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Neslihan Iskender
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Research Group
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
- ERICS – European Refugee Information and Communication Service (EIT-Digital, Project Lead)
- OurPuppet: Pflegeunterstützung mit einer interaktiven Puppe für informell Pflegende (BMBF)
- ICU - Internes Crowdsourcing in Unternehmen: Arbeitnehmergerechte Prozessinnovationen durch digitale Beteiligung von Mitarbeiter/innen (BMBF)
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
| Citation key | iskender2020b |
|---|---|
| Author | Iskender, Neslihan and Polzehl, Tim and Möller, Sebastian |
| Title of Book | Proceedings of The 12th Language Resources and Evaluation Conference |
| Pages | 245–253 |
| Year | 2020 |
| Location | Marseille, France |
| Address | Paris, France |
| Month | may |
| Note | online |
| Publisher | European Language Resources Association (ELRA) |
| Series | LREC |
| How Published | Fullpaper |
| Abstract | The intrinsic and extrinsic quality evaluation is an essential part of the summary evaluation methodology usually conducted in a traditional controlled laboratory environment. However, processing large text corpora using these methods reveals expensive from both the organizational and the financial perspective. For the first time, and as a fast, scalable, and cost-effective alternative, we propose micro-task crowdsourcing to evaluate both the intrinsic and extrinsic quality of query-based extractive text summaries. To investigate the appropriateness of crowdsourcing for this task, we conduct intensive comparative crowdsourcing and laboratory experiments, evaluating nine extrinsic and intrinsic quality measures on 5-point MOS scales. Correlating results of crowd and laboratory ratings reveals high applicability of crowdsourcing for the factors overall quality, grammaticality, non-redundancy, referential clarity, focus, structure & coherence, summary usefulness, and summary informativeness. Further, we investigate the effect of the number of repetitions of assessments on the robustness of mean opinion score of crowd ratings, measured against the increase of correlation coefficients between crowd and laboratory. Our results suggest that the optimal number of repetitions in crowdsourcing setups, in which any additional repetitions do no longer cause an adequate increase of overall correlation coefficients, lies between seven and nine for intrinsic and extrinsic quality factors. |
Zusatzinformationen / Extras
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