20142020

Research activity per year

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Personal profile

Research interests

Claire Segijn is an Assistant Professor of Advertising at the Hubbard School of Journalism and Mass Communication, University of Minnesota – Twin Cities. Her research interests include synced advertising, multiscreening, media multitasking, attention, and advertising effectiveness. Her work has been published in top tier journals in the field of communication and advertising (e.g., Human Communication Research, Journal of Advertising, International Journal of Advertising). Furthermore, her work has been honored with several awards of the American Academy of Advertising (AAA) and the International Communication Association. In 2017 and 2018, I received the Baschwitz article of the year award for young researchers.

Between 2014 and 2017, She wrote a dissertation at the University of Amsterdam entitled “Everyday Multiscreening. How the simultaneous usage of multiple screens affects information processing and advertising effectiveness,” which was awarded with the Annie Lang Dissertation Award in May 2018 and the Biennial Best Dissertation Award of the Mobile Communication Interest Group in May 2019. Furthermore, she received several competitive grants from different academic organizations (e.g., AAA, ICA) to support her research and mentoring of undergraduate student research. As of March 2019, she serves as the chair of the AAA Global and Multicultural committee. Finally, she has taught several courses both to undergraduate and graduate students, ranging from individual supervision to teaching in front of large groups of students.

Expertise related to UN SDGs

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 12 - Responsible Consumption and Production

Research Interest Keywords

  • Multiscreening
  • Synced Advertising
  • Attention
  • Eye-tracking
  • Media multitasking
  • experimental methods

Fingerprint

The Fingerprint is created by mining the titles and abstracts of the person's research outputs and projects/funding awards to create an index of weighted terms from discipline-specific thesauri.
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