marketing

Title

Harnessing Machine Learning toOptimize Social Media Marketing

Creator

Dkhar, Josaiah Murfeal; John, Tegil; Rai, Pranab

Description

Machine learning (ML) has transformed the way digital advertising is done and analyzed by social media data. This paper explores ML in targeted advertising, including techniques such as supervised learning, neural networks, and NLP. While ML improves campaign precision and consumer engagement, it also presents challenges such as algorithmic bias, data privacy concerns, and computational scalability. This study is a synthesis of existing research and explores real-world applications, providing a critical analysis of MLs capacity to optimize social media advertising. It argues that while ML may provide exceptional possibilities for customization and engagement, its success can only be ensured through appropriate ethical practices, transparency, and innovation in technology. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.

Source

Lecture Notes in Networks and Systems;Volume;1497 LNNS;pp.581-598

Date

01-01-2026

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Digital advertisement; Machine learning; NLP; Social media marketing

Coverage

Dkhar J.M., Christ University, Bengaluru, India; John T., Christ University, Bengaluru, India; Rai P., Christ University, Bengaluru, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 23673370; ISBN: 978-981969183-8;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-96-9184-5_43

https://www.scopus.com/pages/publications/105028353338?origin=resultslist