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Gabriella M. Harari
ResearcherPublications, citations & collaboration network
Gabriella M. Harari is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 105 works, 4,745 citations, an h-index of 31 and an i10-index of 48.
105
Works
4,745
Citations
31
h-index
48
i10-index
How has Gabriella M. Harari's publication output changed over time?
ScholarIQpublication output · 2014–2024
Output grew0% over the shown period — from 1 works in 2014 to 1 in 2024.
1
1
2
1
1
1
2
1
20142015201620172018201920202024
What are the most-cited papers on Gabriella M. Harari?
ScholarIQmost cited works
StudentLife
Rui Wang, Fanglin Chen, Zhenyu Chen, Tianxing Li, Gabriella M. Harari, Stefanie M. Tignor, Xia Zhou, Dror Ben‐Zeev, Andrew T. Campbell
20141,132 Citations
Using Smartphones to Collect Behavioral Data in Psychological Science
Gabriella M. Harari, Nicholas D. Lane, Rui Wang, Benjamin S. Crosier, Andrew T. Campbell, Samuel D. Gosling
S27228949. 2016537 Citations
Predicting personality from patterns of behavior collected with smartphones
Clemens Stachl, Quay Au, Ramona Schoedel, Samuel D. Gosling, Gabriella M. Harari, Daniel Buschek, Sarah Theres Völkel, Tobias Schuwerk, Michelle Oldemeier, Theresa Ullmann, Heinrich Hußmann, Bernd Bischl, Markus Bühner
Proceedings of the National Academy of Sciences. 2020320 CitationsOPEN ACCESS
Smartphone sensing methods for studying behavior in everyday life
Gabriella M. Harari, Sandrine R. Müller, Min Hane Aung, Peter J. Rentfrow
S2764598273. 2017265 CitationsOPEN ACCESS
The potential of generative AI for personalized persuasion at scale
Sandra Matz, Jacob D. Teeny, Sumer S. Vaid, H. Peters, Gabriella M. Harari, Moran Cerf
Scientific Reports. 2024237 CitationsOPEN ACCESS
Related on ScholarIQ
Stanford University
Institution
StudentLife
Paper
Using Smartphones to Collect Behavioral Data in Psychological Science
Paper
Predicting personality from patterns of behavior collected with smartphones
Paper
Smartphone sensing methods for studying behavior in everyday life
Paper
The potential of generative AI for personalized persuasion at scale
Paper