Abstract:

Digital marketing has become a practical part of modern business strategies, allowing companies to reach wider audiences and engage with customers innovatively. Understanding customer sentiment towards products, services, and experiences is essential for effective marketing campaigns. In this line, Sentiment Analysis (sa), a task of Natural Language Processing, offers valuable insights by automatically analyzing and categorizing opinions expressed in textual data.
Consequently, this paper studies different aspect-based approaches to sa in digital marketing but focuses primarily on the Middle East, where Arabic is the primary spoken language. Note that Arabic Chat Alphabet (aca) is the informal language used in online chats, social media platforms, and instant messaging applications. More in detail, this work presents some of the Aspect-Based Sentiment Analysis (absa) work done using Arabic data sets, highlighting a substantial gap in the
in the absa literature concerning aca across different dialects—particularly the Egyptian dialect, also referred to as Egyptzi.