## 6 Conclusions, Limitations, and Future Work  
In this study, we proposed a neutrosophic-based SA process suitable for the uncertain nature of OSNs. In the proposed model, a new element was integrated with the classical opinion elements using NL. The new element is the user's weight, which depends on measuring the influence of users using the SNA centrality measure and recorded reactions to their expressed opinions, then classifying them into four main influencer types using ANN. A comparative analysis of different SNA tools was conducted and ended in choosing Graphistry for the mission. Different polarity scores than the regularly applied techniques, TextBlob in our case, were generated due to the perspectivism factor of users. This resulted in different scores for the same text when shared by users of different influence levels. NL was implemented for the integration purpose of all opinion elements, to provide hybrid classification, and for its ability to handle the resulted opinion dynamicity by considering perspectivism, and the classification indeterminacy. The proposed model succeeded in representing the perspectivism in an effective numerical way by classifying users of the dataset into their influence types using ANN with promising error performance. Moreover, the proposed model opportunely processed perspectivism and SA in parallel, as planned, and integrated both processes using NL. As the first of its type encouraging application, NL effectively achieved the goal of solving the problem of opinion dynamicity and identifying undecided polarities by emulating humans that in turn reflected on the process of OM and its dependable results. On top of that, the proposed model appropriately emphasized \begin{table}
\begin{tabular}{l l l l} \hline \hline \multirow{2}{*}{**User \#**} & **Polarity Score** & **Users’ Weights** & **Polarity Score** \\  & **(TextBlob)** & **(ANN)** & **(Using Our Proposed NL Model)** \\ \hline
13 & 0.25 & 0.00 & (0.00, 0.07, 0.07) & N or WP \\
23 & 0.25 & 0.29 & (0.00, 0.06, 0.06) & N or WP \\
159 & 0.25 & 0.73 & (0.3, 0.84, 0.84) & P or SP \\
44 & 0.8 & 0.33 & (0.68, 0.84, 0.84) & P or SP \\
282 & 0.383 & 0.68 & (0.68, 0.85, 0.85) & P or SP \\
119 & 0.7 & 0.15 & (0.15, 0.31, 0.31) & WP or P \\
415 & 0.7 & 0.23 & (0.15, 0.29, 0.29) & WP or P \\
232 & 0.7 & 0.73 & (0.89, 0.75, 0.75) & SP or P \\
388 & 0.357 & 0.73 & (0.90, 0.30, 0.30) & SP or P \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Sample cases of undecided polarities in the dataset. \begin{table}
\begin{tabular}{l l} \hline \hline \multicolumn{2}{c}{**The Traditional Opinion Elements**} & \multicolumn{1}{c}{**The Proposed Opinion Elements**} \\ \multicolumn{1}{c}{(\(e_{i}\), \(a_{ij}\), \(oa_{ijk}\), \(h_{k}\), \(t_{i}\))**} & \multicolumn{1}{c}{(\(e_{j}\), \(a_{ij}\), \(oa_{ijk}\), \(h_{k}\), \(w_{kl}\), \(t_{i}\))**} \\ \hline \hline (World Football Cup, Africa, 0.8, User#1, July 19) & (World Football Cup, Africa, 0.5, User#1, Micro, July 19) \\ (World Football Cup, \(-\)0.7, User#11, July 18) & (World Football Cup, \(-\)0.15, User#11, Micro, July 18) \\ (World Football Cup, goal, 0.6, User#96, July 18) & (World Football Cup, goal, 0.5, User#96, Macro, July 18) \\ (World Football Cup, Croatia, \(-\)0.1, User#560, July 18) & (World Football Cup, Croatia, \(-\)0.16, User#560, [PERSON], July 18) \\ (World Football Cup, [PERSON], \(-\)0.4, User#214, July 18) & (World Football Cup, [PERSON], \(-\)0.5, User#214, Mega, July 18) \\ (World Football Cup, User#345, 0.1, July 18) & (World Football Cup, User#345, 0.15, Mega, July 18) \\ (World Football Cup, games, 0.4, User#1047, July 11) & (World Football Cup, games, 0.91, User#1047, A-Lister, July 11) \\ (World Football Cup, South Korea game, \(-\)0.1, User#1002, A-Lister, Jun 18) & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Opinions representation between the classic elements and the new proposed elements. readapting OM while applying OSNs to texts for high-quality information suitable for accurate decision making.