Swee Lan See

483 citations
12 papers · 308 · h-index 7

Impact in

Papers in

Swee Lan See

11 papers receiving 293 citations

Peers

Swee Lan See
Comparison fields: 5 of 64
  • Social Psychology 210
  • Human-Computer Interaction 37
  • Artificial Intelligence 158
  • Applied Psychology 24
  • Experimental and Cognitive Psychology 54
Replace Raquel Oliveira with:
Raquel Oliveira Portugal
Benedict Tiong Chee Tay Singapore
Emer Gilmartin Ireland
Özge Nilay Yalçın Canada
Md. Iftekhar Tanveer United States
Aimi Shazwani Ghazali Malaysia
Hendrik Buschmeier Germany
Tim Bickmore United States
Peter A. M. Ruijten Netherlands
Eetu Haataja Finland
Swee Lan See relative to Raquel Oliveira Portugal Raquel Oliveira's profile →
Citations per field
00.5×4.3×
Raquel Oliveira · 1×
Citations per year

Countries citing papers authored by Swee Lan See

Since Specialization
Citations

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

Fields of papers citing papers by Swee Lan See

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Swee Lan See. 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 Swee Lan See. The network helps show where Swee Lan See may publish in the future.

Co-authors

The 5 scholars most cited alongside Swee Lan See, 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 Swee Lan See Line = papers co-authored together Swee Lan See links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2013212
2 201136
3 201522
4 20149
5 20128
6 20156
7 20146
8 20055
9 20112
10
The Influence of Voice Pitch on the Evaluation of a Social Robot Receptionist
20111
11
Making Social Robots More Attractive: The Effects of Voice Pitch, Humor and Empathy
20121
12
INVESTIGATING SOCIAL ATTITUDES TOWARDS PRICING MODELS IN SOCIAL GAMING
20140

About Swee Lan See

Swee Lan See is a scholar working on Social Psychology, Artificial Intelligence, Sociology and Political Science, Clinical Psychology and Information Systems and Management, having authored 12 papers that have together received 308 indexed citations. Recurring topics across this work include Social Robot Interaction and HRI (5 papers), AI in Service Interactions (3 papers), Technology Adoption and User Behaviour (2 papers), Speech and dialogue systems (2 papers), Digital Marketing and Social Media (2 papers), Humor Studies and Applications (2 papers), Digital Mental Health Interventions (2 papers) and Emotion and Mood Recognition (2 papers). The work is most often cited by research in Social Psychology (210 citations), Human-Computer Interaction (37 citations), Artificial Intelligence (158 citations), Applied Psychology (24 citations) and Experimental and Cognitive Psychology (54 citations). Swee Lan See has collaborated with scholars based in Singapore and Netherlands. Frequent co-authors include Anton Nijholt, Betsy van Dijk, Andreea I. Niculescu, Haizhou Li and Ting Liu. Their work appears in journals such as International Journal of Social Robotics, Procedia Manufacturing, University of Twente Research Information and SSRN Electronic Journal.

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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