Original scientific paper

https://doi.org/10.17559/TV-20151020205558

Advertising recommendation system based on dynamic data analysis on Turkish speaking Twitter users

Onur Sevli ; Mehmet Akif Ersoy University, 15030 Burdur, Turkey
Ecir Uğur Küçüksille orcid.org/0000-0002-3293-9878 ; Süleyman Demirel University, 32260 Isparta, Turkey

Abstract

Online environments and especially social networks have become a great alternative to advertisement publishing. In order to accomplish effective advertising it is important that the contents coincide with the expectations of the target audience. Considering that expectations may change over time, it is required to identify the orientation of the users in real time and dynamically. In this study, the messages shared by Turkish Twitter users were analysed in real time and the instant expectations of the users have been identified. To perform this work, a web service was designed which analyses the user’s profile and presents the advertisements that suit best to expectations. A method called Heuristic Pruning Method (HPM) has been revealed in order to filter the most appropriate advertising content. The developed system has been tested on a voluntary participant group who actively uses Twitter, and the effectiveness of the system is demonstrated by the received feedback.

Keywords

advertising recommendation; content filtering; map reduce; social network marketing

Hrčak ID:

179876

URI

https://hrcak.srce.hr/179876

Publication date:

14.4.2017.

Article data in other languages: croatian

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