A Semantic Approach for User-Brand Targeting in On-Line Social Networks
Abstract
We propose a general framework for the recommendation of possible customers (users) to advertisers (e.g., brands) based on the comparison between On-line Social Network profiles. In particular, we represent both user and brand profiles as trees where nodes correspond to categories and sub-categories in the associated On-line Social Network. When categories involve posts and comments, the comparison is based on word embedding, and this allows to take into account the similarity between topics popular in the brand profile and user preferences. Results on real datasets show that our approach is successfull in identifying the most suitable set of users to be used as target for a given advertisement campaign.
Keywords
Cite
@article{arxiv.1907.01326,
title = {A Semantic Approach for User-Brand Targeting in On-Line Social Networks},
author = {Mariella Bonomo and Gaspare Ciaccio and Andrea De Salve and Simona E. Rombo},
journal= {arXiv preprint arXiv:1907.01326},
year = {2019}
}
Comments
10 pages, 3 figures, extended work from a conference paper