A Bibliometric Analysis of Human-Robot Interaction Behaviour Research
Bibliographic record
Abstract
In Human-Robot Interaction (HRI) research, "behaviour" refers to one way robots express themselves and convey information. With the increased interest in robots in industrial, research, and domestic settings, understanding how robots behave and are perceived has become a top priority in the HRI community. Using the Web of Science Core Collection (WoSCC), we conducted a bibliometric analysis on 2,464 articles and proceedings about robot behaviour published from 2005 to 2025. Our analysis reveals a rapid development with a clear shift in HRI research on robot behaviour, moving from early theoretical and conceptual foundations toward more application-oriented studies, such as task analysis and navigation. Behavioural science and collaborative robotics have emerged as central research themes within this evolving landscape, with current research no longer limited to interaction methodologies but increasingly integrating other learning-based approaches to enhance user interaction experiences. Our analysis highlights that the field is characterized by strong cross-regional and institutional collaboration, with the United States serving as an international research center, and suggests future studies may include exploration into the interplay between behavioural science, human-robot collaboration, artificial intelligence, and robotic behaviours.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.551 | 0.660 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.088 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".