Table 8 Summary of the lexicon-based approach (Corpus based approach) used for opinion mining

[98]

To introduce SmartSA, a lexicon-based sentiment classification system for social media genres

Hybridise a general-purpose lexicon, SmartSA, SWN

Twitter, Digg, MySpace

Positive and negative

[99]

To improve the detection of emotional state of patients in Brazilian online cancer communities by using the proposed approach

SentiHealth-Cancer

(SHC-pt)

Facebook

Positive, negative or neutral

[100]

To present the results of the systematic analysis of opinion mining (OM) for YouTube comments

Italian sentiment dictionary from the SentiWordNet sentiment lexicons and the MPQA Lexicon

Review from videos of products, English and Italian

Positive, negative or neutral

[86]

To learn sentiment words based on both content domain and language domain

Corpus-based lexicon generation method

Twitter stock market

Positive and negative

[101]

To extract aspects, classify aspect-related sentiment and generate an aspect-level summary

Hybrid sentiment classification scheme, lexicon-based (corpus-based approach)

SentiWordNet lexicon

Product reviews

Positive and negative

[102]

To detect sentiment out of textual snippets which express people’s opinions in different languages by proposed methodology

Hybrid approach lexicon Greek Sentiment Lexicon, NRC Word-Emotion Association Lexicon (EmoLex)

Online user reviews in both Greek and English (Greek e-shopping site with various products)

Positive or negative

[97]

To correlate the distinct twitter comments of statesmen of distinct countries for having concrete knowledge on the application of drugs to patients attacked by COVID-19

TextBlob lexicon

Twitter

Positive and negative