Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach | Paper Citation Record

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

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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

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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

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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

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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

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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

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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

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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

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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

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This paper cites Flusberg, Kevin J.

Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Flusberg, Kevin J

Reference 10

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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

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Observation 0d2078c0-93cb-40e1-98d2-22c7058762b7 · outbound

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Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Unresolved cited work

Reference 12

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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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

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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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+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

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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

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Observation 8e665175-499b-4e20-aca6-228546a56ac2 · outbound

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Language of Persuasion and Misrepresentation in Business Communication: A Textual Detection Approach Unresolved cited work

Reference 32

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+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

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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

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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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+00:00.

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Reference resolution

Outbound references

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