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Paper Citation Record · LEDGER

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories

As of 4 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2606.11476.

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

pith.paper-citation-record.v1
2606.11476 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T12:04:47.662819Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

38 of 38 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7a0ee445-39a6-491d-83c2-09477b6f96a5 · outbound

This paper cites an unresolved cited work.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Unresolved cited work

Reference 1

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:e94f34148cb5e7a99fb38ba13c94ed43ef6d4fa3b955c135fd9ce770a4da03f4

Observation 2da6e53a-4c74-4b55-8bde-6d48acac2075 · outbound

This paper cites Available: https://docs.github.com/en/issues/tracking- your-work-with-issues/learning-about-issues/about-issues.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Available: https://docs.github.com/en/issues/tracking- your-work-with-issues/learning-about-issues/about-issues

Reference 2

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:af7975aeb499cacd1876af48f965dd687aa7ed7cba257e93808a6ad64e328857

Observation 9979892d-d42b-4665-b08d-020d8b0c7692 · outbound

This paper cites an unresolved cited work.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Unresolved cited work

Reference 3

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:640ab13bccb82ed71a3bf65eee89b6cee863692c1b549819e0cee9d4a0602ebb

Observation ad5793f7-77e6-4cb3-bc19-13017feb73d8 · outbound

This paper cites Opinion mining and sentiment analysis,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Opinion mining and sentiment analysis,

Reference 4

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:8ba5b70ab53b04617624f34a178cfbf24b0041fcb667e6f45b9a4f14b711fb85

Observation 9e5916fa-1140-45dc-9716-fd06cdc58ba5 · outbound

This paper cites Liu,Sentiment Analysis and Opinion Mining, ser.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Liu,Sentiment Analysis and Opinion Mining, ser

Reference 5

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:3ccf6b4d53e1fcb4772a0a669b6ffbae8cd0711cb4c2304f6ec37e09abf14135

Observation 4e9ebfdd-0471-42e7-b3ce-c11d6ea8134e · outbound

This paper cites Sentiment analysis in monitoring software development processes: An exploratory case study on GitHub’s project issues,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Sentiment analysis in monitoring software development processes: An exploratory case study on GitHub’s project issues,

Reference 6

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:943e2dc0e05357b5de7a6402dc6e5b40c48a7b07ac92d12a0287f26562b87c74

Observation 72a59234-9dc2-493c-a798-c52971a3a1ea · outbound

This paper cites Sentiment analysis of commit comments in GitHub: An empirical study,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Sentiment analysis of commit comments in GitHub: An empirical study,

Reference 7

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:81e4c7dd857a72752886b54a2281e18a1758f9ad1ff5a4d9993fd31391d38d24

Observation 721d1edf-d211-4b41-be9c-40c0e60ede60 · outbound

This paper cites Security and emotion: Sentiment analysis of security discussions on GitHub,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Security and emotion: Sentiment analysis of security discussions on GitHub,

Reference 8

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:1f1c9d1cae3f842336eead60dd0c7d63e05f8935a53edffa5d432ecdc52946f3

Observation ffdfee7d-03b5-480f-ad4f-952b8187206b · outbound

This paper cites Are bullies more productive? empirical study of affective- ness vs. issue fixing time,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Are bullies more productive? empirical study of affective- ness vs. issue fixing time,

Reference 9

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:993bd14ce63eb56bfecba2d99ecfbf09a37e02dbcbd3a37774e3968c25a51413

Observation 27702d24-dc93-4c77-94f7-46f6e8b6c101 · outbound

This paper cites The emotional side of software developers in JIRA,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories The emotional side of software developers in JIRA,

Reference 10

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:f8a93a8e4514fbf4a76f634cfdf81c4757cdd9f8845b024d819dca2eeed4762c

Observation f2ebf11c-0a99-418b-a94a-b721fc948e5d · outbound

This paper cites SentiStrength-SE: Exploiting domain specificity for improved sentiment analysis in software engineering text,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories SentiStrength-SE: Exploiting domain specificity for improved sentiment analysis in software engineering text,

Reference 11

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:a54aebe9f3348eff862086234e003f4370ee01414f95d0b431657f72aaa5352d

Observation c10502af-358c-404e-b030-0eec0d47f8de · outbound

This paper cites Sentiment polarity detection for software development,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Sentiment polarity detection for software development,

Reference 12

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:bc328568a03a17bf99632d7016a8dcd556de81ab62a05aff1412a3e41a5a3eb5

Observation bb56cb2d-6a0a-4d0a-95d2-82cb28775578 · outbound

This paper cites SentiCR: A customized sentiment analysis tool for code review interactions,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories SentiCR: A customized sentiment analysis tool for code review interactions,

Reference 13

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:495547501066d985c5846f32f6a2d92e993ce5a2be2e5af81869ab72cbc848c2

Observation 72842b97-ae88-4469-8062-9d636011d1b8 · outbound

This paper cites On negative results when using sentiment analysis tools for software engineering research,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories On negative results when using sentiment analysis tools for software engineering research,

Reference 14

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:99d1eca0f27698782c285a5abaa95237f85879d6150a01e8d5d524ba33e1b265

Observation 02e082bc-49dd-4c71-a6ed-f6f6b2e2f54d · outbound

This paper cites Assessment of off-the-shelf SE-specific sentiment analysis tools: An extended repli- cation study,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Assessment of off-the-shelf SE-specific sentiment analysis tools: An extended repli- cation study,

Reference 15

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:ba2763c8f1261d72c2ab2809df01442e151e0cac415a7a4464c8a63bd731b1bd

Observation 41e4ae81-cefb-4dfa-81d0-b98431ed9f6f · outbound

This paper cites Sentiment analysis tools in software engineering: A systematic mapping study,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Sentiment analysis tools in software engineering: A systematic mapping study,

Reference 16

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:011ec152a35b22a78287c9414b96271ebe8fa3243d088c92caf10de359c713af

Observation 36280a85-c74f-4a62-af37-6c59c2698236 · outbound

This paper cites “looks good to me ;-).

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories “looks good to me ;-)

Reference 17

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:b44a1ff51ee497035425fa35af63674aaab437773c971091e2f3b5e322e9c1a3

Observation 06bd649a-7e87-47ba-8c81-4897d3650bdf · outbound

This paper cites Impact of data quality for automatic issue classification using pre-trained language models,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Impact of data quality for automatic issue classification using pre-trained language models,

Reference 18

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:65d676f2538fb9796943f546bc51865450f869ad81fd672aee8dc807192a683e

Observation ac85a270-c5a2-4325-97d1-486b6aaed01e · outbound

This paper cites Detecting non-natural language artifacts for de- noising bug reports,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Detecting non-natural language artifacts for de- noising bug reports,

Reference 19

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:c17da8098b3a139c542ab2e9bd592e26b6d597485831284de81105d345fd43f0

Observation f614d8ac-5bc8-4c0c-a060-f608f0a217e6 · outbound

This paper cites Solving the problem of cas- cading errors: Approximate bayesian inference for linguistic annotation pipelines,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Solving the problem of cas- cading errors: Approximate bayesian inference for linguistic annotation pipelines,

Reference 20

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:c99d2c0a1939759b00ed1fc36d42349458ec2d065d17c71005a4691d59b5f33c

Observation d968c0ff-988c-4c35-973d-49e04eaa647b · outbound

This paper cites When it’s all piling up: Inves- tigating error propagation in an NLP pipeline,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories When it’s all piling up: Inves- tigating error propagation in an NLP pipeline,

Reference 21

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:b5340c85129d325e6716fae5456f513e42467b17da202c5be87a727fb5d665b8

Observation 561505dc-ba77-4b5f-b6a2-c00fd9051aca · outbound

This paper cites ROUGE: A package for automatic evaluation of summaries,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories ROUGE: A package for automatic evaluation of summaries,

Reference 22

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:2ef919ac59b2cb2e89b19ba476bb2827a0088a64e3cd83713b3860de676cbcac

Observation 25dc7821-0095-4903-84ab-082a0d1c2954 · outbound

This paper cites Evaluating the factual consistency of abstractive text summarization,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Evaluating the factual consistency of abstractive text summarization,

Reference 23

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:92f8747e99bc888bb41692215619b3e68b55b5c084580374a8aa85339a733ffa

Observation 7c84f405-a047-4863-beb4-8cb85609d8a1 · outbound

This paper cites SEAHORSE: A multilingual, multifaceted dataset for summarization evaluation,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories SEAHORSE: A multilingual, multifaceted dataset for summarization evaluation,

Reference 24

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:ca9726fc9c9489aa3a1c996ce174a3c146fbf6857e6d8afde3aabaaefed24a54

Observation 522b786c-470b-4847-a13f-321d8a39d76e · outbound

This paper cites GPTScore: Evaluate as You Desire.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories GPTScore: Evaluate as You Desire

Reference 25

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local_arxiv, observed 2026-07-03T07:27:44.969842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:646e0d6a649b313059f75bcd3bdc8c38b711a1a860ff94c1a86660f69775d358

Observation 89ff1393-ac99-432d-b2ca-a7d437994a9a · outbound

This paper cites SemEval 2017 task 10: ScienceIE – extracting keyphrases and relations from scientific publications,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories SemEval 2017 task 10: ScienceIE – extracting keyphrases and relations from scientific publications,

Reference 26

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:d8ce8ff57b40c69b8dfb59b04f8d907fed0e83aae6b2dd9bb62cc18a1e7d0eef

Observation 80696b98-06d5-4793-be79-aada792ad376 · outbound

This paper cites What are developers talking about? an analysis of topics and trends in Stack Overflow,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories What are developers talking about? an analysis of topics and trends in Stack Overflow,

Reference 27

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:d46673dfd1298890e32832f2b18fe9f448500e56ceebea88e8b1440363aa4d3b

Observation 9ce99c75-37d4-46a2-9f9e-b84f3dca1c82 · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 28

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local_arxiv, observed 2026-07-03T07:27:44.977020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:4c3e6b11aba20631da2eff95692b882a0a01ca3ac50a872726256def2e5a09da

Observation 5cbdfe1b-86e9-4133-bc9c-ddbea052d882 · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 29

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verified exact
local_arxiv, observed 2026-07-03T07:27:44.979284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:f19fd89baa05361543d587619181b9103db840b5be5e53a8e77f836cd75f71ba

Observation 2dff5b12-22f5-47f4-84d9-50bb7f285808 · outbound

This paper cites Density-based clustering based on hierarchical density estimates,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Density-based clustering based on hierarchical density estimates,

Reference 30

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:16c5eedcdd942fe5a9ec09f7e3acc48b0f7d9daeb82026d3f8c2b55100c2ec7d

Observation 147a8abf-21a5-47c2-9e5d-eb49ce4db1ff · outbound

This paper cites Density-based clustering validation,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Density-based clustering validation,

Reference 31

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:7166886fe3d20ba8dec27ff1c11ea5cb24f94377e890696623e831acd14aca39

Observation 6cf22d94-be73-4c98-9e79-174b78f08291 · outbound

This paper cites A combination of opinion mining and social network techniques for discussion analysis,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories A combination of opinion mining and social network techniques for discussion analysis,

Reference 32

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:d8abddaf6b2758c8a9cfdf6b55b2c272a1cb9ee62b53aead8eb342fae28e737b

Observation e2c8d8d7-a0cf-40e7-acec-a7a426b2f35a · outbound

This paper cites Leveraging large language models to identify conversation threads in collaborative learning,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Leveraging large language models to identify conversation threads in collaborative learning,

Reference 33

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arxiv_id, observed 2026-07-03T07:27:44.974895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:1ad0214d3a641bab3e881298793b1dea9e45158a47e2c6213819adf76f23c43d

Observation 93e55efc-b34f-4a59-9116-5a4290cbd2ba · outbound

This paper cites Large language models for software engineering: Sur- vey and open problems,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Large language models for software engineering: Sur- vey and open problems,

Reference 34

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:547cd4dcf98281fa46167d6c0649061914f707c5763ce8ea64c24208bc5f25f4

Observation 8c76161e-ce87-4cef-8ec6-db3532a20f7f · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Retrieval-augmented generation for knowledge-intensive NLP tasks,

Reference 35

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:b67dedabb4ce13ec098169f676d99e4a1dbd963a01a10b1ba260944f4d8e4501

Observation 36efb516-e087-4a3d-af49-6b1ff4c2b4f8 · outbound

This paper cites Unveiling the potential of a conversational agent in developer support: Insights from mozilla’s PDF.js project,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories Unveiling the potential of a conversational agent in developer support: Insights from mozilla’s PDF.js project,

Reference 36

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source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:e0b72e52b02fcbb7302c8632d61ce2fb0b415cb48a5fdedda24423efb997ce90

Observation bacf9577-47e7-4d09-883b-8a072c6ede4d · outbound

This paper cites A comparison of conversational models and humans in answering technical questions: The Firefox case,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories A comparison of conversational models and humans in answering technical questions: The Firefox case,

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-07-03T07:27:44.972491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:a83f368a52d742846e22cce72cdffb014f0d14736a83ba7a3808c32b2c6ae620

Observation 17f990f2-9b1a-4515-afbf-34f3ab7d83f3 · outbound

This paper cites V ADER: A parsimonious rule-based model for sentiment analysis of social media text,.

SentTrack: Sentiment-Driven Bottleneck Detection in GitHub Issue Repositories V ADER: A parsimonious rule-based model for sentiment analysis of social media text,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-06-27T12:04:47.662819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-27T12:04:47.662819Z digest=sha256:eeb5bf0fe416f7f370fd129f65c4baab2a1560679db2583a2d195dd763b9bb6d

Pith citing papers

No inbound Pith citation observations are available.