dc.contributor.author | De Maio, C | |
dc.contributor.author | Gallo, M | |
dc.contributor.author | Hao, F | |
dc.contributor.author | Loia, V | |
dc.contributor.author | Yang, E | |
dc.date.accessioned | 2021-02-04T11:06:38Z | |
dc.date.issued | 2020-10-14 | |
dc.description.abstract | One of the most important sources of revenue for social media platforms, like, Twitter, Facebook, Reddit, etc., is advertising. An effective social media advertising plan moves people from awareness and interest in desire and action. Despite the potentiality, campaigns and marketing strategies should be improved. One of the challenges is to identify the right target audience at the right time, considering both communities of interests and locations and the development of these conditions along the timeline. This is crucial to create the right communication strategy and the right advertising message. This paper proposes a context-aware ad-targeting methodology using time, locations, and inferring users' interests by analyzing published content. The method relies on a fuzzy extension of Triadic Formal Concept Analysis for identifying Location-based and Content-based communities of users. Then, a task of community fusion takes place, named Join, for matching a target audience. The matching may be tuned for identifying a wide or narrow community and implementing a fine-grained ad targeting. Experimental results are given. | en_GB |
dc.description.sponsorship | European Union Horizon 2020 | en_GB |
dc.identifier.citation | 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 11 - 14 October 2020, Toronto, Canada, pp. 3059 - 3065 | en_GB |
dc.identifier.doi | 10.1109/SMC42975.2020.9282827 | |
dc.identifier.grantnumber | 840922 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/124607 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.rights | © 2020 IEEE | en_GB |
dc.subject | Formal concept analysis | en_GB |
dc.subject | Uncertainty | en_GB |
dc.subject | Social networking (online) | en_GB |
dc.subject | Blogs | en_GB |
dc.subject | Advertising | en_GB |
dc.subject | Task analysis | en_GB |
dc.subject | Cybernetics | en_GB |
dc.title | Fine-Grained Context-aware Ad Targeting on Social Media Platforms | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2021-02-04T11:06:38Z | |
dc.identifier.isbn | 9781728185262 | |
dc.description | This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record | en_GB |
dc.identifier.eissn | 2577-1655 | |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
dcterms.dateAccepted | 2020-08-18 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2020-10-14 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2021-02-04T10:57:28Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2021-02-04T11:06:51Z | |
refterms.panel | B | en_GB |