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Creating an Intelligent Social Media Campaign Decision-Support Method

Published: 22 June 2024 Publication History

Abstract

Predicting the success of marketing campaigns on social media can help improve campaign managers’ decision-making (e.g., deciding to stop a marketing campaign) and thus increase their profits. Most research in the field of online marketing has focused on analyzing users’ behavior rather than improving campaign manager decision-making. Furthermore, determining the success of marketing campaigns is quite challenging due to the large number of possible metrics that must be analyzed daily. In this study, we suggest a method that incorporates machine learning models with traditional business rules to provide daily decision recommendations, based on the various metrics and considerations, and aimed at achieving the campaign’s goals. We evaluate our approach on a unique dataset collected from the most popular social networks, Facebook and Instagram. Our evaluation demonstrates the proposed method’s ability to outperform an expert-based method and the machine learning baselines examined, and dramatically increase the campaign managers’ profits.

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cover image ACM Conferences
UMAP '24: Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization
June 2024
338 pages
ISBN:9798400704338
DOI:10.1145/3627043
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Published: 22 June 2024

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Author Tags

  1. campaign management
  2. datasets
  3. decision support
  4. machine learning
  5. social networks

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