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Machine learning algorithms for social media analysis: A survey
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Metadata
- Authors
- T.K., B., Annavarapu, C. S. R., & Bablani, A.
- Affiliations
- Indian Institute of Technology Dhanbad (IN)
- Indian Institute of Information Technology Sri City (IN)
- Corresponding author
- Annavarapu, Chandra Sekhara Rao
- Venue
- Computer Science Review
- Publisher
- Elsevier BV
- Published
- 2021-05
- Volume
- 40
- Pages
- 100395
- ISSN
- 1574-0137 (ISSN-L)
- OpenAlex
- W3136003884
- Cited by
- 276
- References
- 263
- Citations by year
- 2026: 14 · 2025: 70 · 2024: 82 · 2023: 69 · 2022: 35 · 2021: 6
- FWCI
- 16.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computer Science Review (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
- Keywords
- social media analytics, machine learning algorithms, social media data, big data processing, machine learning applications
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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