Table 1 Comparing various state-of-the-art research works on sentiment analysis.
From: Ensemble stacked model for enhanced identification of sentiments from IMDB reviews
Citation | Proposed | Techniques | Benefits | Limitations | Year |
|---|---|---|---|---|---|
Mashooq et al.30 | A comprehensive evaluation Research on sentiment analysis has been conducted in the Urdu-language literature. | A taxonomy that adheres to classification techniques. | Feature extraction methods are also extracted. | SLR of 24 reviews to researchers. | 2022 |
Zeeshan Rasheed31 | By using a database, a Python program, and a SQL query. | A SQL query was utilized in this study to eliminate all tweets that weren’t in English. | Distinguishing tweets in English from those in other languages was challenging. | Investigation into the independence of languages. | 2022 |
Rana et al.32 | Unsupervised method | To get user opinions, a lexicon of opinions is employed. | Required unlabelled training data. | The absence of alternative language resources and a common lexicon. | 2021 |
Ahmad and Wan33 | Create a detailed aspect-based Urdu sentiment analysis dataset. | This study developed an ABSA system involving various ML models. | Reliable baselines for ABSA in Urdu. | Research to a bilingual dataset | 2021 |
Ali Awan et al.25 | Classify multiclass sentence classification. | Applying the random forest technique to machine learning models. | The accuracy for the unigram, bigram, and trigram features was 80%, 76.88%, and 64.41%, respectively. | Grammatical, contextual, and lexical data. | 2021 |
Batra et al.29 | A large corpus is used on Urdu text classification. | Emojis are retrieved to verify machine learning. | The lack of data in a structured style. | Unavailable datasets. By compiling a sizable dataset. | 2021 |
Asghar et al.34 | The development of advanced SA applications. | Urdu terms get polarity scores; modifiers are tagged. | The paper’s assessment yields good results using polarity ratings, with baseline. | The publicly not available Urdu lexical resources. | 2019 |
Khan et al.35 | This paper provides a review of approaches that have been used in the past using Urdu sentimental analysis. | Lexicon Opinion Detecting opinion Resolving co-reference. | To identify gaps in previous results. | Most previous approaches gave better results. | 2018 |
Rehman and Bajwa19 | Identifying the polarity of a particular phrase or sentence in Urdu. | Pre-processing (initial phase). Sentence (polarity identification). | The lexicon-based approach’s results are satisfactory. | Lack of electronic information and vocabulary. | 2016 |
