Tasya Nadila
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Prediksi Tren Konsumen melalui Social Media Listening Pendekatan Machine Learning dalam Strategi Pemasaran Modern Zuhrinal M. Nawawi; Tasya Nadila
Ekonomi Keuangan Syariah dan Akuntansi Pajak Vol. 2 No. 3 (2025): Ekonomi Keuangan Syariah dan Akuntansi Pajak (EKSAP)
Publisher : Asosiasi Riset Ekonomi dan Akuntansi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/eksap.v2i3.969

Abstract

This study uses a qualitative method to explore how social media listening, combined with a machine learning approach, can be utilized to predict consumer trends in modern marketing strategies. In today’s digital era, social media serves as a rich data source for capturing consumer preferences, needs, and behaviors in real time. With machine learning algorithms such as natural language processing (NLP) and sentiment analysis, data from platforms like Twitter, Instagram, and TikTok can be processed to identify patterns that indicate market trends. This approach not only enables companies to respond quickly to consumer dynamics but also allows them to craft more targeted and data-driven marketing strategies. This study examines five major brands that implement social media listening as part of their digital strategy by observing consumer conversations, dominant emotions, and viral issues. The findings show that the integration of social media listening and machine learning can serve as an effective predictive tool in developing adaptive and contextual marketing campaigns.