Targeted advertising is a key characteristic of online as well as traditional-media marketing. However it is very limited in outdoor advertising, that is, performing campaigns by means of billboards in public places. The reason is the lack of information about the interests of the particular passersby, except at very imprecise and aggregate demographic or traffic estimates. In this work we propose a methodology for performing targeted outdoor advertising by leveraging the use of social media. In particular, we use the Twitter social network to gather information about users’ degree of interest in given advertising categories and about the common routes that they follow, characterizing in this way each zone in a given city. Then we use our characterization for recommending physical locations for advertising. Given an advertisement category, we estimate the most promising areas to be selected for the placement of an ad that can maximize its targeted effectiveness. We show that our approach is able to select advertising locations better with respect to a baseline reflecting a current ad-placement policy. To the best of our knowledge this is the first work on offline advertising in urban areas making use of (publicly available) data from social networks.

Targeted interest-driven advertising in cities using Twitter / Anagnostopoulos, Aris; Petroni, Fabio; Sorella, Mara. - In: DATA MINING AND KNOWLEDGE DISCOVERY. - ISSN 1384-5810. - 32:3(2018), pp. 737-763. [10.1007/s10618-017-0529-7]

Targeted interest-driven advertising in cities using Twitter

Anagnostopoulos, Aris;Petroni, Fabio;Sorella, Mara
2018

Abstract

Targeted advertising is a key characteristic of online as well as traditional-media marketing. However it is very limited in outdoor advertising, that is, performing campaigns by means of billboards in public places. The reason is the lack of information about the interests of the particular passersby, except at very imprecise and aggregate demographic or traffic estimates. In this work we propose a methodology for performing targeted outdoor advertising by leveraging the use of social media. In particular, we use the Twitter social network to gather information about users’ degree of interest in given advertising categories and about the common routes that they follow, characterizing in this way each zone in a given city. Then we use our characterization for recommending physical locations for advertising. Given an advertisement category, we estimate the most promising areas to be selected for the placement of an ad that can maximize its targeted effectiveness. We show that our approach is able to select advertising locations better with respect to a baseline reflecting a current ad-placement policy. To the best of our knowledge this is the first work on offline advertising in urban areas making use of (publicly available) data from social networks.
2018
Geotag; Targeted outdoor advertising; Twitter; Information Systems; Computer Science Applications1707 Computer Vision and Pattern Recognition; Computer Networks and Communications
01 Pubblicazione su rivista::01a Articolo in rivista
Targeted interest-driven advertising in cities using Twitter / Anagnostopoulos, Aris; Petroni, Fabio; Sorella, Mara. - In: DATA MINING AND KNOWLEDGE DISCOVERY. - ISSN 1384-5810. - 32:3(2018), pp. 737-763. [10.1007/s10618-017-0529-7]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1185741
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