Cited by 81Hate Speech and Cyberbullying DetectionSentiment Analysis and Opinion MiningText and Document Classification Technologies

Towards Cyberbullying-free social media in smart cities: a unified multi-modal approach

Kumari, Kirti, Singh, Jyoti Prakash, Dwivedi, Yogesh Kumar, Rana, Nripendra Pratap·2020·Soft Computing

Integrity signals

Registry

Crossref · 10.1007/s00500-019-04550-x

Cites

38 of 38 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Kumari et al. utilized OCR to extract text from images to classify cyberbullying in image data.

    “Kumari et al. [87] utilized OCR to extract text from the images to classify cyberbullying in image data.”

    From A Review on Deep-Learning-Based Cyberbullying Detection (2023) · cites this paper as [87]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Kumari, K., Singh, J. P., Dwivedi, Y. K., & Rana, N. P.
Affiliations
  • National Institute of Technology Patna (IN)
  • Swansea University (GB)
  • University of Bradford (GB)
Corresponding author
Kumari, Kirti
Venue
Soft Computing
Published
2019-11-27
Volume
24
Issue
15
Pages
11059-11070
ISSN
  • 1432-7643 (ISSN-L)
  • 1433-7479
OpenAlex
W2990156638
Cited by
81
References
38
Citations by year
2026: 6 · 2025: 10 · 2024: 12 · 2023: 14 · 2022: 16 · 2021: 16 · 2020: 7
FWCI
4.50
Type
journal article
Language
en
Open access
closed
Locations
  • Soft Computing (publishedVersion)
  • Bradford Scholars (University of Bradford) (submittedVersion)
Funders
Ministry of Electronics and Information technology
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Physical Sciences › Computer Science › Artificial Intelligence › Text and Document Classification Technologies
Keywords
cyberbullying detection, social media, smart cities, multimodal representation, text and image fusion, convolutional neural networks, hate speech

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 ›

Are you an author, or do you see a problem with this page? Request a review