C-LINK Agent. Connecting social media post generation with recommender systems<sup>*</sup>

Social Media Posts are one of the main communication paths that businesses of every size utilize in order to inform their audience. Recommender systems often struggle to get real time updates from social media posts, due either to platform terms of uses, or users that are not aware of. This case study presents a theoretical workflow of building an AI "team of experts" type agent that acts as an intermediate between users and recommender systems. It is the first part of a study on process trying to utilize Generative Artificial Intelligence in order to automatically create social media posts for users and at the same time convert, organize and store each post on an open database able for any recommender system to access in real time. The framework is also proposed to serve as a common experimental platform for AI agent design researchers, enabling comparative studies on various aspects

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/smap63474.2024.00030
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
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article

C-LINK Agent. Connecting social media post generation with recommender systems*

Georgios Trichopoulos, George Caridakis, Konstantinos Ordoumpozanis
Recommender Systems and Techniques
article

C-LINK Agent. Connecting social media post generation with recommender systems*

Georgios Trichopoulos, George Caridakis, Konstantinos Ordoumpozanis
article en

Abstract

Social Media Posts are one of the main communication paths that businesses of every size utilize in order to inform their audience. Recommender systems often struggle to get real time updates from social media posts, due either to platform terms of uses, or users that are not aware of. This case study presents a theoretical workflow of building an AI "team of experts" type agent that acts as an intermediate between users and recommender systems. It is the first part of a study on process trying to utilize Generative Artificial Intelligence in order to automatically create social media posts for users and at the same time convert, organize and store each post on an open database able for any recommender system to access in real time. The framework is also proposed to serve as a common experimental platform for AI agent design researchers, enabling comparative studies on various aspects

University of the Aegean (GR)
Reduced inequalities
Openalex Percentile: Top 57%
Recommender Systems and Techniques
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