SUBMISSIONS

SUBMISSION DETAIL

Emre Suleyman ÖZMEN
 


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EVENT DENSITY VISUALIZATION WITH PYTHON FOLIUM LIBRARY FOR PUBLIC COMPLAINT MANAGEMENT: AN APPLICATION WITH 311 CALLS
 
When products or services face with its audience, risk occurs. The risk is that audience either does not like it, thinks it does not meet expectations and/or falsely advertised. When the audience is getting bigger this even turns to more probable and needs more attention. They are not always right and more importantly it does not really matter. The truth is that there is likely no chances that an organization leave the situation alone. In the end, most majority of these happenings rarely has self-resolving nature. However, knowing that there is a need for answers is usually not enough to have a generic solution. Attempts to manage this with no methodology may jeopardize organization’s reputation. In other words, when it comes to complaint management, ad-hoc attributes do not make a good fit. Therefore, establishing a complaint management process is vital. Machines cannot complaint, complaints are rooted with human behavior and they usually burst emotions. A good complaint management system will not only help to manage the emotional side of the complaints, but it also helps to improve quality. Quality may relate to products, features and services, where it also may consist of environmental aspects, safety or simply others, especially if it is public administration domain. This paper, using Python, scrutinizes the importance of real-time data with complaint management systems.

Anahtar Kelimeler: Auto detect, Complaint management systems, Density management, Real-time data