Sumer S. Vaid

597 total citations · 1 hit paper
12 papers, 276 citations indexed

About

Sumer S. Vaid is a scholar working on Sociology and Political Science, Applied Psychology and Clinical Psychology. According to data from OpenAlex, Sumer S. Vaid has authored 12 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Sociology and Political Science, 6 papers in Applied Psychology and 5 papers in Clinical Psychology. Recurrent topics in Sumer S. Vaid's work include Impact of Technology on Adolescents (6 papers), Personality Traits and Psychology (5 papers) and Behavioral Health and Interventions (3 papers). Sumer S. Vaid is often cited by papers focused on Impact of Technology on Adolescents (6 papers), Personality Traits and Psychology (5 papers) and Behavioral Health and Interventions (3 papers). Sumer S. Vaid collaborates with scholars based in United States, Australia and Germany. Sumer S. Vaid's co-authors include Gabriella M. Harari, Jacob D. Teeny, Sandra Matz, Moran Cerf, Samuel D. Gosling, Clemens Stachl, Markus Bühner, Ramona Schoedel, Florian Pargent and Sven Hilbert and has published in prestigious journals such as Journal of Personality and Social Psychology, Scientific Reports and Computers in Human Behavior.

In The Last Decade

Sumer S. Vaid

12 papers receiving 266 citations

Hit Papers

The potential of generative AI for personalized persuasio... 2024 2026 2025 2024 25 50 75

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sumer S. Vaid United States 6 101 67 56 52 40 12 276
Kevin Koban Austria 11 149 1.5× 50 0.7× 44 0.8× 37 0.7× 34 0.8× 39 280
Katharina Jahn Germany 9 172 1.7× 57 0.9× 26 0.5× 35 0.7× 51 1.3× 24 308
Helena Schmitt Germany 6 90 0.9× 31 0.5× 69 1.2× 26 0.5× 30 0.8× 10 261
Masanori Takano Japan 8 95 0.9× 26 0.4× 23 0.4× 31 0.6× 30 0.8× 35 215
April Tyack Australia 9 153 1.5× 21 0.3× 24 0.4× 36 0.7× 53 1.3× 13 306
Chin‐Lan Huang Taiwan 8 55 0.5× 109 1.6× 54 1.0× 46 0.9× 44 1.1× 10 300
Bartosz Gula Austria 11 57 0.6× 26 0.4× 55 1.0× 30 0.6× 24 0.6× 22 346
Jhen-Ni Ye Taiwan 8 135 1.3× 53 0.8× 10 0.2× 43 0.8× 34 0.8× 18 276
Ashwaq Alsoubai United States 9 138 1.4× 53 0.8× 61 1.1× 7 0.1× 36 0.9× 24 262
Erhan Delen United States 8 94 0.9× 23 0.3× 23 0.4× 57 1.1× 11 0.3× 17 430

Countries citing papers authored by Sumer S. Vaid

Since Specialization
Citations

This map shows the geographic impact of Sumer S. Vaid's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sumer S. Vaid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumer S. Vaid more than expected).

Fields of papers citing papers by Sumer S. Vaid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sumer S. Vaid. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sumer S. Vaid. The network helps show where Sumer S. Vaid may publish in the future.

Co-authorship network of co-authors of Sumer S. Vaid

This figure shows the co-authorship network connecting the top 25 collaborators of Sumer S. Vaid. A scholar is included among the top collaborators of Sumer S. Vaid based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sumer S. Vaid. Sumer S. Vaid is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Vaid, Sumer S., Lara Kroencke, Sanaz Talaifar, et al.. (2024). Variation in social media sensitivity across people and contexts. Scientific Reports. 14(1). 6571–6571. 9 indexed citations
2.
Vaid, Sumer S., et al.. (2024). Meaningful Peer Social Interactions and Momentary Well-Being in Context. Social Psychological and Personality Science. 15(8). 921–932. 3 indexed citations
3.
Peters, Heinrich, et al.. (2024). Social media use is predictable from app sequences: Using LSTM and transformer neural networks to model habitual behavior. Computers in Human Behavior. 161. 108381–108381. 2 indexed citations
4.
Matz, Sandra, et al.. (2024). The potential of generative AI for personalized persuasion at scale. Scientific Reports. 14(1). 4692–4692. 99 indexed citations breakdown →
5.
Vaid, Sumer S.. (2023). Paradigm shifts in digital personalization. Nature Reviews Psychology. 2(7). 390–390. 1 indexed citations
6.
Vaid, Sumer S., et al.. (2023). EMOTION RECOGNITION USING FOOTSTEP-INDUCED FLOOR VIBRATION SIGNALS. 1 indexed citations
7.
Vaid, Sumer S., et al.. (2023). Situating smartphones in daily life: Big Five traits and contexts associated with young adults’ smartphone use.. Journal of Personality and Social Psychology. 125(5). 1096–1118. 4 indexed citations
8.
Stachl, Clemens, Florian Pargent, Sven Hilbert, et al.. (2020). Personality Research and Assessment in the Era of Machine Learning. European Journal of Personality. 34(5). 613–631. 79 indexed citations
9.
Harari, Gabriella M., Sumer S. Vaid, Sandrine R. Müller, et al.. (2020). Personality Sensing for Theory Development and Assessment in the Digital Age. European Journal of Personality. 34(5). 649–669. 30 indexed citations
10.
Vaid, Sumer S. & Gabriella M. Harari. (2020). Who uses what and how often?: Personality predictors of multiplatform social media use among young adults. Journal of Research in Personality. 91. 104005–104005. 26 indexed citations
12.
Vaid, Sumer S., et al.. (2019). Modeling Personality vs. Modeling Personalidad. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 3(3). 1–24. 17 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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