# Sentiment Analysis of Students' Feedback with NLP and Deep Learning: A Systematic Mapping Study
## 4 Systematic Mapping Study Results
### Most Relevant Articles
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Ref.** & **Year** & **Type** & **Techn.** & **App.** & **Models/Algorithms** & **Evaluation Metrics** & **Dataset** & **Rank** \\ \hline
[73] & 2020 & J & NLP, DL & LB, Sup & Glove, LSTM & F1 = 83\%, R = 78\%, P = 90\% & \multirow{2}{*}{16,175 sentences} & \multirow{2}{*}{Q1} \\  & & & & & & Acc = 86\% & & \\ \hline
[24] & 2020 & J & ML, DL & Sup & NB, SVC, LSCV, RF, LSTM, CNN, & & & & \\  & & & & & CNN\_LSTM, BERT, EvoMSA & Acc = 93\% & 24,552 opinions, & \\ \hline
[90] & 2020 & J & NLP, ML, DL & LB, UnS & & h2x, tf’idf, GloVe, fastText, & & & \\  & & & & & LDA2 Vce, NB, SVM, LR, K-NN, & & & \\  & & & & & RF, AdaBoost, Bagging, CNN, & & & \\  & & & & & RNN, GRU, LSTM & & & \\ \hline
[14] & 2020 & J & DL & Sup & LSTM, CNN & F1 = 86.13\% &
\begin{tabular}{c} Coursera \\ (104 K reviews) \\ \end{tabular} & \multirow{2}{*}{Q1} \\ \hline
[25] & 2020 & J & ML & Sup & NB, SVM, k-NN, CBT & F1 = 88\% & Class central & Q1 \\ \hline
[68] & 2020 & J & NLP & UnS & E-LDA, SVM, kMeans, tf’idf & F1 = 89\% &
\begin{tabular}{c} Questionnaire \\ (10 students) \\ \end{tabular} & \multirow{2}{*}{Q1} \\ \hline
[51] & 2019 & J & NLP, ML, & UnS & LDA & N/A & Survey & Q1 \\ \hline
[56] & 2019 & J & NLP, ML, DL & LB &
\begin{tabular}{c} SPPM + ID3, NB, SCM, BFTree, \\ LR, BayeNet, Stacking, AdaBoost \\ \end{tabular} & \multirow{2}{*}{30,500 sentences} & \multirow{2}{*}{Q1} \\ \hline
[87] & 2019 & J & NLP & LB, UnS & \begin{tabular}{c} VADER, Topic Modeling, \\ Ensemble LDA \\ \end{tabular} & \
\begin{tabular}{c} F1 = 79.54\%, P = 79.69\%, \\ R = 79.84\% \\ \end{tabular} &
\begin{tabular}{c} Niche.com \\ (100 K) \\ \end{tabular} & \multirow{2}{*}{Q1} \\ \hline
[13] & 2019 & J & DL & LB, Sup & Glove, LSTM & F1 = 86\%, P = 88\%, R = 85\%, &
\begin{tabular}{c} Questionnaire \\ (5015) \\ \end{tabular} & \multirow{2}{*}{Q1} \\ \hline
[89] & 2019 & J & NLP & LB, UnS & Sentiment topic models-LDA & Acc = 86.5\% &
\begin{tabular}{c} Feedback form \\ (4895) \\ \end{tabular} & \multirow{2}{*}{Q2} \\ \hline
[51] & 2019 & J & NLP & UnS & LDA & N/A & Survey (2254) & Q1 \\ \hline
[61] & 2019 & J & NLP & LB & Semantira & N/A & Survey & Q2 \\ \hline
[12] & 2018 & C & ML, DL & LB, UnS & \
\begin{tabular}{c} BiNB, BiSVM, LSTM, DT-LSTM, \\ L-SVM, D-SVM, LD-SVM \\ \end{tabular} &
\begin{tabular}{c} F1 = 89.77\%, Acc = 90.12\%, \\ Pearson = 0.095 \\ \end{tabular} & \multirow{2}{*}{B} \\ \hline
[32] & 2018 & C & ML & Sup & NB, ME & F1 = 87.94\% & Survey (16,000) & B \\ \hline
[58] & 2018 & J & DL, ML & Sup & CNN, SVM & Acc = 76\%, Kappa = 85\% &
\begin{tabular}{c} Feedback form \\ (73 reviews) \\ \end{tabular} & \multirow{2}{*}{Q1} \\ \hline
[60] & 2018 & C & NLP & LB & VADER & N/A & Survey (16,000) & B \\ \hline
[69] & 2018 & C & NLP, ML & UnS & DT, NB, GLM, CT, LDA & F1 = 79.3\%, P = 67.5\%, & \multirow{2}{*}{Questionnaire} \\  & & & & & R = 96.2\% & \\ \hline
[79] & 2018 & C & NLP, ML & LB, Sup & NB, ME & F1=87\% & SFMS (5341) & B \\ \hline \hline \end{tabular}
\end{table} 
Table 9: A summary of relevant articles.