## 4 Analysis of Results
Therefore, indirectly, we can verify that the inclusion of the search terms in the document title forms part of the sorting algorithm, which we already knew, but for which we are now able to provide quantitative evidence showing that the weight of this factor is lower than that of citations since there is little difference between the two correlations. Unfortunately, this same analysis cannot be conducted in the case of Microsoft Academic because it does not permit full-text searches. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**System** & \begin{tabular}{c} **Number of Search** \\ **Terms** \\ \end{tabular} & \
\begin{tabular}{c} **Search** \\ **Restrictions Included** \\ \end{tabular} &
\begin{tabular}{c} **Spearman’s** \\ **Coefficient** \\ \end{tabular} & \(\boldsymbol{p}\) \\ \hline Google Scholar & 1 & unrestricted & 0.968 & \textless{}0.0001 \\ Google Scholar & 2 & unrestricted & 0.721 & \textless{}0.0001 \\ Google Scholar & 1 & title & 0.990 & \textless{}0.0001 \\ Google Scholar & 2 & title & 0.994 & \textless{}0.0001 \\ Microsoft Academic & 1 & title, abstract, keywords & 0.907 & \textless{}0.0001 \\ Microsoft Academic & 2 & title, abstract, keywords & 0.937 & \textless{}0.0001 \\ Scopus & 2 & title, abstract, keywords & \textless{}0.107 & \textless{}0.001 \\ WoS-version 1 & 2 & title, abstract, keywords & \textless{}0.075 & \textless{}0.05 \\ Wos-version 2 & 2 & title, abstract, keywords & 0.907 & \textless{}0.0001 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Correlation coefficients for the academic search engines. Figure 1: Google Scholar Searches with One Word and No Title Restriction (rho 0.968, median in blue, the rest of data in gray). Figure 2: Google Scholar Searches with Two Words and No Title Restriction (rho 0.721, median in blue, the rest of data in gray). Figure 4: Google Scholar Searches with Two Words and Title Restriction (rho 0.994, median in blue, the rest of data in gray). Figure 3: Google Scholar Searches with One Word and Title Restriction (rho 0.990, median in blue, the rest of data in gray). Figure 5: Microsoft Academic Searches with One Word and Title Restriction (rho 0.907, median in blue, the rest of data in gray). Figure 6: Microsoft Academic Searches with Two Words and Title Restriction (rho 0.937, median in blue, the rest of data in gray). Likewise, we detected no differences between Google Scholar and Microsoft Academic, above all when comparing the results of searches restricted to the title (Figures 3 and 6). In all four cases, we obtained correlation coefficients of 0.9. Therefore, it seems that both academic search engines apply a very similar weight to the factor of citations received. Finally, it is worth noting that the two bibliographic databases (see Figures 8 and 9) do not employ citations received as a positioning factor, as stated in their documentation. Therefore, it is perfectly logical that their corresponding correlation coefficients are almost zero. However, somewhat surprisingly, in the case of WoS, we found that between 20 May 2019 and 25 May 2019 the ranking was different and we obtained a correlation coefficient similar to that of the academic search engines, i.e., 0.9 (see Figures 10-12) and that, therefore, a different algorithm was being applied with the significant inclusion of citation counts. It is common that before introducing changes in the design of websites, tests are made with real users. Figures 10 and 11 illustrate screenshots of the same search but employing two different relevance rankings. This can be done by randomly publishing different prototypes to gather information on user behavior in order to determine which prototype achieves greatest acceptance. As discussed above, it would seem that WoS was implementing such a procedure and was carrying out tests aimed at modifying its relevance ranking using an algorithm similar to that of academic search engines, although we should insist that this is only an inference. Figure 7: Google Scholar: Title Restriction vs No Title Restriction with Two Words.