Paper Citation Record · LEDGER

SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2307.10234.

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

pith.paper-citation-record.v1
2307.10234 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:55:56.387170Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:06:58.474660Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8e9a6634-bc02-4a4a-94ff-c1c1767f2d2e · inbound

Adaptable Embeddings Network (AEN) cites this paper.

Adaptable Embeddings Network (AEN) SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T15:57:59.235487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8460b31-5052-4bbd-b268-b62991791c14 · inbound

Topic Modeling and Sentiment Analysis on Japanese Online Media's Coverage of Nuclear Energy cites this paper.

Topic Modeling and Sentiment Analysis on Japanese Online Media's Coverage of Nuclear Energy SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T11:18:12.569814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 807e3375-4c8f-4235-bbbd-e7370e653481 · inbound

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics cites this paper.

Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographics SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T16:51:36.334629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e4b2211-ec9c-4259-968d-63f1dc8226d6 · inbound

SIExVulTS: Sensitive Information Exposure Vulnerability Detection System using Transformer Models and Static Analysis cites this paper.

SIExVulTS: Sensitive Information Exposure Vulnerability Detection System using Transformer Models and Static Analysis SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T16:55:56.387170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f70ecd49-a2b6-4943-a7ee-fed77d8cfed5 · inbound

Recommendations for Efficient and Responsible LLM Adoption within Industrial Software Development cites this paper.

Recommendations for Efficient and Responsible LLM Adoption within Industrial Software Development SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:11:27.454715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6cf995c7-c907-4afd-a6e6-61b2795ce4ac · inbound

Quantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion Taxonomies cites this paper.

Quantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion Taxonomies SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:06:58.476421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.