# The Trends and Content of Research Related to the Sustainable Development Goals: A Systemic Review
## 3 Results and Discussions
### Work of the Hierarchical Agglomerative Clustering Technique  
We employed CATAR to carry out multi-stage document clustering (MSDC) with bibliographic coupling (BC) as the core algorithm. A landscape of 11 clusters was derived, with a total of 1170 papers participating in the process. The numbers and percentages of papers and the characteristic terms of the 11 clusters were demonstrated in Table 7. Together with the characteristic terms, these papers can be referred to for defining each cluster. The most cited articles in each cluster can also be obtained by running CATAR. Figure 3: The number of SDG-related papers in the database from 2013 to 2021. Figure 2: The number and trends of citations in the top eight fields and the number in the top year for each field. We found relatively few papers included in the last three clusters. It means that information shown by these clusters would not be essential, but adopting them in the whole HAC framework could make interpretations and applications complicated. Thus, these three clusters were removed. Further analysis of the remaining eight clusters was then conducted. Table 8 demonstrates the two most cited papers in each cluster [28; 91; 92; 93; 94; 95; 96; 97; 98; 99; 100; 101; 102; 103; 104; 105]. The resulting names of the clusters were also determined and included in this table. The biggest cluster related to synergies and trade-offs of SDGs, including almost half of the papers. The second-largest cluster captured papers with a rather critical point of view toward SDGs, emphasizing education and inequity. The third cluster covered a similar number of papers to the second one, basically relating to systems analysis techniques such as optimization, multi-objective programming, and multi-criteria decision making (MCDM). The fourth cluster was also about interactions between SDGs but more on the knowledge structure analysis, comparison, and classification. The remaining clusters were also named according to the most cited papers and keywords extracted by CATAR. They are \"business and institution\", \"income and networking\", \"cooperation and resilient transformation\", and \"water and citizen science\". \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Cluster No.** & **Number of Papers** & **Percentage of Papers** & **Characteristic Terms** \\ \hline
1 & 504 & 43.10\% & synergy, trade-offs, successful, turn, spain \\
2 & 144 & 12.30\% & education, critical, education for sustainable development, esdg, hertendals \\
3 & 134 & 11.50\% & program, multi-objective, optimization, goal program, multi-objective optimization \\
4 & 92 & 7.90\% & interaction, sdg interaction, comparison, literature, fic \\
5 & 73 & 6.20\% & institutional, investor, compa, pension, business \\
6 & 67 & 5.70\% & network, interlinkage, quantitative, decouple, income-based \\
7 & 58 & 5.00\% & company, logic, sustainability, decade of action \\
8 & 51 & 4.40\% & citizen, monitor, citizen science, water, quality \\
9 & 26 & 2.20\% & promote, unify, database, bundle \\
10 & 17 & 1.50\% & prioritization, machine, natural, language, boost \\
11 & 4 & 0.30\% & partial, order, partial order, european, union \\ \hline \hline \end{tabular}
\end{table} 
Table 7: The 11 clusters derived by CATAR and the corresponding numbers and percentages of papers, and the characteristic terms.