# Detection of Hidden Communities in Twitter Discussions of Varying Volumes
## 6 Discussion and Conclusions  
The experiments conducted have shown the relative mathematical efficiency of the selected methods for detecting user communities in the discussions of Twitter (the microblogging service with elements of a social network) when the discussions are presented in the form of directed graphs of different sizes. In Appendix A, we show the summary of the results. Table A1 clearly demonstrates that the Infomap algorithm can be called the best; however, due to the property of highlighting one large society, it can rather be used as a preparatory stage for the subsequent clustering by another algorithm, or the repeated application of Infomap. After Infomap comes the Leiden algorithm, which has shown the best results after Infomap, and does not have the ability to single out one large community. Therefore, these two algorithms can be used in conjunction. If it is necessary to isolate overlapping communities based on test results, the GANXiS algorithm should be used. Table A2 shows that the generalized \(K\)-means and GANXiS algorithms are not suitable for large-scale Twitter data. Infomap and Leiden (again), just as Direct Louvain, show very similar results as to the number of the detected communities, and the numbers are lower. Here, we need to repeat that, without a clear sociological task, we could not set the ground truth to which to compare the test results; the number of the detected communities (higher or lower) is better depending on the research goal. In general, the low number of robust communities is optimal. This is why we see these three algorithms as coming closer to possible ground truth in social research. Yet, it is also necessary to state that algorithmic results do not correspond to the logic of social studies designated in Section 2.2, as the methods come to either delineation of one large community or a much larger number of smaller communities detected. Of the three aforementioned algorithms with the best (lowest) number of communities, Infomap finds the largest groups, which might be considered the best result. Yet, it would be too bold to call such a result satisfactory in sociological terms. Sociologically, the use of the tested algorithms poses a general question on their applicability for current social science tasks, as well as the following questions:  
* How does the structure of hidden communities relate to the expected social, cultural, and/or political cleavages in the discussion? * How can algorithmic detection of hidden communities come closer to detecting communities of views, as linked to communities of formal connections? Earlier, we had partly answered this question [37] by using a complicated multi-step methodology of group views detection. However, the use of a combination of Infomap (to find the discussion core) and Leiden (to find modules within the core) might be a shorter way to find the communities based on social traits or views. This creates implications for further research that will show whether the formal community structure corresponds to the substantial divisions in the discourses. \begin{table}
\begin{tabular}{l c c c c c c c} \hline  & **Number** & **1** & **2** & **3** & **4** & **5** & **6** & **7** \\ \hline DLPA & 84,409 & 1244 & 882 & 726 & 662 & 576 & 529 & 488 \\ DirLouv & 26,415 & 68,217 & 45,678 & 44,734 & 40,369 & 26,807 & 22,583 & 18,774 \\ Infomap & 26,497 & 164,839 & 33,635 & 32,111 & 25,038 & 20,098 & 17,226 & 14,033 \\ OSLOM & 67,296 & 34,960 & 27,735 & 26,061 & 17,319 & 10,912 & 7614 & 6962 \\ GKM & - & - & - & - & - & - & - & - \\ LeidMod & 26,335 & 56,201 & 39,371 & 33,976 & 27,120 & 25,745 & 20,270 & 17,705 \\ LeidCPM & 34,647 & 949 & 719 & 626 & 607 & 565 & 531 & 521 \\ GANXiSd & - & - & - & - & - & - & - & - \\ GANXiSo & - & - & - & - & - & - & - & - \\ \hline \end{tabular}
\end{table} 
Table 8: The number of communities obtained on the Charlie Hebdo dataset and the value of the seven largest of them for each algorithm. Comparing our results to other works also shows the following.