Paper Citation Record · LEDGER

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME

As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 2 inbound Pith citation observations for arXiv:2506.10154.

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

pith.paper-citation-record.v1
2506.10154 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:38:00.318431Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:19:42.515529Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T05:00:56.936183Z

Reference resolution

18 of 18 outbound references displayed

verified exact2
verified fuzzy12
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ae40619-c5b8-4455-b572-cc4fafaac4fe · outbound

This paper cites A hybrid model for automatic emotion recognition in suicide notes.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME A hybrid model for automatic emotion recognition in suicide notes

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.648255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 96796a89-e1df-4728-a4a4-eb6b03fc761e · outbound

This paper cites Automatic detection of insulting sentences in conversation.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Automatic detection of insulting sentences in conversation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.631772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c7e0a67c-5455-4108-ae05-2345742dcce2 · outbound

This paper cites Canceremo: A dataset for fine-grained emo- tion detection.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Canceremo: A dataset for fine-grained emo- tion detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.612984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 34d06ac0-411c-475b-839b-02c6e64f69da · outbound

This paper cites ProceedingsoftheFourth International Workshop on Semantic Evaluations (SemEval-2007).

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME ProceedingsoftheFourth International Workshop on Semantic Evaluations (SemEval-2007)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.596426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 63ec0ee8-d96f-4226-badc-f6cb46aa89b9 · outbound

This paper cites Semeval-2018 task 1: Affect in tweets.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Semeval-2018 task 1: Affect in tweets

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.581011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3bcf2d31-2154-4cb4-98c0-99e592dd5a1a · outbound

This paper cites GoEmotions: A Dataset of Fine-Grained Emotions.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME GoEmotions: A Dataset of Fine-Grained Emotions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:38:00.256846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0c5317f-c600-4598-83a3-6e76bda395a8 · outbound

This paper cites an unresolved cited work.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:38:00.565011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4952844e-c84e-41b4-a76f-1b86fe979f6a · outbound

This paper cites Emonoba: A dataset for analyzing fine-grained emotions on noisy bangla texts.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Emonoba: A dataset for analyzing fine-grained emotions on noisy bangla texts

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.549394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 59ac44df-f92a-4a48-b77c-e0571ea92f22 · outbound

This paper cites Comparison of Classical Machine Learning Approaches on Bangla Textual Emotion Analysis.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Comparison of Classical Machine Learning Approaches on Bangla Textual Emotion Analysis

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:38:00.421620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bdb23099-4e25-46ea-a41e-d813d455cc66 · outbound

This paper cites Long short-term memory.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Long short-term memory

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.533304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8a0e6d38-df84-4422-a6f6-3ece1250e156 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Neural Machine Translation by Jointly Learning to Align and Translate

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T04:38:00.283983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87184721-427c-4d0f-8915-4f1aa217be6c · outbound

This paper cites A study of fasttext word embedding effects in document classification in bangla language.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME A study of fasttext word embedding effects in document classification in bangla language

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.516179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0df2e913-621f-413a-b247-774d2906bba6 · outbound

This paper cites A survey of opinion mining and sentiment analysis.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME A survey of opinion mining and sentiment analysis

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.499881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ceb6d5db-ab28-4baf-b357-54aa51e56cac · outbound

This paper cites A comparative study Shah, Kanish, et al.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME A comparative study Shah, Kanish, et al

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.483493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dbdbce1d-7394-453f-986e-51a22f015afd · outbound

This paper cites News articles classification using random forests and weighted multimodal features.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME News articles classification using random forests and weighted multimodal features

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.467677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 328e325d-94e9-42f8-8614-852a84567bf5 · outbound

This paper cites Detecting ambiguities in requirements documents using inspections.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME Detecting ambiguities in requirements documents using inspections

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:38:00.453009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1cc7a677-b011-44d5-8117-6a05d489413d · outbound

This paper cites An Empirical Study of Gendered Stereotypes in Emotional Attributes for Bangla in Multilingual Large Language Models.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME An Empirical Study of Gendered Stereotypes in Emotional Attributes for Bangla in Multilingual Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T04:38:00.313492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6574976e-f5a8-49c3-abab-583b4554207c · outbound

This paper cites LowResource at BLP-2023 Task 2: Leveraging BanglaBert for Low Resource Sentiment Analysis of Bangla Language.

Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME LowResource at BLP-2023 Task 2: Leveraging BanglaBert for Low Resource Sentiment Analysis of Bangla Language

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:38:00.364539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation 6bc8a4c1-93b4-4d95-9fd0-3df42b77a077 · inbound

BIDWESH: A Bangla Regional Based Hate Speech Detection Dataset cites this paper.

BIDWESH: A Bangla Regional Based Hate Speech Detection Dataset Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T15:19:42.515529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76304703-929e-452c-9337-f4252a06b856 · inbound

MultiSoc-4D: A Benchmark for Diagnosing Instruction-Induced Label Collapse in Closed-Set LLM Annotation of Bengali Social Media cites this paper.

MultiSoc-4D: A Benchmark for Diagnosing Instruction-Induced Label Collapse in Closed-Set LLM Annotation of Bengali Social Media Analyzing Emotions in Bangla Social Media Comments Using Machine Learning and LIME

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:00:56.940144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.