Article
CONSUMER ATTITUDE TOWARDS ONLINE ADVERTISING
The digital advertising ecosystem has undergone a radical transformation with the advent of advanced computational technologies. Consumer attitudes, once relatively passive in response to traditional advertising, have evolved dramatically in today’s hyper connected environment. This research delves deep into the complexities of consumer attitudes toward online advertising in an era increasingly shaped by artificial intelligence, machine learning (ML), and deep learning (DL). Consumers interact with a multitude of ads across platforms like Google, Facebook, Instagram, YouTube, and e-commerce websites, often without consciously engaging. As online advertising grows more data-driven and algorithmically optimized, this study seeks to understand the factors shaping consumer responses—ranging from perceived utility, relevance, trust, to privacy concerns and emotional reactions. Incorporating AI techniques, the study uses natural language processing (NLP), user clustering, predictive modeling, and neural network sentiment analysis to dissect consumer sentiments and behavioral tendencies. It highlights how ML and DL enable the personalization of ad experiences and how these same technologies can be employed to measure, predict, and ethically guide consumer engagement. By evaluating largescale datasets and consumer interviews, the study not only reveals patterns of ad acceptance and avoidance but also proposes a roadmap for responsible AI integration in digital marketing. This multidisciplinary research provides critical insights for businesses, marketers, technologists, and policymakers striving to balance innovation, consumer satisfaction, and digital ethics in advertising
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