Bibliographic Details
| Title: |
ADVERTISING RECOMMENDATION SYSTEM BASED ON DYNAMIC DATA ANALYSIS ON TURKISH SPEAKING TWITTER USERS. |
| Alternate Title: |
Preporučeni sustav oglašavanja zasnovan na dinamičkoj analizi podataka turskih korisnika Twittera. |
| Authors: |
Sevli, Onur1 onursevli@mehmetakif.edu.tr, Küçüksille, Ecir Uğur2 ecirkucuksille@sdu.edu.tr |
| Source: |
Technical Gazette / Tehnički Vjesnik. Mar/Apr2017, Vol. 24 Issue 2, p571-578. 8p. |
| Subjects: |
Twitter (Web resource), Feedback control systems, Social networks, Real-time control, Data analysis |
| Abstract (English): |
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. [ABSTRACT FROM AUTHOR] |
| Abstract (Croatian): |
Online okruženja, a posebno društvene mreže postala su snažna alternative objavljivanju oglasa. Za učinkovito oglašavanje važno je da se sadržaj poistovjećuje s očekivanjima ciljane publike. Uzimajući u obzir da se očekivanja mogu s vremenom promijeniti, potrebno je u realnom vremenu i dinamički prepoznati orijentaciju korisnika. U ovom su se radu u realnom vremenu analizirale poruke turskih korisnika Twittera i identificirala njihova trenutna očekivanja. U tu je svrhu dizajnirana web usluga koja analizira profil korisnika i daje oglase koji najbolje odgovaraju očekivanjima. Za filtriranje odgovarajućeg sadržaja oglašavanja korištena je metoda nazvana heuristička metoda odstranjivanja suvišnog (Heuristic Pruning Method - HPM). Razvijeni sustav je testiran na grupi volontera, aktivnih korisnika Twittera, a učinkovitost sustava se pokazala dobivenom povratnom informacijom-feedbackom. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
