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Paper Citation Record · LEDGER

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning

As of 18 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2412.00609.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.00609 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:13:24.290895Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

  • verified exact5
  • verified fuzzy9
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c78c29f8-fde4-48c4-a612-3dbbb1a9f03f · outbound

This paper cites When the timeline meets the pipeline: A survey on automated cyberbullying detection,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning When the timeline meets the pipeline: A survey on automated cyberbullying detection,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.592249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5308a49d-b788-48c1-a118-2301b95b7f94 · outbound

This paper cites Automated Hate Speech Detection and the Problem of Offensive Language.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Automated Hate Speech Detection and the Problem of Offensive Language

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T05:13:23.747424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:13:23.747424Z digest=sha256:d4a1ab93f027085121e7911eea483188258626d3aed2e0dac68d98c5146388dc

Observation d15ac518-62f9-4338-b0fa-1f4dd6c9964f · outbound

This paper cites Sosnet: A graph convolutional network approach to fine-grained cyberbullying detection,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Sosnet: A graph convolutional network approach to fine-grained cyberbullying detection,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.574458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:23.814635Z digest=sha256:153d8573cf892e20bd8bad94c1cb3121d358bf85bee5acc51cfca7bd77f83102

Observation c0e68c63-93d9-44dd-ac83-ee6526cb2edc · outbound

This paper cites ID-XCB: Data-independent Debiasing for Fair and Accurate Transformer-based Cyberbullying Detection.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning ID-XCB: Data-independent Debiasing for Fair and Accurate Transformer-based Cyberbullying Detection

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:13:24.913276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:23.880768Z digest=sha256:d99fa52a4a1f0e939ff102f80b14f56d3c44e882896734be72be7b51b896f283

Observation 924bb364-9719-4494-a599-e44269f4b5da · outbound

This paper cites Accurate cyberbullying detection and prevention on social media,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Accurate cyberbullying detection and prevention on social media,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.546585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:23.967133Z digest=sha256:b674caf096471490291d2971bf97d0b7078fa22c1ef32810eaad2d43856cf040

Observation eb04060a-ddb6-46db-aabe-9feb75850fd8 · outbound

This paper cites Investigating the role of swear words in abusive language detection tasks,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Investigating the role of swear words in abusive language detection tasks,

Reference 6

Resolution
verified exact
doi, observed 2026-08-12T05:13:24.449003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.047676Z digest=sha256:b49c37fdac65a9b24c06fb2a37d740585ce77f7c7f52bc5f8e983f78bed67038

Observation 496bc17b-309e-43be-9144-ef6213b9ff31 · outbound

This paper cites Using machine learning to detect cyberbullying,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Using machine learning to detect cyberbullying,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.396268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.074531Z digest=sha256:0493973c1a272ff6df32b830da7174b4b7d3079066fa59f30655adbc70bdb9b1

Observation db3fed88-f0a7-4181-b5a3-5f4360bc9271 · outbound

This paper cites The development of a serious game on cyberbullying: A concept test,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning The development of a serious game on cyberbullying: A concept test,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.338015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.097447Z digest=sha256:2c6574aef5d733ed6c1cc8261e0fb620f5c0b70226745dab055c6b6920ab8f6d

Observation e9cfdf8d-a1cf-43c2-8231-9963f5608c9a · outbound

This paper cites Mean Birds: Detecting Aggression and Bullying on Twitter.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Mean Birds: Detecting Aggression and Bullying on Twitter

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:13:24.878253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.122045Z digest=sha256:edd3bb57fdc9b1bcef6b51f2d6c26dd7989976e494137cbf8d4a162e09f35f8d

Observation c0c916c7-fbd1-45ea-a332-bb6f6b4fcad0 · outbound

This paper cites A large labeled corpus for online harassment research,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning A large labeled corpus for online harassment research,

Reference 10

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unresolved
no resolver link, observed 2026-08-12T05:13:24.143707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:13:24.143707Z digest=sha256:60be79e8e0a5dd5fbd24c0986a05f91db627557ca01709d59a975746b0a2ce55

Observation 9bf0b461-2309-43e4-8f30-bb220248c39e · outbound

This paper cites Identification of hate speech in social media,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Identification of hate speech in social media,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.320045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.156823Z digest=sha256:876a00106f34faef811bb6f16183619200f4b14f6a4d4c3979a07f7a6cbccbb7

Observation 6fdc7c4a-0f1a-408f-897d-bbb4aab7ca96 · outbound

This paper cites Hateful symbols or hateful people? predictive features for hate speech detection on Twitter,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Hateful symbols or hateful people? predictive features for hate speech detection on Twitter,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.266684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.166362Z digest=sha256:b2cff43ba7b9bbb04be03d81090aa669ebc07c659dbb43bc98e712a17fb008d0

Observation 9ba47a21-1314-4535-a695-50a38f5fa638 · outbound

This paper cites Analysing Cyberbullying using Natural Language Processing by Understanding Jargon in Social Media.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Analysing Cyberbullying using Natural Language Processing by Understanding Jargon in Social Media

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:13:24.579913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.178958Z digest=sha256:98edce86f0bf564673ba63767b160fb54a4b1d0a84f2e18631e867199fddcf62

Observation b82245ea-34ac-40b4-8480-3012f2137bd1 · outbound

This paper cites Effective hate-speech detection in twitter data using recurrent neural networks,.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Effective hate-speech detection in twitter data using recurrent neural networks,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.109414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.188457Z digest=sha256:d4ecb6a8d1f9fe9c84fc816685acf6ddc76842afb070f72b5154290642ad3f9c

Observation b9a6d56e-f1da-4a38-af84-c42b2e614bf7 · outbound

This paper cites an unresolved cited work.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:13:24.950575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.194714Z digest=sha256:6fb2e1235e0b1ef538c62f12147de8d06be0c8e68d767b00b8ad2b6b43cc1756

Observation ef6832b8-7334-4654-bb75-50ba5040a9bd · outbound

This paper cites What the F-measure doesn't measure: Features, Flaws, Fallacies and Fixes.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning What the F-measure doesn't measure: Features, Flaws, Fallacies and Fixes

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T05:13:24.199605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:13:24.199605Z digest=sha256:0f79905b3e40569db2f34470d1c1b3a4f288d46477515c109981e10d7c077cdb

Observation 93ac3191-3cda-427a-a1b1-b6db4a0c3724 · outbound

This paper cites Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-12T05:13:24.491653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T05:13:24.290895Z digest=sha256:fdbbc94d92fba9dddf43a8c3dbeee6f6894f5e1ae3b45d78413da5689bcfeade

Observation 59143d5b-13a6-4c64-8cf5-bbb11f940b23 · outbound

This paper cites Available: https://www.sciencedirect.com/science/article/pii/S1877050921002507.

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning Available: https://www.sciencedirect.com/science/article/pii/S1877050921002507

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:13:25.498913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Pith citing papers

No inbound Pith citation observations are available.