The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Social media sentiment analysis based on COVID-19
Open accessAbstract
In today's world, the social media is everywhere, and everybody come in contact with it every day. With social media datas, we are able to do a lot of analysis and statistics nowdays. Within this scope of article, we conclude and analyse the sentiments and manifestations (comments, hastags, posts, tweets) of the users of the Twitter social media platform, based on the main trends (by keyword, which is mostly the ‘covid’ and coronavirus theme in this article) with Natural Language Processing and with Sentiment Classification using Recurrent Neural Network. Where we analyse, compile, visualize statistics, and summarize for further processing. The trained model works much more accurately, with a smaller margin of error, in determining emotional polarity in today's ‘modern’ often with ambiguous tweets. Especially with RNN. We use this fresh scraped data collections (by the keyword's theme) with our RNN model what we have created and trained to determine what emotional manifestations occurred on a given topic in a given time interval.
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Cites
Recurrent neural network based language model
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Jianqiang, Z., Xiaolin, G., & Xuejun, Z. (2018) · IEEE Access · doi:10.1109/access.2017.2776930 · Cited by 482
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Cited by
Machine Learning Methods for Small Data Challenges in Molecular Science
Dou, B., Zhu, Z., Merkurjev, E., Ke, L., Chen, L., Jiang, J., Zhu, Y., Liu, J., Zhang, B., & Wei, G.-W. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.3c00189 · Cited by 499
COVID-19 Tweets Classification Based on a Hybrid Word Embedding Method
Didi, Y., Walha, A., & Wali, A. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6020058 · Cited by 38
Metadata
- Authors
- Nemes, L., & Kiss, A.
- Venue
- Journal of Information and Telecommunication
- Publisher
- Informa UK Limited
- Published
- 2020-07-14
- Volume
- 5
- Issue
- 1
- Pages
- 1-15
- ISSN
- 2475-1839 (ISSN-L)
- 2475-1847
- OpenAlex
- W3043013845
- Cited by
- 268
- References
- 14
- FWCI
- 16.86
- Type
- journal article
- Language
- en
- Open access
- gold
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