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Research Article | Open Access |

Clustering Algorithms in Sentiment Analysis Techniques in Social Media – A Rapid Literature Review

Author 1: Vasile Daniel Pavaloaia
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 15, No. 3 · Published 2024 · Cited by 5

DOI: https://doi.org/10.14569/IJACSA.2024.0150314

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Abstract

Based on the high dynamic of Sentiment Analysis (SA) topic among the latest publication landscape, the current review attempts to fill a research gap. Consequently, the paper elaborates on the most recent body of literature to extract and analyze the papers that elaborate on the clustering algorithms applied on social media datasets for performing SA. The current rapid review attempts to answer the research questions by analyzing a pool of 46 articles published in between Dec 2020 – Dec 2023. The manuscripts were thoroughly selected from Scopus (Sco) and WebOf-Science (WoS) databases and, after filtering the initial pool of 164 articles, the final results (46) were extracted and read in full.

Keywords

Clustering algorithms K-means HAC DBSCAN sentiment analysis natural language processing techniques social media datasets Twitter/X

How to Cite this Article

Pavaloaia, V. D. (2024). Clustering Algorithms in Sentiment Analysis Techniques in Social Media – A Rapid Literature Review. International Journal of Advanced Computer Science and Applications, 15(3). https://doi.org/10.14569/IJACSA.2024.0150314

Pavaloaia, Vasile Daniel. "Clustering Algorithms in Sentiment Analysis Techniques in Social Media – A Rapid Literature Review." International Journal of Advanced Computer Science and Applications, vol. 15, no. 3, 2024, https://doi.org/10.14569/IJACSA.2024.0150314.

@article{Pavaloaia2024,
  title     = {Clustering Algorithms in Sentiment Analysis Techniques in Social Media – A Rapid Literature Review},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {3},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Vasile Daniel Pavaloaia},
  doi       = {10.14569/IJACSA.2024.0150314},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150314}
}

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