TU Berlin

Quality and Usability LabNeslihan Iskender

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Neslihan Iskender

Lupe

Research Group

Crowdsourcing and Open Data

 

Teaching

  • Study Project Quality & Usability (Since SS 2018)
  • Interdiziplinäres Medienprojekt (Since SS 2018)
  • Usability Engineering (Exercise SS 2018)

 

Biography

Neslihan Iskender received her Bachelor and Master of Science degree in Industrial Engineering and Management at the Karlsruhe Institute of Technology. During her studies, she focused on managing new technologies and innovation management. Since May 2017, she is employed as a research assistant at the Quality and Usability Labs where she is working towards a PhD in the field of crowdsourcing. Her research Topics are:

  • Crowd assessments: Usability, UX, QoE, Quality
  • Real-time interaction, human computation as a service, (HuaaS)
  • Hybrid Worfklows for micro-task crowdsourcing
  • Internal Crowdsourcing

 

Current Projects

 

Past Projects

 

Contact

E-Mail: neslihan.iskender@tu-berlin.de

Phone: +49 (30) 8353-58347 

Fax: +49 (30) 8353-58409 

 

Address

Quality and Usability Lab

Deutsche Telekom Laboratories

Technische Universität Berlin

Ernst-Reuter-Platz 7

D-10587 Berlin, Germany 

 

 

Publications

An Empirical Analysis of an Internal Crowdsourcing Platform: IT Implications for Improving Employee Participation
Zitatschlüssel iskender2021a
Autor Iskender, Neslihan and Polzehl, Tim
Buchtitel Internal Crowdsourcing in Companies: Theoretical Foundations and Practical Applications
Seiten 103–134
Jahr 2021
ISBN 978-3-030-52881-2
DOI 10.1007/978-3-030-52881-2_6
Adresse Cham
Monat feb
Notiz online
Herausgeber Ulbrich, Hannah and Wedel, Marco and Dienel, Hans-Liudger
Verlag Springer International Publishing
Wie herausgegeben Fullpaper
Zusammenfassung Crowdsourcing has become one of the main resources for working on so-called microtasks that require human intelligence to solve tasks that computers cannot yet solve and to connect to external knowledge and expertise. Instead of using external crowds, several organizations have increasingly been using their employees as a crowd, with the aim of exploiting employee's potentials, mobilizing unused technical and personal experience and including personal skills for innovation or product enhancement. However, understanding the dynamics of this new way of digital co-working from the technical point of view plays a vital role in the success of internal crowdsourcing, and, to our knowledge, no study has yet empirically investigated the relationship between the technical features and participation in internal crowdsourcing. Therefore, this chapter aims to provide a guideline for organizations and employers from the perspective of the technical design of internal crowdsourcing, specifically regarding issues of data protection privacy and security concerns as well as task type, design, duration and participation time based on the empirical findings of an internal crowdsourcing platform.
Link zur Publikation Link zur Originalpublikation Download Bibtex Eintrag

Publications

B

Barz, Michael and Büyükdemircioglu, Neslihan and Prasad Surya, Rikhu and Polzehl, Tim and Sonntag, Daniel (2018). Device-Type Influence in Crowd-based Natural Language Translation Tasks. Proceedings of the 1st Workshop on Subjectivity, Ambiguity and Disagreement (SAD) in Crowdsourcing 2018, and the 1st Workshop CrowdBias'18: Disentangling the Relation Between Crowdsourcing and Bias Management, 93–97.

Link zur Publikation Link zur Originalpublikation

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