Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T20:47:09.950116Z
Paper Citation Record · LEDGER
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach
As of 9 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2508.09935.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
70 of 70 outbound references displayed
- verified exact0
- verified fuzzy64
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 86e3ab1a-4e70-4919-81a3-1accd1456fc6 · outbound
This paper cites A statistical language modeling approach to online deception detection.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach A statistical language modeling approach to online deception detection
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.284283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 72e5ee06-4825-4f07-b9ef-c8491a84df25 · outbound
This paper cites Park, Simon Goldstein, Aidan O’Gara, Michael Chen, and Dan Hendrycks.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Park, Simon Goldstein, Aidan O’Gara, Michael Chen, and Dan Hendrycks
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.268920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8827cc02-465e-45d5-825e-cebc7bebae28 · outbound
This paper cites Textual analysis in accounting: What's next? Contemporary Accounting Research , 40(2):765--805, 2023.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Textual analysis in accounting: What's next? Contemporary Accounting Research , 40(2):765--805, 2023
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.254328Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b0a67e1f-7587-47ff-8545-905af9dd8f1e · outbound
This paper cites Identification of fraudulent financial statements using linguistic credibility analysis.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Identification of fraudulent financial statements using linguistic credibility analysis
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.238931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f2bd3411-3e3f-40f9-aba9-62a814faae07 · outbound
This paper cites Enhancing environmental information transparency through corporate social responsibility reporting regulation.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Enhancing environmental information transparency through corporate social responsibility reporting regulation
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.223801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 45e15c99-1739-4db8-b1d7-81aa1a295c75 · outbound
This paper cites Mapping the greenwashing research landscape: A theoretical and field analysis.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Mapping the greenwashing research landscape: A theoretical and field analysis
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.208389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 76a49556-ed5e-4ce9-9f87-1b12e46f59cb · outbound
This paper cites Detecting and unmasking ai-generated texts through explainable artificial intelligence using stylistic features.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Detecting and unmasking ai-generated texts through explainable artificial intelligence using stylistic features
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.191290Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e6670bd4-d5a8-43c0-a303-3ddd06e61f0a · outbound
This paper cites Carillion's strategic choices and the boardroom's strategies of persuasive appeals: ethos, logos and pathos.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Carillion's strategic choices and the boardroom's strategies of persuasive appeals: ethos, logos and pathos
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.176306Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c92f3e95-5296-480a-a8f1-cb1ab5d97683 · outbound
This paper cites Walking the talk about corporate social responsibility communication: An elaboration likelihood model perspective.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Walking the talk about corporate social responsibility communication: An elaboration likelihood model perspective
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.161420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f010144e-a4f7-4f1f-aa66-2538586156ab · outbound
This paper cites Flusberg, Kevin J.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Flusberg, Kevin J
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.144643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 77570d87-3a7d-407b-bd46-f22ca42866c7 · outbound
This paper cites Sustainable finance as a contested concept: Tracing the evolution of five frames between 1998 and 2018.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Sustainable finance as a contested concept: Tracing the evolution of five frames between 1998 and 2018
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.129939Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0d2078c0-93cb-40e1-98d2-22c7058762b7 · outbound
This paper cites an unresolved cited work.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T20:47:13.113825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation caea9bd3-a4bd-4959-96bd-6affe22af93b · outbound
This paper cites Using metadiscourse to enhance persuasiveness in corporate press releases: A corpus-based study.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Using metadiscourse to enhance persuasiveness in corporate press releases: A corpus-based study
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.097966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 564696e3-390c-418d-bf79-7025793cf84e · outbound
This paper cites Anthropomorphization and beyond: conceptualizing humanwashing of ai-enabled machines.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Anthropomorphization and beyond: conceptualizing humanwashing of ai-enabled machines
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.083466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f23c13a0-ef06-4b65-a6ed-cadd4f23875b · outbound
This paper cites Voluntary disclosure of sustainable development goals in mandatory non-financial reports: The moderating role of cultural dimension.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Voluntary disclosure of sustainable development goals in mandatory non-financial reports: The moderating role of cultural dimension
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.067804Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d6dc8d50-3ede-4084-bba6-5cef73c3a0cd · outbound
This paper cites Makana Chock.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Makana Chock
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.053099Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 5dd7dde4-82f2-4bb4-8808-92aad81d772f · outbound
This paper cites Ethical and Legal Challenges of AI in Marketing : An Exploration of Solutions.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Ethical and Legal Challenges of AI in Marketing : An Exploration of Solutions
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.038748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6eca564a-7925-497b-a39b-32da9bda2b95 · outbound
This paper cites Finchain-bert: A high-accuracy automatic fraud detection model based on nlp methods for financial scenarios.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Finchain-bert: A high-accuracy automatic fraud detection model based on nlp methods for financial scenarios
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.024298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 4b10551b-c30a-479d-bb3c-81eae5a1884c · outbound
This paper cites How will ai text generation and processing impact sustainability reporting? critical analysis, a conceptual framework, and avenues for future research.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach How will ai text generation and processing impact sustainability reporting? critical analysis, a conceptual framework, and avenues for future research
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:13.009412Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 511983fd-6bb1-4c3d-9dce-d2721c972cf3 · outbound
This paper cites Corporate sustainability communication as ‘fake news’: Firms’ greenwashing on twitter.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Corporate sustainability communication as ‘fake news’: Firms’ greenwashing on twitter
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.994531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 54826020-57ed-4e6d-9650-af0339d9c525 · outbound
This paper cites Machine learning approaches for enhancing fraud prevention in financial transactions.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Machine learning approaches for enhancing fraud prevention in financial transactions
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.979496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 38f56e78-7355-4ee2-962e-a412fe6a4b4e · outbound
This paper cites Fake reviews classification using deep learning ensemble of shallow convolutions.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Fake reviews classification using deep learning ensemble of shallow convolutions
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.964630Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 4c3e987e-f9c4-4ca4-84a1-8db258a19dba · outbound
This paper cites Fraud detection in healthcare insurance claims using machine learning.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Fraud detection in healthcare insurance claims using machine learning
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.948359Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation bf9890d4-5033-42a6-9bad-2f50823751af · outbound
This paper cites Artificial intelligence in finance: A comprehensive review through bibliometric and content analysis.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Artificial intelligence in finance: A comprehensive review through bibliometric and content analysis
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.931684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e4755327-e738-4bdb-9ea1-3fd2b4d8b62a · outbound
This paper cites Anis, Reef M.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Anis, Reef M
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.912919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 1c5871f4-96da-4581-94f0-b94af01a26ae · outbound
This paper cites Attentive statement fraud detection: Distinguishing multimodal financial data with fine-grained attention.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Attentive statement fraud detection: Distinguishing multimodal financial data with fine-grained attention
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.895808Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d68e132e-dee4-462b-8cbf-fe9c9c275dbd · outbound
This paper cites A deep learning method for automatic sms spam classification: Performance of learning algorithms on indigenous dataset.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach A deep learning method for automatic sms spam classification: Performance of learning algorithms on indigenous dataset
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.880109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 96791c62-e37b-471a-bdc2-e708e564f83e · outbound
This paper cites Oswald, Sona Elza Simon, and Arnab Bhattacharya.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Oswald, Sona Elza Simon, and Arnab Bhattacharya
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.861585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0504028d-39d7-4440-bf86-be5062a2b829 · outbound
This paper cites Advancing fake news detection: Hybrid deep learning with fasttext and explainable ai.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Advancing fake news detection: Hybrid deep learning with fasttext and explainable ai
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.843766Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation fde71b42-2508-4701-b615-a8f224964262 · outbound
This paper cites Intelligent financial fraud detection practices in post-pandemic era.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Intelligent financial fraud detection practices in post-pandemic era
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.827661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b8e685a7-f797-43f0-9ee5-f363ff32b00a · outbound
This paper cites A bert based approach to measure web services policies compliance with gdpr.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach A bert based approach to measure web services policies compliance with gdpr
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.812343Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8e665175-499b-4e20-aca6-228546a56ac2 · outbound
This paper cites an unresolved cited work.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Unresolved cited work
Reference 32
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T20:47:12.797458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 09d2b6de-b50b-43d3-bff2-10965db69e72 · outbound
This paper cites Extracting financial data from unstructured sources: Leveraging large language models.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Extracting financial data from unstructured sources: Leveraging large language models
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.782783Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 98f998a7-c6c8-4183-b295-67b13d3c1bb4 · outbound
This paper cites Rethinking Legal Compliance Automation: Opportunities with Large Language Models.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Rethinking Legal Compliance Automation: Opportunities with Large Language Models
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:47:06.949283Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b05806cb-e852-4f3e-876f-156789f863b8 · outbound
This paper cites Sniffer: Multimodal large language model for explainable out-of-context misinformation detection.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Sniffer: Multimodal large language model for explainable out-of-context misinformation detection
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.766679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f1319454-64f2-4ec9-af74-097fcba2a391 · outbound
This paper cites DEAP-FAKED: Knowledge Graph based Approach for Fake News Detection.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach DEAP-FAKED: Knowledge Graph based Approach for Fake News Detection
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.751233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c3c597e9-eb6c-48fd-85e4-0d2c59fd1071 · outbound
This paper cites Fake review detection in e-commerce platforms using aspect-based sentiment analysis.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Fake review detection in e-commerce platforms using aspect-based sentiment analysis
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.734830Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation af71b265-3cf6-4647-9249-92ccbea44397 · outbound
This paper cites From opinion mining to financial argument mining.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach From opinion mining to financial argument mining
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.718987Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 810b5110-9bcd-4a19-b44d-0a98c7893c4e · outbound
This paper cites Analyzing and visualizing text information in corporate sustainability reports using natural language processing methods.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Analyzing and visualizing text information in corporate sustainability reports using natural language processing methods
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.703727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6b12dded-002a-4f2b-8208-ea9d92a9da4d · outbound
This paper cites Three gaps in computational text analysis methods for social sciences: A research agenda.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Three gaps in computational text analysis methods for social sciences: A research agenda
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.688276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 45f70beb-44fb-4129-b669-2fb1a4afdff3 · outbound
This paper cites Missing Counter-Evidence Renders NLP Fact-Checking Unrealistic for Misinformation.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Missing Counter-Evidence Renders NLP Fact-Checking Unrealistic for Misinformation
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:47:07.503621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30505afd-d4c5-4938-bc81-a10a26d4e453 · outbound
This paper cites Larcker and Anastasia A.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Larcker and Anastasia A
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.673773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation abea0f4a-e93a-4c13-8fb6-090769a61beb · outbound
This paper cites Exploring top management language for signals of possible deception: The words of satyam's chair ramalinga raju.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Exploring top management language for signals of possible deception: The words of satyam's chair ramalinga raju
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.659209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 14da315d-7ee4-44f9-89bc-2584fccce17c · outbound
This paper cites Burgoon, Douglas P.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Burgoon, Douglas P
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.643758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7ba3dc28-9a91-4938-88da-b69c12cfe948 · outbound
This paper cites Accounting variables, deception, and a bag of words: Assessing the tools of fraud detection.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Accounting variables, deception, and a bag of words: Assessing the tools of fraud detection
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.625827Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7c4ec4cc-f544-4608-be35-59ab89253396 · outbound
This paper cites Deceptive opinion spam detection using neural network.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Deceptive opinion spam detection using neural network
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.610617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d36cf274-4faa-4434-91f4-3ac9d2542c29 · outbound
This paper cites Pay attention and you won’t lose it: A deep learning approach to sequence imputation.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Pay attention and you won’t lose it: A deep learning approach to sequence imputation
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.594989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e475152b-09c9-470a-84ad-2779651e93e2 · outbound
This paper cites Vickers, L.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Vickers, L
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.579556Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 27bce324-db2c-48d3-a6b3-13121cd8756d · outbound
This paper cites Yoo, Chan Yeob Yeun, Dirar Homouz, and Ahmed Taha.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Yoo, Chan Yeob Yeun, Dirar Homouz, and Ahmed Taha
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.564496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b86b182e-206c-432d-9e5f-b03e3fa9fdbc · outbound
This paper cites F1 score in machine learning explained.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach F1 score in machine learning explained
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.549097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a0071986-2050-48b7-8231-b9e545f70827 · outbound
This paper cites Classification: Accuracy, recall, precision, and related metrics.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Classification: Accuracy, recall, precision, and related metrics
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.534266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6b2957e6-b7a5-4c3c-9182-66b15f1d6ad5 · outbound
This paper cites Understanding and applying f1 score: Ai evaluation essentials.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Understanding and applying f1 score: Ai evaluation essentials
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.519797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 82f7f2b3-b17c-4ebc-ae8a-85c49c8a21c7 · outbound
This paper cites Custom text classification evaluation metrics.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Custom text classification evaluation metrics
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.504098Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 7fa7fc46-1fa9-45df-a74a-5468da2c5ebe · outbound
This paper cites an unresolved cited work.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Unresolved cited work
Reference 54
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T20:47:12.489276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 642eab2f-d784-4725-91e7-f983160e5d8b · outbound
This paper cites Decoding persuasion: a survey on ml and nlp methods for the study of online persuasion.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Decoding persuasion: a survey on ml and nlp methods for the study of online persuasion
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.472844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9e8c09db-c1d7-44dc-9ca0-69b0f34dbb92 · outbound
This paper cites Mohawesh, H.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Mohawesh, H
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.458197Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8de52949-3c85-4285-977d-3ffa738657f4 · outbound
This paper cites A comprehensive analysis of deception detection techniques leveraging machine learning.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach A comprehensive analysis of deception detection techniques leveraging machine learning
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.443245Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e304750d-9f4b-45f0-a7fb-9ee43a2d30ce · outbound
This paper cites Swaminathan and B.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Swaminathan and B
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.427454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 640cae31-0800-4b6c-b10c-170eef15741c · outbound
This paper cites an unresolved cited work.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Unresolved cited work
Reference 59
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T20:47:12.412157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 181152c1-771d-4549-b24b-3b2e46f61e63 · outbound
This paper cites A systematic review of aspect-based sentiment analysis: domains, methods, and trends.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach A systematic review of aspect-based sentiment analysis: domains, methods, and trends
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.395009Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 19313aed-8ada-4ba6-9ab3-e4df98f068c4 · outbound
This paper cites Environmental claim detection, 2023.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Environmental claim detection, 2023
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.217797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ad12475d-f616-49c4-9032-a577fb737e02 · outbound
This paper cites The effects of communication media and culture on deception detection accuracy.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach The effects of communication media and culture on deception detection accuracy
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:12.050873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ef7c8f27-09b0-4458-98a8-30dad9072012 · outbound
This paper cites Ai-driven approaches for real-time fraud detection in us financial transactions: Challenges and opportunities.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Ai-driven approaches for real-time fraud detection in us financial transactions: Challenges and opportunities
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:11.838622Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 957b9c5e-c035-4055-9966-c9337105733c · outbound
This paper cites Albuquerque.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Albuquerque
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:11.587227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation fc6fe63c-5884-4d55-82a6-0f4839f19b71 · outbound
This paper cites Fake news detection: a survey of evaluation datasets.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Fake news detection: a survey of evaluation datasets
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:11.414742Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 5a37b87b-18ed-4ece-9640-6014f189ef7e · outbound
This paper cites Financial fraud detection using vocal, linguistic and financial cues.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Financial fraud detection using vocal, linguistic and financial cues
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:11.166263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f8b4dec3-984e-4299-9b50-d85077963d05 · outbound
This paper cites Hossen and M.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Hossen and M
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:10.896885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 702fc519-0683-4d7d-9483-c811cb399532 · outbound
This paper cites Hossen and M.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Hossen and M
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:10.708790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d16ecd1d-1ffb-4f52-b76f-142db87fba94 · outbound
This paper cites Hossen and M.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Hossen and M
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:10.425728Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 00e18d58-4a59-4c7a-b8e2-480e36f452a0 · outbound
This paper cites Hossen and M.
Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Hossen and M
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T20:47:10.273986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.