Page 140 - Handbook of Deep Learning in Biomedical Engineering Techniques and Applications

Chapter 5 Depression discovery in cancer communities using deep learning 129

Table 5.2 Literature Summary of supervised ML approaches for SA.

Algorithms Level of
Authors used Data set/Source Polarity Language granularity
Pang et al. [32] NB, ME, SVM IMDB Pos/neg English Document
level
Gamon [33][89] NB, k-NN, SVM Survey feedback Ratings 1e4 English Document
with SMO reports level
Pang and Lee [34] NB and SVM Movie review snippets Subjective versus English Sentence
from imdb.com and objective level
rottentomatoes.com
Read [35] NB and SVM IMDB Pos/neg English Document
level
Gokulakrishnan NB, SVM, SMO, Twitter Pos/neg and neutral English Sentence
et al. [37] random forest, level
J48
Jiang et al. [38] SVM Twitter Pos/neg and neutral English Sentence
level
Ghazi et al. [39] SVM Blogs posts and Neutral/emotional, pos/ English Document
children's stories neg, sadness/fear/ and
labeled for affect surprise/disgust/ sentence
anger levels
Kasper and Vela Hotel reviews Pos/neg and neutral German Document
[40] level
Esmin et al. [41] Multiclass SVM Twitter Emotional/ English Sentence
nonemotional level
Pos/neg, emotion
categorizations
Taboda et al. [42] SVM and NB rottentomatoes.com Pos/neg English Document
level
Lombart [43] NB, SVM, Movie reviews, twitter Pos/neg English Document
random and
forests and sentence
neural levels
networks
Hasan et al. [44] SVM, NB Twitter Pos/neg Urdu Sentence
level
IMDB, Internet Movie Database; k-NN, kernel nearest neighbor; ML, machine learning; ME, maximizationeexpectation; NB, naþve
Bayes; SMO, sequential mining optimization; SVM, support vector machine.