Natural Language Processing Psychometrics | Paper Citation Record

Observation b1e2655d-4c2b-46e5-bd06-44415487eec4 · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 1

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Observation 745c874e-c794-42d5-9f15-e4479ad66d4c · outbound

This paper cites Self-efficacy and locus of control when facing listening challenges: Validation of the listening challenges attitude scale (licas).

Natural Language Processing Psychometrics Self-efficacy and locus of control when facing listening challenges: Validation of the listening challenges attitude scale (licas)

Reference 2

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Observation de169a24-1582-4adc-baa0-bd508c75b24d · outbound

This paper cites Exploratory factor analysis: Current use, methodological developments and recommendations for good practice.Current psychology, 40(7):3510–3521, 2021.

Natural Language Processing Psychometrics Exploratory factor analysis: Current use, methodological developments and recommendations for good practice.Current psychology, 40(7):3510–3521, 2021

Reference 3

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Observation 46b8bff0-72b5-49dc-9e1a-5ff7c4d4f916 · outbound

This paper cites Dasentimental: Detecting depression, anxiety, and stress in texts via emotional recall, cognitive networks, and machine learning.Big data and cognitive computing, 5(4):77, 2021.

Natural Language Processing Psychometrics Dasentimental: Detecting depression, anxiety, and stress in texts via emotional recall, cognitive networks, and machine learning.Big data and cognitive computing, 5(4):77, 2021

Reference 4

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Observation d5ac2b1e-3725-4979-8c95-318987b7e3d5 · outbound

This paper cites LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies.

Natural Language Processing Psychometrics LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies

Reference 5

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Observation 077a0456-a707-4b91-a3ba-48a4971e7801 · outbound

This paper cites Examining linguistic differences in electronic health records for diverse patients with diabetes: natural language processing analysis.JMIR Medical Informatics, 12(1):e50428, 2024.

Natural Language Processing Psychometrics Examining linguistic differences in electronic health records for diverse patients with diabetes: natural language processing analysis.JMIR Medical Informatics, 12(1):e50428, 2024

Reference 6

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Observation 89e3c163-096c-46be-bd19-332e82ee5719 · outbound

This paper cites Language is primarily a tool for communication rather than thought.Nature, 630(8017):575–586, 2024.

Natural Language Processing Psychometrics Language is primarily a tool for communication rather than thought.Nature, 630(8017):575–586, 2024

Reference 7

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Observation 16f94765-ac0a-4a1e-8ca1-0cef0e55e18f · outbound

This paper cites John Wiley & Sons, 2012.

Natural Language Processing Psychometrics John Wiley & Sons, 2012

Reference 8

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Observation 88ddbb29-0316-48b9-a1bf-b5286802f983 · outbound

This paper cites Deep lexical hypothesis: Identifying personality structure in natural language.Journal of Personality and Social Psychology, 125(1):173, 2023.

Natural Language Processing Psychometrics Deep lexical hypothesis: Identifying personality structure in natural language.Journal of Personality and Social Psychology, 125(1):173, 2023

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.110876Z

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Observation ded9a208-4df7-4188-a4b7-2f97ac9102f6 · outbound

This paper cites Emoatlas: An emotional network analyzer of texts that merges psychological lexicons, artificial intelligence, and network science.Behavior Research Methods, 57(2):77, 2025.

Natural Language Processing Psychometrics Emoatlas: An emotional network analyzer of texts that merges psychological lexicons, artificial intelligence, and network science.Behavior Research Methods, 57(2):77, 2025

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.144611Z

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Observation 6613b261-354f-4214-9801-affb04556e83 · outbound

This paper cites Using complex networks to understand the mental lexicon.

Natural Language Processing Psychometrics Using complex networks to understand the mental lexicon

Reference 11

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Observation f3b2f4fe-67ea-4414-b797-ab2dcf1f0ca5 · outbound

This paper cites Structure and flexibility: Inves- tigating the relation between the structure of the mental lexicon, fluid intelligence, and creative achievement.

Natural Language Processing Psychometrics Structure and flexibility: Inves- tigating the relation between the structure of the mental lexicon, fluid intelligence, and creative achievement

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.301944Z

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Observation 19aeb13c-ecf8-4c5b-943a-e7522a81f37e · outbound

This paper cites Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.Psychonomic Bulletin & Review, 31(5):1981–2004, 2024.

Natural Language Processing Psychometrics Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges.Psychonomic Bulletin & Review, 31(5):1981–2004, 2024

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.349388Z

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Observation 6c9ee9ee-f456-49a3-b505-e07068253408 · outbound

This paper cites In an absolute state: Elevated use of absolutist words is a marker specific to anxiety, depression, and suicidal ideation.Clinical psychological science, 6(4):529–542, 2018.

Natural Language Processing Psychometrics In an absolute state: Elevated use of absolutist words is a marker specific to anxiety, depression, and suicidal ideation.Clinical psychological science, 6(4):529–542, 2018

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:44.363328Z

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Observation 6e979e0e-1a35-40db-806b-850b9eab5b87 · outbound

This paper cites How do users of a mental health app conceptualise digital therapeutic alliance? a qualitative study using the framework approach.

Natural Language Processing Psychometrics How do users of a mental health app conceptualise digital therapeutic alliance? a qualitative study using the framework approach

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:44.351986Z

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Observation 411fa2f5-6def-4ee7-964d-87681d7c24c9 · outbound

This paper cites Detecting and measuring depression on social media using a machine learning approach: systematic review.JMIR Mental Health, 9(3): e27244, 2022.

Natural Language Processing Psychometrics Detecting and measuring depression on social media using a machine learning approach: systematic review.JMIR Mental Health, 9(3): e27244, 2022

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:44.338797Z

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Observation 3bb1bbf1-2acd-4bc5-9541-05907a09b50c · outbound

This paper cites Predicting depression via social media.

Natural Language Processing Psychometrics Predicting depression via social media

Reference 17

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Observation b056d8d3-b271-4a7f-a471-e031b8fbf63c · outbound

This paper cites Digital shadows in mental health map how llms simulate depression, anxiety, and stress through language and psychometrics.PsyArXiv,.

Natural Language Processing Psychometrics Digital shadows in mental health map how llms simulate depression, anxiety, and stress through language and psychometrics.PsyArXiv,

Reference 18

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Observation 2431d8f9-d7b7-4d8c-bb6f-dd5623e4459e · outbound

This paper cites Harvard University, 2024.

Natural Language Processing Psychometrics Harvard University, 2024

Reference 19

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Observation 39780863-611b-48a5-8fb3-1cfaa77e8dd1 · outbound

This paper cites Text psychometrics: Assessing psychological constructs in text using natural language processing, 2026.

Natural Language Processing Psychometrics Text psychometrics: Assessing psychological constructs in text using natural language processing, 2026

Reference 20

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Observation f81dee48-e414-4b99-a789-66eada5bae9e · outbound

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Natural Language Processing Psychometrics Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-10T10:28:43.947161Z

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Observation 7c6fa032-e694-41e5-abe3-5d1b4aa0a68f · outbound

This paper cites The phq-9: validity of a brief depression severity measure.Journal of general internal medicine, 16(9):606–613, 2001.

Natural Language Processing Psychometrics The phq-9: validity of a brief depression severity measure.Journal of general internal medicine, 16(9):606–613, 2001

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.935946Z

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Observation 7557b040-d2f3-4de6-9340-2e4ce37988c1 · outbound

This paper cites Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior.

Natural Language Processing Psychometrics Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.674371Z

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Observation 0b1f849f-3da9-4be9-93cd-6449c15ee848 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Natural Language Processing Psychometrics Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.679110Z

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Observation 3661d8af-ed78-4667-bc52-02981617fb83 · outbound

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Natural Language Processing Psychometrics Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-10T10:28:43.924579Z

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Observation 6b91d091-394e-499a-87e6-1f173e29c6f6 · outbound

This paper cites Escaping the jingle-jangle jungle: Increasing conceptual clarity in psychology using large language models.Current Directions in Psychological Science, 35(2):59–65, 2026.

Natural Language Processing Psychometrics Escaping the jingle-jangle jungle: Increasing conceptual clarity in psychology using large language models.Current Directions in Psychological Science, 35(2):59–65, 2026

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.912765Z

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Observation 91ba97af-fd76-441c-8801-045a6af6f1cf · outbound

This paper cites Lost in the middle: How language models use long contexts.Transactions of the Association for Computational Linguistics, 12:157–173, 2024.

Natural Language Processing Psychometrics Lost in the middle: How language models use long contexts.Transactions of the Association for Computational Linguistics, 12:157–173, 2024

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.690763Z

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Observation bc40b7b3-e75f-4a8b-9b4b-eadadc14df87 · outbound

This paper cites Large language models accurately identify decision reasons in verbal reports.Proceedings of the National Academy of Sciences, 123(27):e2526798123, 2026.

Natural Language Processing Psychometrics Large language models accurately identify decision reasons in verbal reports.Proceedings of the National Academy of Sciences, 123(27):e2526798123, 2026

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.893799Z

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Observation 0195748e-56b6-457f-8537-4164d33fc240 · outbound

This paper cites Evaluating llms for synthetic personas generation: A comparative analysis of personality representation and censorship effects.

Natural Language Processing Psychometrics Evaluating llms for synthetic personas generation: A comparative analysis of personality representation and censorship effects

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.882395Z

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Observation f2fd1f7e-038b-42bd-91e4-81fff6675ded · outbound

This paper cites Quantifying the Persona Effect in LLM Simulations.

Natural Language Processing Psychometrics Quantifying the Persona Effect in LLM Simulations

Reference 30

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Observation bffd59bc-6fc8-44e6-a78a-210354e90ac3 · outbound

This paper cites Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable.

Natural Language Processing Psychometrics Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.706927Z

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Observation 1c41d8a0-da19-4014-91a7-f20a5ce69f8d · outbound

This paper cites Large language models that replace human participants can harmfully misportray and flatten identity groups.Nature Machine Intelligence, 7(3):400–411, 2025.

Natural Language Processing Psychometrics Large language models that replace human participants can harmfully misportray and flatten identity groups.Nature Machine Intelligence, 7(3):400–411, 2025

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.870155Z

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Observation 27c972a1-0342-48a9-ab19-21c4e8091165 · outbound

This paper cites Large language models are homogeneously creative.PNAS nexus, 5(3): pgag042, 2026.

Natural Language Processing Psychometrics Large language models are homogeneously creative.PNAS nexus, 5(3): pgag042, 2026

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.856344Z

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Observation 33f47695-95a6-4954-bd77-4390877bf431 · outbound

This paper cites Math Education Digital Shadows for Investigating Learning with GenAI: Mathematics Performance, Anxiety, and Confidence in LLMs.

Natural Language Processing Psychometrics Math Education Digital Shadows for Investigating Learning with GenAI: Mathematics Performance, Anxiety, and Confidence in LLMs

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-10T10:28:41.980560Z

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Observation d692acfa-3335-462c-88dc-b7cc69419ebd · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-10T10:28:43.844790Z

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Observation 1a04c9dc-41ab-4c93-a4d9-e615e8985bd4 · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-10T10:28:43.834051Z

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Observation 857aa70d-d18a-4234-9f86-750102770959 · outbound

This paper cites A diagnostic meta-analysis of the patient health questionnaire- 9 (phq-9) algorithm scoring method as a screen for depression.General hospital psychiatry, 37(1):67–75, 2015.

Natural Language Processing Psychometrics A diagnostic meta-analysis of the patient health questionnaire- 9 (phq-9) algorithm scoring method as a screen for depression.General hospital psychiatry, 37(1):67–75, 2015

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.776578Z

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Observation 81875dbc-cac9-408b-84c6-ac40135d7626 · outbound

This paper cites Using network science to analyze concept maps of psychology undergraduates.Applied Cognitive Psychology, 33(4):662–668, 2019.

Natural Language Processing Psychometrics Using network science to analyze concept maps of psychology undergraduates.Applied Cognitive Psychology, 33(4):662–668, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.571108Z

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Observation be89c6d0-da48-4f50-9794-9aaa9e43e25a · outbound

This paper cites Cognitive networks for knowledge modeling: A gentle introduction for data-and cognitive scientists.Wiley Interdisciplinary Reviews: Cognitive Science, 17(2):e70026, 2026.

Natural Language Processing Psychometrics Cognitive networks for knowledge modeling: A gentle introduction for data-and cognitive scientists.Wiley Interdisciplinary Reviews: Cognitive Science, 17(2):e70026, 2026

Reference 39

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Observation 2cf5ef69-a2a8-4090-87e4-44f5080a68b0 · outbound

This paper cites Cognitive network science: A review of research on cognition through the lens of network representations, processes, and dynamics.Complexity, 2019(1): 2108423, 2019.

Natural Language Processing Psychometrics Cognitive network science: A review of research on cognition through the lens of network representations, processes, and dynamics.Complexity, 2019(1): 2108423, 2019

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.389552Z

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Observation ad66a87e-3ba6-4476-af18-d14855be8861 · outbound

This paper cites spreadr: An r package to simulate spreading activation in a network.Behavior Research Methods, 51(2):910–929, 2019.

Natural Language Processing Psychometrics spreadr: An r package to simulate spreading activation in a network.Behavior Research Methods, 51(2):910–929, 2019

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Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:40.924130Z

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Observation cc4f886b-3102-401d-b6be-d27832c9d47a · outbound

This paper cites Using network science in the language sciences and clinic.International journal of speech-language pathology, 17(1):13–25, 2015.

Natural Language Processing Psychometrics Using network science in the language sciences and clinic.International journal of speech-language pathology, 17(1):13–25, 2015

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.371992Z

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Observation 91a1eb29-f1f2-4758-b868-8b698a89a4dc · outbound

This paper cites Crowdsourcing a word–emotion association lexicon.Computational intelligence, 29(3):436–465, 2013.

Natural Language Processing Psychometrics Crowdsourcing a word–emotion association lexicon.Computational intelligence, 29(3):436–465, 2013

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Observation c3ca5b3c-1cab-4783-9fc3-621670bcd5d6 · outbound

This paper cites Affective biases in english are bi-dimensional.Cognition and Emotion, 29(7):1147–1167, 2015.

Natural Language Processing Psychometrics Affective biases in english are bi-dimensional.Cognition and Emotion, 29(7):1147–1167, 2015

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.354641Z

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Observation 251bc3cc-f736-410d-a216-a7bbd23c4477 · outbound

This paper cites A perspective on explainable artificial intelligence methods: Shap and lime.Advanced Intelligent Systems, 7(1):2400304, 2025.

Natural Language Processing Psychometrics A perspective on explainable artificial intelligence methods: Shap and lime.Advanced Intelligent Systems, 7(1):2400304, 2025

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.342393Z

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Observation 85be87a0-6229-45d6-8f0e-431e1d57c138 · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nature machine intelligence, 1(5):206–215, 2019.

Natural Language Processing Psychometrics Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nature machine intelligence, 1(5):206–215, 2019

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.100002Z

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Observation 8f0a3023-d158-46bb-9b37-b2af2e28e8e9 · outbound

This paper cites Personality traits in large language models.Prepritnt, 2023.

Natural Language Processing Psychometrics Personality traits in large language models.Prepritnt, 2023

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.325525Z

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Observation 1ea48700-1aa7-4c0b-baf1-80d0c63f041f · outbound

This paper cites The satisfaction with life scale.Journal of personality assessment, 49(1):71–75, 1985.

Natural Language Processing Psychometrics The satisfaction with life scale.Journal of personality assessment, 49(1):71–75, 1985

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.314584Z

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Observation 2988692f-c7c7-4cce-b445-8366366199a9 · outbound

This paper cites Screening for depressive disorders in patients with skin diseases: a comparison of three screeners.Acta dermato-venereologica, 85(5):414–419, 2005.

Natural Language Processing Psychometrics Screening for depressive disorders in patients with skin diseases: a comparison of three screeners.Acta dermato-venereologica, 85(5):414–419, 2005

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.303080Z

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Observation 5a4e414b-f635-4e02-ad16-ca90fa87eca4 · outbound

This paper cites Advanced natural-based interaction for the italian language: Llamantino-3-anita, 2024.

Natural Language Processing Psychometrics Advanced natural-based interaction for the italian language: Llamantino-3-anita, 2024

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.290561Z

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Observation d365e7c6-ff3a-4791-ae00-f13eeb2bbd2a · outbound

This paper cites Qwen3 Technical Report.

Natural Language Processing Psychometrics Qwen3 Technical Report

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.119152Z

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Observation 87e3f56a-c0a5-4971-9ed0-2da3ed65b15c · outbound

This paper cites gpt-oss-120b & gpt-oss-20b Model Card.

Natural Language Processing Psychometrics gpt-oss-120b & gpt-oss-20b Model Card

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.123359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ee601a7-7b0e-4051-b375-bac761ac13a8 · outbound

This paper cites Olmo 3.

Natural Language Processing Psychometrics Olmo 3

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.127297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f65dbe9-8136-454b-9a87-ac1a57dd728b · outbound

This paper cites Nemotron 3 nano: Open, efficient mixture-of-experts hybrid mamba-transformer model for agentic reasoning.arXiv preprint arXiv:2512.20848, 2025.

Natural Language Processing Psychometrics Nemotron 3 nano: Open, efficient mixture-of-experts hybrid mamba-transformer model for agentic reasoning.arXiv preprint arXiv:2512.20848, 2025

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.131797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 772ce7ed-0677-4896-8dbb-8c28eb1a78ea · outbound

This paper cites Testing theory of mind in large language models and humans.Nature Human Behaviour, 8(7):1285–1295, 2024.

Natural Language Processing Psychometrics Testing theory of mind in large language models and humans.Nature Human Behaviour, 8(7):1285–1295, 2024

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.135387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2891d5a2-9566-40e1-baa6-920498691732 · outbound

This paper cites Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception.Cognition, 13(1):103–128, 1983.

Natural Language Processing Psychometrics Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children’s understanding of deception.Cognition, 13(1):103–128, 1983

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.139114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 286ce5b3-ab85-48c7-be3f-2b2e6436d7ee · outbound

This paper cites Comparative performance of large language models in emotional safety classification across sizes and tasks.Frontiers in Artificial Intelligence, 8:1706090, 2025.

Natural Language Processing Psychometrics Comparative performance of large language models in emotional safety classification across sizes and tasks.Frontiers in Artificial Intelligence, 8:1706090, 2025

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.266097Z

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 5e571775-b1df-4571-8df4-7ea977499722 · outbound

This paper cites The cost of thinking is similar between large reasoning models and humans.Proceedings of the National Academy of Sciences, 122(47):e2520077122, 2025.

Natural Language Processing Psychometrics The cost of thinking is similar between large reasoning models and humans.Proceedings of the National Academy of Sciences, 122(47):e2520077122, 2025

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.254452Z

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 7ba107b5-a3a3-4f2c-b27e-20a9e659d7a5 · outbound

This paper cites Language models don’t always say what they think: Unfaithful explanations in chain-of-thought prompting.Advances in Neural Information Processing Systems, 36:74952–74965, 2023.

Natural Language Processing Psychometrics Language models don’t always say what they think: Unfaithful explanations in chain-of-thought prompting.Advances in Neural Information Processing Systems, 36:74952–74965, 2023

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.150974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f831512-5a67-44a4-8b76-a2d167a564b3 · outbound

This paper cites Leveraging llm respondents for item evaluation: A psychometric analysis.British Journal of Educational Technology, 56(3):1028–1052, 2025.

Natural Language Processing Psychometrics Leveraging llm respondents for item evaluation: A psychometric analysis.British Journal of Educational Technology, 56(3):1028–1052, 2025

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:43.048716Z

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 da468584-2257-417e-8976-1dbdbef141d2 · outbound

This paper cites Covid-19 pandemic and lockdown measures impact on mental health among the general population in italy.Frontiers in psychiatry, 11:550552, 2020.

Natural Language Processing Psychometrics Covid-19 pandemic and lockdown measures impact on mental health among the general population in italy.Frontiers in psychiatry, 11:550552, 2020

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.930363Z

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 a89d959a-ddba-4516-8636-78e6f11820b1 · outbound

This paper cites Psychological distress among italians during the 2019 coronavirus disease (covid-19) quarantine.

Natural Language Processing Psychometrics Psychological distress among italians during the 2019 coronavirus disease (covid-19) quarantine

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.918955Z

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 86122838-c440-46d0-b908-c99a2f9782a7 · outbound

This paper cites Text-mining forma mentis networks reconstruct public perception of the stem gender gap in social media.PeerJ Computer Science, 6:e295, 2020.

Natural Language Processing Psychometrics Text-mining forma mentis networks reconstruct public perception of the stem gender gap in social media.PeerJ Computer Science, 6:e295, 2020

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.907785Z

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 1f3fcafb-e9b8-4715-87ed-25e69985d074 · outbound

This paper cites Textual forma mentis networks bridge language structure, emotional content and psychopathology levels in adolescents.

Natural Language Processing Psychometrics Textual forma mentis networks bridge language structure, emotional content and psychopathology levels in adolescents

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.171706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ee080ee-67d9-4ec1-8b8a-829736ccda8a · outbound

This paper cites Cognitive networks for knowledge modelling: A gentle tutorial for data-and cognitive scientists.PsyArXiv Preprints, 2023.

Natural Language Processing Psychometrics Cognitive networks for knowledge modelling: A gentle tutorial for data-and cognitive scientists.PsyArXiv Preprints, 2023

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.215131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e281c28-ed1d-4326-9750-9fe37a49411e · outbound

This paper cites Estimating the number of communities in a network.Physical review letters, 117(7):078301, 2016.

Natural Language Processing Psychometrics Estimating the number of communities in a network.Physical review letters, 117(7):078301, 2016

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.889918Z

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 578bd05d-672c-4cbf-a7a8-6125bcb0147d · outbound

This paper cites Ysocial: An artificial intelligence powered social media virtual twin.

Natural Language Processing Psychometrics Ysocial: An artificial intelligence powered social media virtual twin

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.878424Z

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 fe62c558-100a-4e5f-beb5-ac322a7d5d49 · outbound

This paper cites Forma mentis networks quantify crucial differences in stem perception between students and experts.PloS one, 14(10):e0222870, 2019.

Natural Language Processing Psychometrics Forma mentis networks quantify crucial differences in stem perception between students and experts.PloS one, 14(10):e0222870, 2019

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.867283Z

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 40693c3f-35c8-4506-a55a-ee462a0e5c70 · outbound

This paper cites A general psychoevolutionary theory of emotion.

Natural Language Processing Psychometrics A general psychoevolutionary theory of emotion

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.854579Z

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 49ad7173-b992-4d7b-ae56-9b56fc8760f5 · outbound

This paper cites Random forests.Machine learning, 45(1):5–32, 2001.

Natural Language Processing Psychometrics Random forests.Machine learning, 45(1):5–32, 2001

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.536895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b9d3fbc-ce7f-4038-96ca-12c050600a63 · outbound

This paper cites Pedregosa, G.

Natural Language Processing Psychometrics Pedregosa, G

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.541057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a613955-6238-4864-8e0e-a9441b5e3d53 · outbound

This paper cites A unified approach to interpreting model predictions.Advances in neural information processing systems, 30, 2017.

Natural Language Processing Psychometrics A unified approach to interpreting model predictions.Advances in neural information processing systems, 30, 2017

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.544131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae93cdf0-160b-4d3a-bc17-2b7237749f2c · outbound

This paper cites From local explanations to global understanding with explainable ai for trees.Nature machine intelligence, 2(1):56–67, 2020.

Natural Language Processing Psychometrics From local explanations to global understanding with explainable ai for trees.Nature machine intelligence, 2(1):56–67, 2020

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.547989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e387df7d-06e3-4374-bf37-cc2f1f828ef7 · outbound

This paper cites Do models of mental health based on social media data generalize? InFindings of the association for computational linguistics: EMNLP 2020, pages 3774–3788, 2020.

Natural Language Processing Psychometrics Do models of mental health based on social media data generalize? InFindings of the association for computational linguistics: EMNLP 2020, pages 3774–3788, 2020

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.816900Z

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 85d22da5-4315-441d-94e3-96ab2079a945 · outbound

This paper cites The androids corpus: A new publicly available benchmark for speech based depression detection.Depression, 47:11–9, 2023.

Natural Language Processing Psychometrics The androids corpus: A new publicly available benchmark for speech based depression detection.Depression, 47:11–9, 2023

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.804327Z

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 b01bf2db-b2e6-4285-83e9-ce6baa6d25d0 · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

Natural Language Processing Psychometrics Robust speech recognition via large-scale weak supervision

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-10T10:28:41.558761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55cb1972-f9c1-434a-8f86-8355c5cdfa3c · outbound

This paper cites Modeling depressive patterns in italian discourse: Insights from natural language processing, 2025.

Natural Language Processing Psychometrics Modeling depressive patterns in italian discourse: Insights from natural language processing, 2025

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.649849Z

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 e83b2c94-7e43-4d47-bedd-932cf4f233f9 · outbound

This paper cites Will money increase subjective well-being?Social indicators research, 57 (2):119–169, 2002.

Natural Language Processing Psychometrics Will money increase subjective well-being?Social indicators research, 57 (2):119–169, 2002

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.413329Z

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 aa28470c-b91c-457d-94ed-c45994a9156f · outbound

This paper cites High income improves evaluation of life but not emotional well-being.

Natural Language Processing Psychometrics High income improves evaluation of life but not emotional well-being

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.309060Z

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 cbd0be37-7256-4b46-9fc1-800b333ddbc6 · outbound

This paper cites Happiness, income satiation and turning points around the world.Nature Human Behaviour, 2(1):33–38, 2018.

Natural Language Processing Psychometrics Happiness, income satiation and turning points around the world.Nature Human Behaviour, 2(1):33–38, 2018

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.279502Z

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 c603d5c2-ce5a-440f-a8c9-2d327a4fb5e7 · outbound

This paper cites Sadness as an integral part of depression.Dialogues in clinical neuroscience, 10(3):321–327, 2008.

Natural Language Processing Psychometrics Sadness as an integral part of depression.Dialogues in clinical neuroscience, 10(3):321–327, 2008

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.268906Z

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 5355d85a-64a1-4a37-890c-d2d288cc45b9 · outbound

This paper cites American psychiatric association Washington, DC, 2013.

Natural Language Processing Psychometrics American psychiatric association Washington, DC, 2013

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.258188Z

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 fc151111-4acd-4b00-aff0-7b2cad490c66 · outbound

This paper cites Language use of depressed and depression-vulnerable college students.Cognition & Emotion, 18(8):1121–1133, 2004.

Natural Language Processing Psychometrics Language use of depressed and depression-vulnerable college students.Cognition & Emotion, 18(8):1121–1133, 2004

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.247800Z

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 fcbf0943-85c3-427e-b31c-4aebc65f7b51 · outbound

This paper cites Facebook language predicts depression in medical records.

Natural Language Processing Psychometrics Facebook language predicts depression in medical records

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.236207Z

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 8353271d-f910-4e82-9824-080189c87371 · outbound

This paper cites Constructive and unconstructive repetitive thought.Psychological bulletin, 134(2):163, 2008.

Natural Language Processing Psychometrics Constructive and unconstructive repetitive thought.Psychological bulletin, 134(2):163, 2008

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.224957Z

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 a99c1966-41bf-4c41-80f7-a14cab9c2a19 · outbound

This paper cites Language-based personality: A new approach to personality in a digital world.Current opinion in behavioral sciences, 18:63–68, 2017.

Natural Language Processing Psychometrics Language-based personality: A new approach to personality in a digital world.Current opinion in behavioral sciences, 18:63–68, 2017

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.212581Z

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 bafbda36-e1d9-48c2-ae72-3b75ba42e21e · outbound

This paper cites Forma mentis networks map how nursing and engineering students enhance their mindsets about innovation and health during professional growth.PeerJ Computer Science, 6:e255, 2020.

Natural Language Processing Psychometrics Forma mentis networks map how nursing and engineering students enhance their mindsets about innovation and health during professional growth.PeerJ Computer Science, 6:e255, 2020

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.200465Z

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 17c17327-466d-4a05-aa4a-0f748cc4c8cc · outbound

This paper cites Rethinking rumination.Perspectives on psychological science, 3(5):400–424, 2008.

Natural Language Processing Psychometrics Rethinking rumination.Perspectives on psychological science, 3(5):400–424, 2008

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.187572Z

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 688efb6d-b949-4444-bb31-5f321cf2c2c4 · outbound

This paper cites Linking “big” personality traits to anxiety, depressive, and substance use disorders: a meta-analysis.Psychological bulletin, 136(5):768, 2010.

Natural Language Processing Psychometrics Linking “big” personality traits to anxiety, depressive, and substance use disorders: a meta-analysis.Psychological bulletin, 136(5):768, 2010

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.174390Z

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 f8b9f734-9610-4284-9b6a-87ffaa85ba0f · outbound

This paper cites Worry: A cognitive phenomenon intimately linked to affective, physiological, and interpersonal behavioral processes.Cognitive therapy and research, 22(6):561–576, 1998.

Natural Language Processing Psychometrics Worry: A cognitive phenomenon intimately linked to affective, physiological, and interpersonal behavioral processes.Cognitive therapy and research, 22(6):561–576, 1998

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T10:28:42.160120Z

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 6664000f-0e31-445a-8cfb-36887ef7c485 · outbound

This paper cites Machine Psychology.

Natural Language Processing Psychometrics Machine Psychology

Reference 91

Resolution: malformed identifier; no resolver link, observed 2026-08-10T10:28:41.613505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69507402-af41-4018-8d58-e13d7fc6044c · outbound

This paper cites an unresolved cited work.

Natural Language Processing Psychometrics Unresolved cited work

Reference 2026

Resolution: verified exact; doi, observed 2026-08-10T10:28:41.648987Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers