Paper Citation Record · LEDGER

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches

As of 22 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2608.12007.

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

pith.paper-citation-record.v1
2608.12007 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:23:02.581909Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

24 of 24 outbound references displayed

verified exact8
verified fuzzy5
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38511969-3786-4072-a207-d6b6218caf57 · outbound

This paper cites Artificial Intelligence and Consumer Financial Behavior: A Systematic Literature Review and Agenda for Future Research,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Artificial Intelligence and Consumer Financial Behavior: A Systematic Literature Review and Agenda for Future Research,

Reference 1

Resolution: verified exact; doi, observed 2026-08-16T00:23:02.820517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c7c35835-70e0-4ccf-a5c6-de08cda8728f · outbound

This paper cites Ivanov, A.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Ivanov, A

Reference 2

Resolution: verified exact; doi, observed 2026-08-16T00:23:02.808347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7598adbc-ea3f-4475-b00a-e988afc71bb2 · outbound

This paper cites Sentiment Analysis of Pr oduct Reviews Using Machine Learning and Pre -Trained LLM,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Sentiment Analysis of Pr oduct Reviews Using Machine Learning and Pre -Trained LLM,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.504934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b37bcad-52c9-4ca0-8892-5dfd9026ed19 · outbound

This paper cites Optimizing Sentiment Analysis on Imbalanced Hotel Review Data Using SMOTE and Ensemble Machine Learning Techniques,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Optimizing Sentiment Analysis on Imbalanced Hotel Review Data Using SMOTE and Ensemble Machine Learning Techniques,

Reference 4

Resolution: verified exact; doi, observed 2026-08-16T00:23:02.789714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7c766f68-108b-478f-9d6d-9b73989ca4aa · outbound

This paper cites Using machine learning to develop customer insights from user-generated content,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Using machine learning to develop customer insights from user-generated content,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.512530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c9ff6fa-cffb-4b71-b7ab-abb1aaec945b · outbound

This paper cites SenticNet 6: Ensemble Application of Symbolic and Subsymbolic AI for Sentiment Analysis,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches SenticNet 6: Ensemble Application of Symbolic and Subsymbolic AI for Sentiment Analysis,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.516210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e1e9452-0986-400b-a9a7-1d5fbb2f36a6 · outbound

This paper cites Sentiment Analysis for Customer Behavior Insights: A Natural Language Processing Approach to Business Decision-Making,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Sentiment Analysis for Customer Behavior Insights: A Natural Language Processing Approach to Business Decision-Making,

Reference 7

Resolution: verified exact; doi, observed 2026-08-16T00:23:02.778110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a6e28305-0085-4d3e-80c8-801ea21258c8 · outbound

This paper cites A systematic study of the class imbalance problem in convolutional neural networks,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches A systematic study of the class imbalance problem in convolutional neural networks,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.523593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 882e2ace-b5a6-459b-9a6f-10c2ab9969ef · outbound

This paper cites Magnets for Sarcasm: Making Sarcasm Detection Timely, Contextual and Very Personal,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Magnets for Sarcasm: Making Sarcasm Detection Timely, Contextual and Very Personal,

Reference 9

Resolution: verified exact; doi, observed 2026-08-16T00:23:02.759006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2be6437b-d154-4a5f-a145-e216b8d1a3e0 · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.530931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5f4ec87-25f9-4bf8-9fd5-0e79139cdf42 · outbound

This paper cites Sentiment Analysis using various Machine Learning and Deep Learning Techniques,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Sentiment Analysis using various Machine Learning and Deep Learning Techniques,

Reference 11

Resolution: verified exact; doi, observed 2026-08-16T00:23:02.740189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0f60cd4b-a566-4708-8309-a0754d2c77c8 · outbound

This paper cites Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:23:03.263991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 21022571-464d-4a0c-b343-d287596a0200 · outbound

This paper cites Thumbs up? Sentiment Classification using Machine Learning Techniques,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Thumbs up? Sentiment Classification using Machine Learning Techniques,

Reference 14

Resolution: verified exact; doi, observed 2026-08-16T00:23:02.716987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0050fa71-b984-4ac0-a55a-3438fc593d9f · outbound

This paper cites Deep Learning for Sentiment Analysis : A Survey.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Deep Learning for Sentiment Analysis : A Survey

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.546037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61081998-0c24-496b-978f-ec35c7843069 · outbound

This paper cites Convolutional Neural Networks for Sentence Classification.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Convolutional Neural Networks for Sentence Classification

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.549003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54911717-8647-4b72-8800-a5a4aa20971a · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.552362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2836ad1-8b80-4a57-9a3b-ad7d75cf1353 · outbound

This paper cites Sentiment Analysis of IMDB Movie Reviews.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Sentiment Analysis of IMDB Movie Reviews

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:23:03.252603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0d717ddd-1c85-4221-9441-3d1354786115 · outbound

This paper cites Sentiment Analysis on the Yelp Reviews Dataset.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Sentiment Analysis on the Yelp Reviews Dataset

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:23:03.241252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 88c7a867-4fba-4801-9407-2884a0236961 · outbound

This paper cites A Deep Text Mining-Based Cosmetics Consumer Sentiment Analysis Model,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches A Deep Text Mining-Based Cosmetics Consumer Sentiment Analysis Model,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.561717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64a51389-edbf-457a-b191-9afd7d0107c9 · outbound

This paper cites Social Media Sentiment Analysis for Airline Customer Satisfaction,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Social Media Sentiment Analysis for Airline Customer Satisfaction,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.568498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abb14692-61cf-492d-95bd-367ffebaa1b0 · outbound

This paper cites Improvising E-Commerce Sentiment Analysis with Hybrid VADER-BERT Ensemble Model,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Improvising E-Commerce Sentiment Analysis with Hybrid VADER-BERT Ensemble Model,

Reference 23

Resolution: verified exact; raw_fallback, observed 2026-08-16T00:23:02.979499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 41bf5fb4-89f2-4038-9eab-ec85b310de6f · outbound

This paper cites Sentiment Analysis of P2P Lending Fintech Service User Comments Using CNN-ROS-NCL on Imbalanced Data,.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Sentiment Analysis of P2P Lending Fintech Service User Comments Using CNN-ROS-NCL on Imbalanced Data,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T00:23:02.575007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b01da8f-fe6e-447e-943c-56b5946d1109 · outbound

This paper cites Starbucks Reviews Dataset.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Starbucks Reviews Dataset

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:23:03.231241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 865f880c-918a-4d84-bfc5-6d1696fffa21 · outbound

This paper cites Available: https://www.kaggle.com/datasets/harshalhonde/starbuck s-reviews-dataset.

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches Available: https://www.kaggle.com/datasets/harshalhonde/starbuck s-reviews-dataset

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:23:03.220200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.