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Paper Citation Record · LEDGER

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops

As of 8 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.15114.

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

pith.paper-citation-record.v1
2607.15114 v2

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T00:11:40.693826Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8154a600-3082-4e34-887c-994df2961e1b · outbound

This paper cites Ricci, L.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Ricci, L

Reference 1

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Observation e86f57ba-9683-47f4-99da-8035d00d197b · outbound

This paper cites Matrix factorization techniques for recommender systems,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Matrix factorization techniques for recommender systems,

Reference 2

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source=pdf_text observed=2026-08-02T00:11:40.531276Z digest=sha256:ba1533917052bf07d596f05e30e83c7ef99e76d26a314fc30b40b87e53bf359e

Observation 090afbdc-8f4b-4e40-9026-867e7163e9dd · outbound

This paper cites Bpr: Bayesian personalized ranking from implicit feedback,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Bpr: Bayesian personalized ranking from implicit feedback,

Reference 3

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source=pdf_text observed=2026-08-02T00:11:40.536799Z digest=sha256:5df5642189e6b31789c3c502902bbbf607819664ea2dfdcb29a54bdf758f148d

Observation 4bd53e31-ae7b-441b-9a41-2fc537de5ec3 · outbound

This paper cites Lightgcn: Simplifying and powering graph convolution network for recommenda- tion,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Lightgcn: Simplifying and powering graph convolution network for recommenda- tion,

Reference 4

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source=pdf_text observed=2026-08-02T00:11:40.542872Z digest=sha256:29984da6fa4651112efef4c84fad4b09492c7a062464345c1dece8f6f028228e

Observation de96b1db-b998-4e3b-b138-6d894f71908d · outbound

This paper cites The relevance of algorithms,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops The relevance of algorithms,

Reference 5

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source=pdf_text observed=2026-08-02T00:11:40.549080Z digest=sha256:330a8e93e43c6360c3d5bf4695b3b38cc07ded6418dd090f82cb2c899924e950

Observation ec1df0ff-738f-4d31-a772-f824b731866d · outbound

This paper cites Automated media: An institutional theory perspective on algorithmic media production and consumption,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Automated media: An institutional theory perspective on algorithmic media production and consumption,

Reference 6

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source=pdf_text observed=2026-08-02T00:11:40.554470Z digest=sha256:e97344d9500782844d61cdac12c219100b18bbc49a6435fd1de646fc6269fdae

Observation d9c80735-eed3-4a28-9e09-3388ca66ceb7 · outbound

This paper cites Toward trustwor- thy recommender systems: An analysis of attack models and algorithm robustness,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Toward trustwor- thy recommender systems: An analysis of attack models and algorithm robustness,

Reference 7

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source=pdf_text observed=2026-08-02T00:11:40.562051Z digest=sha256:d4cbb7ef86b74e418d089a10b034e466adaa75f1830335a34da54d6d46a0ade1

Observation f679bd45-46df-476f-851d-bdda210cbe00 · outbound

This paper cites Shilling attacks against recommender systems: A comprehensive survey,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Shilling attacks against recommender systems: A comprehensive survey,

Reference 8

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source=pdf_text observed=2026-08-02T00:11:40.567728Z digest=sha256:46deed0b40f53a5353c92ae26eb06377ec49af6e6790f492def344d5f9519054

Observation 2eb47283-0fe5-490d-9cb8-3384f326b902 · outbound

This paper cites Data poisoning attacks on factorization-based collaborative filtering,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Data poisoning attacks on factorization-based collaborative filtering,

Reference 9

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source=pdf_text observed=2026-08-02T00:11:40.573098Z digest=sha256:94ebb6dd87bca05d5163685272477c3c7f073a8b68836ecd20a818f91f846afd

Observation 08e6db75-e9de-4bb0-96af-e657daf702c2 · outbound

This paper cites How algorithmic confounding in recommendation systems increases homogeneity and decreases utility,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops How algorithmic confounding in recommendation systems increases homogeneity and decreases utility,

Reference 10

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source=pdf_text observed=2026-08-02T00:11:40.578488Z digest=sha256:b1a43c0ddafffdf00ea457897f36d53a2006de5526dfccae175792cee48258fc

Observation d4ef14d4-67a7-4f12-bac5-cd4602bfde24 · outbound

This paper cites Feedback loop and bias amplification in recommender systems,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Feedback loop and bias amplification in recommender systems,

Reference 11

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source=pdf_text observed=2026-08-02T00:11:40.583533Z digest=sha256:387edb249628b1c0933f6b2a909a7951d381b86c3b2de6b00d62d05719d7153e

Observation 7c617df3-328b-447e-b5a2-12634decc90f · outbound

This paper cites The unfairness of popularity bias in recommendation,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops The unfairness of popularity bias in recommendation,

Reference 12

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source=pdf_text observed=2026-08-02T00:11:40.589584Z digest=sha256:fbd4bd01023bab196b5896cef620d219faa4abfe00bd8cbdc2715b723357e384

Observation 145c5940-d4bc-4ed4-aa95-f6bb0d2b1bdc · outbound

This paper cites The rise of social bots,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops The rise of social bots,

Reference 13

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source=pdf_text observed=2026-08-02T00:11:40.597458Z digest=sha256:779c3e23392f16060cf01570b342b0fcb3b3a985aa550c097a3c3c76af7de556

Observation 0b7356d3-ff9a-48d8-89f2-cff4d37a8675 · outbound

This paper cites Online human-bot interactions: Detection, estimation, and characterization,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Online human-bot interactions: Detection, estimation, and characterization,

Reference 14

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source=pdf_text observed=2026-08-02T00:11:40.602759Z digest=sha256:c04bea257eb48e7b929345357c9974b6f7f46b2d60239210924dd0c974560b0c

Observation 910772b8-213a-4af4-af4c-8cd50eb180d5 · outbound

This paper cites The spread of true and false news online,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops The spread of true and false news online,

Reference 15

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source=pdf_text observed=2026-08-02T00:11:40.608347Z digest=sha256:9022f1da307af731378830b0d7f217629e41b9ffd992db6274eb47639d6e8d8b

Observation e2050650-d947-4dea-a4f7-4e2118f2a5aa · outbound

This paper cites Generative agents: Interactive simulacra of human behavior,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Generative agents: Interactive simulacra of human behavior,

Reference 16

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source=pdf_text observed=2026-08-02T00:11:40.615468Z digest=sha256:6c5201e99e0e5f9c2eec3ae38673c0053008749dc1cedb0b3668cedda539619d

Observation 4d5efa0c-9bbc-4538-8273-bcb0845321eb · outbound

This paper cites User behavior simulation with large language model-based agents,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops User behavior simulation with large language model-based agents,

Reference 17

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source=pdf_text observed=2026-08-02T00:11:40.622890Z digest=sha256:671470a1bffdc0a51322feac98cc5f1a2270a3cc73ccf59eadde043de94c537c

Observation 1b6fd168-6837-45d5-826b-9cff83ba510a · outbound

This paper cites On generative agents in recommendation,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops On generative agents in recommendation,

Reference 18

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source=pdf_text observed=2026-08-02T00:11:40.628973Z digest=sha256:0eae6bfb70cf29c6eeae226983bf6b4335d99abf3458f3e8e6122b5abed715b7

Observation 00534716-efbd-4625-b634-cfc9eaba4c2c · outbound

This paper cites RecSim: A Configurable Simulation Platform for Recommender Systems.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops RecSim: A Configurable Simulation Platform for Recommender Systems

Reference 19

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source=pdf_text observed=2026-08-02T00:11:40.635338Z digest=sha256:a4bcb803d7ef757209eac75780eee53cee1e86fd5a41d921bf87b0e3fbd5ff54

Observation a6c8043a-d34b-4f17-b693-abbe31596805 · outbound

This paper cites OASIS: Open Agent Social Interaction Simulations with One Million Agents.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops OASIS: Open Agent Social Interaction Simulations with One Million Agents

Reference 20

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Observation 68b6ad39-bbe9-437a-adb0-fcc250394625 · outbound

This paper cites Mind: A large-scale dataset for news recommendation,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Mind: A large-scale dataset for news recommendation,

Reference 21

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source=pdf_text observed=2026-08-02T00:11:40.649604Z digest=sha256:8fd5783fbb411d05e94549f93320320f038b0c020eb9e36c6cd9b2b6cfbb1f55

Observation 57bf204a-e1bb-4abf-bfd5-8a6ac5ab4ddd · outbound

This paper cites The movielens datasets: History and context,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops The movielens datasets: History and context,

Reference 22

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source=pdf_text observed=2026-08-02T00:11:40.656402Z digest=sha256:3a7f4a8999e7c5397bfbb43ec965ad67e4573fbd334cc62e399c5a5e28bc796d

Observation ee21c476-1aaa-472b-b618-b07374523e03 · outbound

This paper cites Hetrec 2011 datasets,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Hetrec 2011 datasets,

Reference 23

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source=pdf_text observed=2026-08-02T00:11:40.662481Z digest=sha256:4f039a0ae2e2c8896242737c50a75d566d09b1919c9589326db7193273e6938a

Observation b26e7c75-b2e5-473c-823f-6133d2d9ff46 · outbound

This paper cites What kind of news gatekeepers do we want machines to be? filter bubbles, fragmentation, and the normative dimensions of algorithmic recommendations,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops What kind of news gatekeepers do we want machines to be? filter bubbles, fragmentation, and the normative dimensions of algorithmic recommendations,

Reference 24

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source=pdf_text observed=2026-08-02T00:11:40.669716Z digest=sha256:52d44543a3196e80d2dfb1d0c0f7b96519da4eb59014d569f374a8756297ad62

Observation 58140e33-6d1e-40ed-88c4-eb2ff808cdec · outbound

This paper cites Experimental study of inequality and unpredictability in an artificial cultural market,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Experimental study of inequality and unpredictability in an artificial cultural market,

Reference 25

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source=pdf_text observed=2026-08-02T00:11:40.675257Z digest=sha256:978e880ba1994d743eae354380ab57acfa056617ad20fca830af5883573613cc

Observation 6b8e90b7-e256-4d13-bae9-a2d2e24e9eea · outbound

This paper cites Exposure diversity as a design principle for recommender systems,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops Exposure diversity as a design principle for recommender systems,

Reference 26

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source=pdf_text observed=2026-08-02T00:11:40.681805Z digest=sha256:540d8fd5e058b5f5acae02cc80106c0a909dc214c406c79fca00a764806c2bdc

Observation 559e228f-c0da-4a2f-b931-5b308407ce40 · outbound

This paper cites The logic of connective action: Digital media and the personalization of contentious politics,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops The logic of connective action: Digital media and the personalization of contentious politics,

Reference 27

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source=pdf_text observed=2026-08-02T00:11:40.687425Z digest=sha256:cafec87118238494b90e0bd0561d2c7a1686c78ae6c8d5a1dd1b44d0d8cc3e2f

Observation 4578d887-b3ab-4d58-ad4c-a481fa7c79c7 · outbound

This paper cites On the detection of disinformation campaign activity with network analysis,.

CoSimRec: Measuring Coordinated-Content Penetration in Recommender Feedback Loops On the detection of disinformation campaign activity with network analysis,

Reference 28

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source=pdf_text observed=2026-08-02T00:11:40.693826Z digest=sha256:86a5468bbe904361aad468c0faacc7df0580b9a506b06ff9ca513a7332523ed5

Pith citing papers

No inbound Pith citation observations are available.