## 4 Results
### Model Testing on DS2 (COVID-19 Dataset)
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & & & \multicolumn{3}{c}{**LR**} & \multicolumn{3}{c}{**SVM**} & \multicolumn{3}{c}{**NB**} & \multicolumn{3}{c}{**RF**} \\ \cline{3-14}  & & \multicolumn{3}{c}{_Accuracy_} & _Precision_ & _Recall_ & _Accuracy_ & _Precision_ & _Recall_ & _Accuracy_ & _Precision_ & _Recall_ & _Accuracy_ & _Precision_ & _Recall_ \\ \hline \multirow{3}{*}{1,2} & \multirow{3}{*}{LIWC} & \multirow{3}{*}{74.62} & 75.13 & 76.36 & 73.32 & 72.37 & 77.27 & 74.58 & 74.75 & 75.53 & 69.98 & 70.88 & 69.32 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams} & 67.69 & 67.70 & 69.77 & 70.76 & 70.29 & 74.70 & 69.62 & 71.49 & 66.36 & 66.09 & 67.53 & 62.05 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams + LIWC} & \multirow{3}{*}{**75.05**} & 75.72 & 77.27 & 73.37 & 73.98 & 73.94 & 72.55 & 75.45 & 69.77 & 71.68 & 67.82 & 69.70 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams} & 69.22 & 68.64 & 72.27 & 66.59 & 65.30 & 70.53 & 73.86 & 72.60 & 78.11 & 63.95 & 67.00 & 70.53 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams + LIWC} & \multirow{3}{*}{73.79} & 74.05 & 75.53 & 74.64 & 75.23 & 75.61 & **76.39** & 76.17 & **78.18** & 71.67 & 72.51 & 71.44 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams} & 69.17 & 69.97 & 72.35 & 72.05 & 72.68 & 70.68 & 70.04 & 69.90 & 73.94 & 67.45 & 70.20 & 62.95 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams + LIWC} & \multirow{3}{*}{73.80} & 73.81 & 76.36 & **76.34** & **77.35** & 77.20 & 70.87 & 69.59 & 74.77 & **72.97** & 72.54 & 70.61 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams} & 70.49 & 70.35 & 73.11 & 65.69 & 64.46 & 69.62 & 71.29 & 69.67 & 77.27 & 64.84 & 65.00 & 65.53 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams + LIWC} & \multirow{3}{*}{74.64} & 74.64 & 75.16 & 76.44 & 74.64 & 75.59 & 74.77 & 73.82 & 73.22 & 76.52 & 71.25 & 70.29 & 69.70 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams} & 71.67 & 71.34 & 74.85 & 68.71 & 67.01 & 68.68 & 70.91 & 70.43 & 70.40 & 70.43 & 70.83 & 67.20 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams + LIWC} & \multirow{3}{*}{74.66} & 74.88 & 77.20 & 74.64 & 74.17 & 77.20 & 69.20 & 67.82 & 75.76 & 72.93 & 70.79 & 73.03 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams} & 59.33 & 58.80 & 63.03 & 58.89 & 59.44 & 58.71 & 59.73 & 59.68 & 61.21 & 57.59 & 55.78 & 76.52 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams + LIWC} & \multirow{3}{*}{73.77} & 74.52 & 75.53 & 72.48 & 73.29 & 73.71 & 65.20 & 64.04 & 69.47 & 69.98 & 70.81 & 75.53 \\ \cline{3-14}  & & \multicolumn{3}{c}{n-grams + LIWC} & \multirow{3}{*}{73.77} & \multirow{3}{*}{74.52} & \multirow{3}{*}{75.53} & \multirow{3}{*}{72.48} & \multirow{3}{*}{73.29} & \multirow{3}{*}{73.71} & \multirow{3}{*}{65.20} & \multirow{3}{*}{64.04} & \multirow{3}{*}{69.47} & \multirow{3}{*}{69.98} & \multirow{3}{*}{70.81} & \multirow{3}{*}{75.53} \\ \cline{3-14}  & & \multicolumn{3}{c}{} & & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Performance of selected machine learning models achieved by applying natural language processing techniques to the COVID-19 dataset (DS2). The maximum recall of 78.18% was achieved by combining an analysis of (1,2)-grams and LIWC using multinomial Naive Bayes while the SVM model achieved the maximum precision of 77.35% with the combined analysis of bigrams and LIWC.