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.

Rombo, S., La Placa, A., Bonomo, M. (2020). Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks. In J.F. Ana L. N. Fred (a cura di), Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR (pp. 193-201) [10.5220/0010109201930201].

Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks

Rombo, Simona
;
Bonomo, Mariella
2020-11-01

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.
nov-2020
Rombo, S., La Placa, A., Bonomo, M. (2020). Identifying the k Best Targets for an Advertisement Campaign via Online Social Networks. In J.F. Ana L. N. Fred (a cura di), Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR (pp. 193-201) [10.5220/0010109201930201].
File in questo prodotto:
File Dimensione Formato  
KDIR_2020_17_CR.pdf

Solo gestori archvio

Descrizione: articolo principale
Tipologia: Pre-print
Dimensione 600.32 kB
Formato Adobe PDF
600.32 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/528788
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 2
social impact