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Authors: Mariella Bonomo ; Armando La Placa and Simona E. Rombo

Affiliation: Department of Mathematics and Computer Science, University of Palermo, Palermo, Italy

Keyword(s): Online Social Networks, Social Advertising, tf-idf, Profile Matching.

Abstract: We propose a novel approach for the recommendation of possible customers (users) to advertisers (e.g., brands) based on two main aspects: (i) the comparison between On-line Social Network profiles, and (ii) neighborhood analysis on the On-line Social Network. Profile matching between users and brands is considered based on bag-of-words representation of textual contents coming from the social media, and measures such as the Term Frequency-Inverse Document Frequency are used in order to characterize the importance of words in the comparison. The approach has been implemented relying on Big Data Technologies, allowing this way the efficient analysis of very large Online Social Networks. Results on real datasets show that the combination of profile matching and neighborhood analysis is successful in identifying the most suitable set of users to be used as target for a given advertisement campaign.

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Paper citation in several formats:
Bonomo, M.; La Placa, A. and Rombo, S. (2020). Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KDIR; ISBN 978-989-758-474-9; ISSN 2184-3228, SciTePress, pages 193-201. DOI: 10.5220/0010109201930201

@conference{kdir20,
author={Mariella Bonomo. and Armando {La Placa}. and Simona E. Rombo.},
title={Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks},
booktitle={Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KDIR},
year={2020},
pages={193-201},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010109201930201},
isbn={978-989-758-474-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - KDIR
TI - Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks
SN - 978-989-758-474-9
IS - 2184-3228
AU - Bonomo, M.
AU - La Placa, A.
AU - Rombo, S.
PY - 2020
SP - 193
EP - 201
DO - 10.5220/0010109201930201
PB - SciTePress

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