# How to Extract Meaningful Insights from UGC:
## 3 Results
### Data Visualization MR  
After applying the MR algorithm, it was possible to preview the communities with different resolutions [36]. The objective was to obtain the largest number of communities related to education and innovation in the sector so that a comparison of results of different tests enables identification of communities that are most relevant [2; 16]. Table 4 shows the results of different tests performed according to the number of communities identified, their modularity, and the resolution applied to detect them. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**N\({}^{\circ}\)** & **Name** & **Description** & **Sentiment** \\ \hline
1 & Innovative teaching (IT) & Learning models based on new teaching & Positive \\
2 & Tutorials and tips for & & \\  & teaching (TTE) & Tutorials and tips for new tools for teaching. & Neutral \\
3 & Digital teaching and & New platforms related to education in digital environments. & Positive \\
4 & Innovative teaching & Skills related to new information technologies for & Negative \\  & skills (ITS) & & teaching and tutoring. & \\
5 & Digital interaction and & Thematic linked to engagement and the reciprocal & \\  & engagement (DIE) & connection of communication through digital environments & Positive \\  & & in the field of education. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Mean latent Dirichlet allocation (LDA) topics results description. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Conclusion Reliability** & **[PERSON]’s Alpha Value** & **This Research Study** & **Average KAV** \\ \hline High & \(\alpha\geq 0.800\) & Positive Sentiment & 0.876 \\ Tentative & \(\alpha\geq 0.667\) & Negative Sentiment & 0.882 \\ Low & \(\alpha<0.667\) & Neutral Sentiment & 0.641 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: LDA topics results description. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**N\({}^{\circ}\)** & **Topic** & **Insight** & **Count** & **WP** \\ \hline
1 & IT & Innovative learning processes increase positive results in teaching. & 273 & 0.302 \\
2 & TTE & Tutorials and tips on new teaching tools are a useful & 213 & 0.291 \\  & & internet resource for teachers & \\
3 & DLE & The platforms for online education are an & & \\  & & efficient resource for teachers. & 209 & 0.283 \\
4 & ITS & There is a gap in the digital skills of teachers regarding & 179 & 0.209 \\  & & the use of digital tools for teaching. & & \\
5 & DIE & The communication between teachers on social networks is & 141 & 0.199 \\  & & enriching and attracts new ideas and teaching tools. & & \\ \hline \end{tabular}
\end{table} 
Table 3: LDA topics insight descriptions. For the visualization of the neural networks and the corresponding communities, visualization filters were implemented using the open source Gephi software. The filters, following the application of the MR algorithm at selected resolution levels, use Force Atlas and Force Atlas 2 as shown in Table 5[37]. These are the settings that are generally applicable and are used to enhance results visualizations. Note that the visualization and resolution regarding the size of each node is 10 and nodes are grouped by communities according to their weight and relation to the main community. In addition, communities are arranged in color scales as shown in Figure 4a-c. In (a) the results of the communities identified with the filters from Table 5 are presented. In (b) a network contraction filter is applied to help visualize the different modularities. Finally, in (c), the distance between each content community is observed with greater resolution to highlight the communities with the highest MR relative to the chosen subject (i.e., innovation in education), (see also Table 6). Figure 4a-c shows that the center of all identified communities obtains a high MMC, represented here by dark blue. This highlights the relevance of the communities. In addition, the UGC content published without being grouped in a community is shown in black.