# Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase
## Appendix A Bibliometric Analysis of Human-Robot Interaction Research  
From the structure of the robotics network, the sub-cluster of human-robot interaction (HRI) was found as part of the autonomous robots research cluster. This sub-cluster collected 58.8% of articles from social robotics. We compared the contents of HRI with the social robotics network to understand their similarities and differences. Besides the creation of citation networks, we compared the contents of the two by computing the cosine similarity score between the textual information of each pair of clusters. Cosine similarity is defined as follows:  
\[cosinesimilarity(t,s)=\ \frac{\vec{j}_{t}\cdot\vec{j}_{s}}{\sqrt{\sum_{i} \vec{i}^{i}\cdot\vec{j}_{t}}} \tag{1}\]  
where \(t\) and \(s\) are clusters in each network and \(j_{t}\) and \(j_{s}\) are the term-vectors of \(t\) and \(s\) respectively. The vectors are created from the words found in the title, abstract and keywords of the articles within each cluster. Terms are weighted by the term-frequency inverse document frequency (tf-idf) [74]. Cosine similarity with tf-idf is a common and effective strategy to determine the similarity of documents in text mining [75]. The citation network of HRI is shown in Figure 10. Ninety percent of the articles are represented by the 10 largest clusters. In the figure, only seven are shown; the rest are hidden behind those larger ones. The complete list of clusters is given in Table 10, including the number of articles, average year and the article receiving the most citations within the cluster. \begin{table}
\begin{tabular}{c l c c c} \hline \hline \# & \multicolumn{2}{c}{**Sub-Cluster**} & **Size** & **Average Year** & **Most Cited** \\ \hline
1 & Human factors and ergonomics in human robot interaction & 1296 & 2012.0 & [5] \\
2 & Care-robotics & 1254 & 2010.8 & [76] \\
3 & Rescue robots, tele-operated robotics and robot competition & 1239 & 2010.7 & [35] \\
4 & Emotion detection & 689 & 2010.6 & [77] \\
5 & Gestures and joint attention & 530 & 2011.5 & [78] \\
6 & Robot for child development & 497 & 2012.8 & [30] \\
7 & Military robotics and ethical issues of robots & 203 & 2012.2 & [79] \\
8 & Algorithms and technologies for care robotics & 199 & 2011.4 & [80] \\
9 & Hand controllers, robot networks & 186 & 2012.2 & [81] \\
10 & Real versus on-screen agents & 95 & 2010.5 & [82] \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Sub-clusters of human-robot interaction (HRI). HRI Sub-clusters 1, 2, 3, 4 and 6 are an expansion of those found in social robotics. They contain the literature from social robotics and robotics papers that cite or are cited by those. In HRI, the cluster we labeled as care-robotics is the merger of robots as partners and robots for the elderly. Other clusters were different from any of the social robotics. HRI Sub-cluster 5, gestures and joint attention, is the research on specific technologies solving the problem of gesture recognition, gesture commands and robot understanding of pointing behavior. Sub-cluster 7, military robotics and ethical issues of robots, targets those technologies for warfare and the development of smart weapons [83]. While robot-ethics may have been expected to also appear in the network of social robots, we found that ethical concerns are discussed in light of military robots [84], thus forming a single cluster. HRI Sub-cluster 8 is similar to HRI Sub-cluster 2; both deal with care-robotics. However, sub-cluster 2 is focused on applications, challenges and user views, while Sub-cluster 8 covers technologies that make these robots possible. Voice recognition systems [85] and especially designed actuators [86] are found here. HRI Sub-cluster 9 is diverse. The main literature targets the development of safe controllers for the task of object handover [87], but also general frameworks, such as cloud networked robotics, are studied [88]. Finally, HRI Sub-cluster 10 covers the difference in interacting with robots versus on-screen agents or characters [82].