Integration von Mouse- und Eyetracking-Daten in das Analyse-Toolkit WHOSE

Status


Finished bachelor thesis

Formalia


External thesis in cooperation with GESIS Köln
Targeted audience
  • AI Bachelor
Preconditions
  • Experience in programming (Java, JavaScript, PHP, MySQL, Maven, GIT)
  • Experience in graphical design, digital libraries, user-sessions is recommended.

Task description


Goal: The Analysis-Toolkit WHOSE [1] can load, process and present Usage Data from log files of web-based information systems and digital libraries in an user interface. System operator and scientists will be able to examine how searchers use the system, where the weaknesses are and how the information search of the system can be improved. The aim of this project is to extend the tool in a way that additionally mouse- and eyetracking data from user experiments can be used for the analysis. Therefore, the cadidate should first implement a mouse tracking solution in JavaScript. This solution should measure the resting time of the mouse pointer on different areas of the website. This data should be combined with eyetracker data. The combined data should than be presented in the WHOSE-Visualization so that it can be used for the analysis.

Tasks:

  • Development of a mouse tracking solution (JavaScript)
  • Integration of data from mouse tracking and eyetracking
  • Development of an interactive visual presentation of the new data at the WHOSE-Tool

Language of this work: German or english

This thesis can also be processed as bachelor thesis. The volume will be adjusted to the conditions.

Contact: Dr. Daniel Hienert
GESIS – Leibniz-Institut für Sozialwissenschaften
Abteilung Wissenstechnologien für Sozialwissenschaften (WTS)
Unter Sachsenhausen 6-8, 50667 Köln
Tel: + 49 (0) 221 / 47694-525
Mail: daniel.hienert@gesis.org
www.gesis.org/wts
More information: http://www.gesis.org/forschung/angewandte-informatik-und-informationswissenschaft/information-retrieval/abschlussarbeiten


[1] Hienert, Daniel, Wilko van Hoek, Alina Weber, and Dagmar Kern. 2015. "WHOSE - A Tool for Whole-Session Analysis in IIR." In Advances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29 - April 2, 2015. Proceedings, Lecture Notes in Computer Science 9022, 172-183. http://www.dx.doi.org/10.1007/978-3-319-16354-3_18.