Visualisering av användarmönster och klusteranalys i en peer-to-peer mobil marknadsplats
InformationFörfattare: Sara Collin, Ingrid Möllerberg
Beräknat färdigt: 2020-06
Handledare: Elliot Rask
Handledares företag/institution: Swace
Ämnesgranskare: Mikael Laaksoharju
PresentationerPresentation av Sara Collin
Presentationstid: 2020-06-02 13:15
Presentation av Ingrid Möllerberg
Presentationstid: 2020-06-02 14:15
Opponenter: Linus Rustas, Herman Guss
The purpose of this study was to develop an interactive tool that enables identification of different types of users of an application based on clickstream data. A complex hierarchical clustering algorithm tool called Recursive Hierarchical Clustering (RHC) was used. RHC additionally provides a visualization of user types as clusters, where each cluster has its own distinguishing action pattern, i.e., one or several consecutive actions made by the user in the application. A case study was conducted on the mobile application Plick, which is an application for selling and buying second hand clothes.
During the course of the project, the analysis and its result was discovered to be difficult to understand by the operators of the tool. The interactive tool had to be extended to visualize the complex analysis and its result in an intuitive way. A literature study of how humans interpret information, and how to present it to operators, was conducted and led to a redesign of the tool. More information was added to each cluster to enable further understanding of the clustering results. A clustering reconfiguration option was also created where operators of the tool got the possibility to interact with the analysis. In the reconfiguration, the operator could change the input file of the cluster analysis and thus the end result. Usability tests showed that the extra added information about the clusters served as an amplification and a verification of the original results presented by RHC. In some cases the original result presented by RHC was used as a verification to user group identification made by the operator solely based on the extra added information. The usability tests proved that the complex analysis with its results could be understood and configured without considerable comprehension of the algorithm. Instead it seemed like it could be successfully used in order to identify user types with help of visual clues in the interface and default settings in the reconfiguration. The visualization tool is shown to be successful in identifying and visualizing user groups in an intuitive way.