Sandra Matz

55 papers receiving 2.7k citations

Hit Papers

The potential of generative AI for personalized persuasion at scale 2024 · 99 citations
992015202620182022200400600

Peers

Sandra Matz
Comparison fields: 5 of 155
  • Applied Psychology 354
  • Marketing 319
  • Social Psychology 633
  • Experimental and Cognitive Psychology 402
  • General Decision Sciences 54
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Countries citing papers authored by Sandra Matz

Since Specialization
Citations

This map shows the geographic impact of Sandra Matz'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 Sandra Matz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandra Matz more than expected).

Fields of papers citing papers by Sandra Matz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sandra Matz. 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 Sandra Matz. The network helps show where Sandra Matz may publish in the future.

Co-authors

The 25 scholars most cited alongside Sandra Matz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sandra Matz Line = papers co-authored together Sandra Matz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines.
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2015602
2
Psychological targeting as an effective approach to digital mass persuasion
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2017469
3
Well-being is more than happiness and life satisfaction: a multidimensional analysis of 21 countries
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2020434
4 2016103
5 2020100
6
The potential of generative AI for personalized persuasion at scale
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202499
7 201696
8 201796
9 202090
10 201964
11 201960
12 202258
13 201945
14 202043
15 202136
16 202034
17 201833
18 202131
19 202030
20 201829

About Sandra Matz

Sandra Matz is a scholar working on Applied Psychology, General Decision Sciences, Marketing, Clinical Psychology and Experimental and Cognitive Psychology, having authored 56 papers that have together received 2.9k indexed citations. Recurring topics across this work include Personality Traits and Psychology (11 papers), Behavioral Health and Interventions (11 papers), Mental Health Research Topics (8 papers), Consumer Behavior in Brand Consumption and Identification (7 papers), Media Influence and Health (7 papers), Digital Mental Health Interventions (6 papers), Psychological Well-being and Life Satisfaction (5 papers) and Mental Health via Writing (3 papers). The work is most often cited by research in Applied Psychology (354 citations), Marketing (319 citations), Social Psychology (633 citations), Experimental and Cognitive Psychology (402 citations) and General Decision Sciences (54 citations). Sandra Matz has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include David Stillwell, Michał Kosiński, Gideon Nave, Samuel D. Gosling, Áine Maguire, Kai Ruggeri, Felicia A. Huppert, Eduardo García‐Garzón, Joe J. Gladstone and Gabriella M. Harari. Their work appears in journals such as Journal of Personality and Social Psychology, Scientific Reports, Proceedings of the National Academy of Sciences, American Psychologist and Computers in Human Behavior.

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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