The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Machine Learning-Based Sentiment Analysis for Twitter Accounts
Open accessAbstract
Growth in the area of opinion mining and sentiment analysis has been rapid and aims to explore the opinions or text present on different platforms of social media through machine-learning techniques with sentiment, subjectivity analysis or polarity calculations. Despite the use of various machine-learning techniques and tools for sentiment analysis during elections, there is a dire need for a state-of-the-art approach. To deal with these challenges, the contribution of this paper includes the adoption of a hybrid approach that involves a sentiment analyzer that includes machine learning. Moreover, this paper also provides a comparison of techniques of sentiment analysis in the analysis of political views by applying supervised machine-learning algorithms such as Naïve Bayes and support vector machines (SVM).
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Cites
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MethodAn algorithm for suffix stripping
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Cited by
Multimodal Sentiment Analysis: A Survey of Methods, Trends, and Challenges
Das, R., & Singh, T. D. (2023) · ACM Computing Surveys · doi:10.1145/3586075 · Cited by 363
Metadata
- Authors
- Hasan, A., Moin, S., Karim, A., & Shamshirband, S.
- Venue
- Mathematical and Computational Applications
- Publisher
- MDPI AG
- Published
- 2018-02-27
- Volume
- 23
- Issue
- 1
- Pages
- 11
- ISSN
- 1300-686X (ISSN-L)
- 2297-8747
- OpenAlex
- W2792883466
- Cited by
- 447
- References
- 37
- FWCI
- 27.30
- Type
- journal article
- Language
- en
- Open access
- gold
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