# Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase
## 4 Discussion
### Current Context of Social Robotics in Robotics Research  
We computed the participation of social robotics papers in the larger network of robotics research. The results are shown in Table 5. The four largest clusters, and the three largest sub-clusters within them, contain 90% of the social robotics articles, and the other 10% is scattered in the remaining small clusters of the large network. Social robotics research is concentrated on the robot learning sub-cluster of robotic locomotion and heavily concentrated in the human robot interaction sub-cluster of autonomous robots.  
The robot learning sub-cluster contains research on robotics learning from demonstration [57], self-reconfigurable robot systems [58] and artificial intelligence methods for movement planning and world representation [59]. It covers research on machine learning techniques that can be applied in robotics systems to decide actions and trajectories.  
The human-robot interaction sub-cluster, as shown in Table 5, gathers 58.8% of social robotics articles. Besides containing the largest proportion of the data under study, it collects research directly related to it. We deemed it pertinent to take a closer look into this sub-cluster and conducted a separate analysis shown in Appendix A.  
The field of social robotics is cohesive. Some emergent academic sub-fields may get dispersed in the clusters of the larger domain [12]. However, we found that a large proportion (58.8%) of social robotics articles remained connected. This may serve as an indicator that the field is maturing, having enough specific material to be cited, and thus staying connected.  
A closer inspection of the references supports that statement. The amount of unique references within the robotics domain is evenly distributed among the four clusters that compose the robotics research as shown in Table 6. However, those articles belonging to robotic locomotion and autonomous robots are more frequently cited; meaning that social robotics enjoys a broad robotics knowledgebase, with a clear concentration toward applied technologies.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Robotics Research Clusters**} & \multicolumn{2}{c}{**References**} & \multicolumn{2}{c}{**Citations**} \\ \cline{2-5}  & **Number** & **\%** & **Number** & **\%** \\ \hline
1. Automation and control systems & 1554 & 14.33\% & 3172 & 10.87\% \\
2. Robotic locomotion & 2893 & 26.68\% & 7803 & 26.74\% \\
3. Autonomous robots & 2922 & 26.95\% & 11,539 & 39.55\% \\
4. Robotic surgery & 2624 & 24.20\% & 5286 & 18.12\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: References and citations from social robotics to clusters in the robotics network.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \# & **Cluster** & **Sub-Cluster** & **Social Robotics Articles** & **\%** \\ \hline \multirow{3}{*}{1} & & 1.1 Path planning/obstacle avoidance & 175 & 5.2\% \\  & Automation and control systems & 1.2 Visual servoing & 1 & 0.0\% \\  & & 1.3 Robot manipulators & 4 & 0.1\% \\ \hline \multirow{3}{*}{2} & & 2.1 Walking robots & 16 & 0.5\% \\  & & 2.2 Robot learning & 539 & 16.2\% \\  & & 2.3 Rehabilitation robotics & 40 & 1.2\% \\ \hline \multirow{3}{*}{3} & & 3.1 Simultaneous localization and mapping & 21 & 0.6\% \\  & Autonomous robots & 3.2 Human-robot interaction & 1959 & 58.8\% \\  & & 3.3 Tactile sensing and robotic grasping & 42 & 1.3\% \\ \hline \multirow{3}{*}{4} & & 4.1 Robotic assisted surgery & 111 & 3.3\% \\  & & 4.2 Robot assisted radical prostatectomy & 76 & 2.3\% \\ \cline{1-1}  & & 4.3 Transoral robotic surgery & 37 & 1.1\% \\ \hline \hline \end{tabular}
\end{table}
Table 5: Participation of social robotics articles in the sub-clusters of the robotics network.