Paper Citation Record · LEDGER

Exploration and Evaluation of Bias in Cyberbullying Detection with Machine Learning

As of 21 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 2026-08-21T06:32:19.484+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 2026-08-21T06:32:19.484+00:00.

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.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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

Resolution: 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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

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.

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 2026-08-21T06:32:19.484+00:00.

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 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.