The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
A Study on Sentiment Analysis Techniques of Twitter Data
Open accessAbstract
The entire world is transforming quickly under the present innovations. The Internet has become a basic requirement for everybody with the Web being utilized in every field. With the rapid increase in social network applications, people are using these platforms to voice them their opinions with regard to daily issues. Gathering and analyzing peoples’ reactions toward buying a product, public services, and so on are vital. Sentiment analysis (or opinion mining) is a common dialogue preparing task that aims to discover the sentiments behind opinions in texts on varying subjects. In recent years, researchers in the field of sentiment analysis have been concerned with analyzing opinions on different topics such as movies, commercial products, and daily societal issues. Twitter is an enormously popular microblog on which clients may voice their opinions. Opinion investigation of Twitter data is a field that has been given much attention over the last decade and involves dissecting “tweets” (comments) and the content of these expressions. As such, this paper explores the various sentiment analysis applied to Twitter data and their outcomes.
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Cites
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Thumbs up? Sentiment Classification using Machine Learning Techniques
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Cited by
Stock Market Increase and Decrease using Twitter Sentiment Analysis and ARIMA Model
Kedar, S. V. (2021) · Turkish Journal of Computer and Mathematics Education (TURCOMAT) · doi:10.17762/turcomat.v12i1s.1596 · Cited by 10
Metadata
- Authors
- Alsaeedi, A., & Zubair, M.
- Venue
- International Journal of Advanced Computer Science and Applications
- Published
- 2019
- Volume
- 10
- Issue
- 2
- ISSN
- 2156-5570 (ISSN-L)
- 2158-107X
- OpenAlex
- W2920568733
- Cited by
- 282
- References
- 38
- FWCI
- 15.08
- Type
- journal article
- Language
- en
- Open access
- diamond
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