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Paper Citation Record · LEDGER

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models

As of 20 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2505.02858.

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

pith.paper-citation-record.v1
2505.02858 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:22:35.455720Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

54 of 54 outbound references displayed

  • verified exact3
  • verified fuzzy26
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4fc7c5a0-1b2f-4459-b7de-4bf5f8d2ee71 · outbound

This paper cites MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets

Reference 1

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Observation 5e4b7867-e481-4e89-9f88-a82cbff84499 · outbound

This paper cites Using large language models to simulate multiple humans and replicate human subject studies.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Using large language models to simulate multiple humans and replicate human subject studies

Reference 2

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Observation 054c840f-be69-4fc8-8ccf-7aa6f87bcfec · outbound

This paper cites an unresolved cited work.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation eea1f544-53ba-405a-8c22-11cd67f982cc · outbound

This paper cites Out of one, many: Using language models to simulate human samples.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Out of one, many: Using language models to simulate human samples

Reference 4

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Observation 1e62898e-69b8-495b-bda7-3b0d021534e8 · outbound

This paper cites Multi-modal embeddings for isolating cross-platform coordinated information campaigns on social media.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Multi-modal embeddings for isolating cross-platform coordinated information campaigns on social media

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3c4bc4dc-f5f6-435a-a417-a26766862ed3 · outbound

This paper cites TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification

Reference 6

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Source-reported events for the cited work

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Observation 768249a7-258c-4d02-84a9-ad4b45755774 · outbound

This paper cites InstaSynth: Opportunities and Challenges in Generating Synthetic Instagram Data with ChatGPT for Sponsored Content Detection.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models InstaSynth: Opportunities and Challenges in Generating Synthetic Instagram Data with ChatGPT for Sponsored Content Detection

Reference 7

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local_arxiv, observed 2026-08-16T04:22:35.709115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a263d66a-92dd-46d3-bcf5-a5cfdf84b6fe · outbound

This paper cites Leveraging llm-generated data for detecting depression symptoms on social media.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Leveraging llm-generated data for detecting depression symptoms on social media

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 654b2a5e-eabf-40fc-943a-49af9cac24b3 · outbound

This paper cites AugGPT: Leveraging ChatGPT for Text Data Augmentation.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models AugGPT: Leveraging ChatGPT for Text Data Augmentation

Reference 9

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Observation 3a22e7c8-e326-4965-85e1-0a564f513935 · outbound

This paper cites OffensiveLang: A Community Based Implicit Offensive Language Dataset.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models OffensiveLang: A Community Based Implicit Offensive Language Dataset

Reference 10

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 26380adf-dcd9-4714-aaf6-f1863a83adba · outbound

This paper cites Identify- ing citizen-related issues from social media using llm-based data augmentation.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Identify- ing citizen-related issues from social media using llm-based data augmentation

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation cb9aa1a1-e22c-4aae-9409-d08b658011d2 · outbound

This paper cites emojinal intelligence.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models emojinal intelligence

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3106ebe8-50b3-47dd-838e-7e7439f1e93a · outbound

This paper cites Socially aware synthetic data generation for suicidal ideation detection using large language models.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Socially aware synthetic data generation for suicidal ideation detection using large language models

Reference 13

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation bc45ae40-483f-455a-8f96-9a1cfa448992 · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 14

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Observation 5641f42c-4d58-43dd-ab9b-671646c2cb17 · outbound

This paper cites Ai and the transformation of social science research.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Ai and the transformation of social science research

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f54d3f0d-19bb-4032-b507-5ee92aa251d9 · outbound

This paper cites Across platforms and languages: Dutch influencers and legal disclosures on instagram, youtube and tiktok.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Across platforms and languages: Dutch influencers and legal disclosures on instagram, youtube and tiktok

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 15196dc5-f0fd-4903-9a05-13752a68cae2 · outbound

This paper cites Evaluating large language models in generating synthetic hci research data: a case study.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Evaluating large language models in generating synthetic hci research data: a case study

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d78ce1c5-8d64-4de2-bca4-7736918d897e · outbound

This paper cites Happenstance: utilizing semantic search to track russian state media narratives about the russo-ukrainian war on reddit.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Happenstance: utilizing semantic search to track russian state media narratives about the russo-ukrainian war on reddit

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 227b5f57-ed15-4c60-95e1-1f7f57f5b730 · outbound

This paper cites ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection

Reference 19

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Observation 5f7941c4-f54b-4caa-a349-9ff0255cc354 · outbound

This paper cites Using twitter data to understand public perceptions of approved versus off-label use for covid-19-related medications.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Using twitter data to understand public perceptions of approved versus off-label use for covid-19-related medications

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1f3e654b-a68b-456a-86c0-e8ca0351d736 · outbound

This paper cites Cross-cultural Inspiration Detection and Analysis in Real and LLM-generated Social Media Data.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Cross-cultural Inspiration Detection and Analysis in Real and LLM-generated Social Media Data

Reference 21

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Observation d1902fe4-7862-490a-9e63-475f39da556e · outbound

This paper cites Employing large language models in survey research.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Employing large language models in survey research

Reference 22

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation cc9eede0-4274-4830-a4da-b5a314accafb · outbound

This paper cites Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction

Reference 23

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Observation a9eb81f6-7b20-4b7d-82ec-011ecbdb59f0 · outbound

This paper cites Synthetic vs. Gold: The Role of LLM Generated Labels and Data in Cyberbullying Detection.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Synthetic vs. Gold: The Role of LLM Generated Labels and Data in Cyberbullying Detection

Reference 24

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Observation 2464694f-65d0-4b0e-b306-3c70f9a03c2c · outbound

This paper cites an unresolved cited work.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9a17df87-7095-4099-b6fc-6ee42100f7b7 · outbound

This paper cites Data augmentation approaches in natural language processing: A survey.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Data augmentation approaches in natural language processing: A survey

Reference 26

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Observation 7a2345b8-b3f9-40af-90ab-3ec4e34af8a1 · outbound

This paper cites Synthetic data generation with large language models for text classification: Potential and limitations.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Synthetic data generation with large language models for text classification: Potential and limitations

Reference 27

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raw_fallback, observed 2026-08-16T04:22:35.921358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 407ac7c7-d9d9-4813-ab4c-960c8c9614b2 · outbound

This paper cites Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8a63c60d-be2e-4dd0-bd64-957ad5b90515 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 29

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Source-reported events for the cited work

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Observation f2e6586c-5d02-4b5a-932e-d8aec8ba6e8b · outbound

This paper cites TimeLMs: Diachronic language models from Twitter.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models TimeLMs: Diachronic language models from Twitter

Reference 30

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raw_fallback, observed 2026-08-16T04:22:35.903099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.359865Z digest=sha256:de5866697d913087d26e2fed6becb96c7c148499b8fdc4354b6b7e3a0b3652ba

Observation 0a1c1f84-8d3f-4534-9dbc-aadd6e5c6ac6 · outbound

This paper cites Coordinating a multi-platform disinformation campaign: Internet research agency activity on three u.s.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Coordinating a multi-platform disinformation campaign: Internet research agency activity on three u.s

Reference 31

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raw_fallback, observed 2026-08-16T04:22:35.892748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4c6d5e05-5670-459a-95a3-dab426d27aa7 · outbound

This paper cites an unresolved cited work.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-16T04:22:35.882135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fa490eaf-475e-4eb2-a77f-ff97c0bb9d5e · outbound

This paper cites The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks

Reference 33

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.370884Z digest=sha256:22fe59f25dfcb0d52cb45220f337573d9591e7cea1d0bc9fa355523c1c71753a

Observation 32951e68-9044-442a-bd57-4d4ef9c90d79 · outbound

This paper cites Text and Code Embeddings by Contrastive Pre-Training.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Text and Code Embeddings by Contrastive Pre-Training

Reference 34

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no resolver link, observed 2026-08-16T04:22:35.374703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.374703Z digest=sha256:bfa56baef04498b04a8521fb4e0e265f67917e619f2a839ed31e2b30ac5dc0fa

Observation 8f60f855-647b-4e45-b61d-a690568626e6 · outbound

This paper cites Multi-platform information operations: Twitter, facebook and youtube against the white helmets.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Multi-platform information operations: Twitter, facebook and youtube against the white helmets

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.870726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.378714Z digest=sha256:66015722c1e9d088dd47a11330cff621ed4f402d5aa0f09185a70b46f4bebf17

Observation 49a246c2-69ef-4543-aae2-67b16f3f2b4c · outbound

This paper cites EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-16T04:22:35.382932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.382932Z digest=sha256:e0da8d17e5d4bb09b865460dd6310a8d548e48c17e12e570c9a3c836c8f291fa

Observation 48b8b881-8d29-4fb5-8b1e-f39505ba666b · outbound

This paper cites Enhancing discourse parsing for local structures from social media with llm-generated data.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Enhancing discourse parsing for local structures from social media with llm-generated data

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.860167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.386969Z digest=sha256:d0fb6d38c6375c58568cfc13b4bc45308af7aaa879ff20ca2e88e6ae1bcf990e

Observation 1c11d7a5-ab71-4c58-8bf3-503c7aab5e7f · outbound

This paper cites Ita-election-2022: A multi-platform dataset of social media conversations around the 2022 italian general election.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Ita-election-2022: A multi-platform dataset of social media conversations around the 2022 italian general election

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.849167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.390593Z digest=sha256:d96254e12d40d058a49c4560faaf5b861c6540afa2868a5fddf716869daeb87c

Observation 3449ecc6-328b-4a48-9e75-86d755098867 · outbound

This paper cites Llm-based synthetic datasets: Applications and limitations in toxicity detection.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Llm-based synthetic datasets: Applications and limitations in toxicity detection

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.838889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.394815Z digest=sha256:b027df94181a1d528bb9358a4d7b5c51a2a6412a6bae58b0b455eea9d4489ae4

Observation 22f2ddcb-5340-4b32-832c-2d507f93336e · outbound

This paper cites Computational repro- ducibility in computational social science.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Computational repro- ducibility in computational social science

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.827107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.398541Z digest=sha256:9085cc1200138cb0912e7d30214f1686e00422d2a9019f8112a139aa6e7e3b59

Observation 8cfdd11a-0378-40c3-9ac7-6ed8fc873276 · outbound

This paper cites Improving Neural Machine Translation Models with Monolingual Data.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Improving Neural Machine Translation Models with Monolingual Data

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-16T04:22:35.402129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.402129Z digest=sha256:37f0a80d1778871ffd8889d7b2e6b5d33676e50a5b1bc4b82d8e6b92695a8c32

Observation 581c3275-5946-4627-bfe4-0d31d354dbe6 · outbound

This paper cites The rise of germany’s afd: A social media analysis.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models The rise of germany’s afd: A social media analysis

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.815312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.406349Z digest=sha256:75799250356872ba203727a56ab45acd8c8be59638dd24403577875a52a5c5c8

Observation 3aa5478b-6483-432b-9ff2-e4aaed311e22 · outbound

This paper cites Leveraging GPT for the Generation of Multi-Platform Social Media Datasets for Research.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Leveraging GPT for the Generation of Multi-Platform Social Media Datasets for Research

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-16T04:22:35.554261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.409736Z digest=sha256:198be26216d9b1c07ec7e789e07e249218bf83034673f710d173838dbab0d4d5

Observation ea1c1cdc-69b7-48a4-97bc-80904a56fb07 · outbound

This paper cites Leveraging gpt for the generation of multi-platform so- cial media datasets for research.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Leveraging gpt for the generation of multi-platform so- cial media datasets for research

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.803786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.414755Z digest=sha256:ad1c15639f6732e66f7e5bb83e514754c5e366a849462ebcc8a69c0dd596ba9b

Observation 6114c419-44fb-41ac-a07d-d15d16a11292 · outbound

This paper cites Simulating Social Media Using Large Language Models to Evaluate Alternative News Feed Algorithms.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Simulating Social Media Using Large Language Models to Evaluate Alternative News Feed Algorithms

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T04:22:35.418691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.418691Z digest=sha256:ada4ded2fd46fa25410a7de7e769153b7a656b035f56c3920efe78c677cb59a4

Observation 27c70c33-b534-42f0-a067-fc01be915053 · outbound

This paper cites Big questions for social media big data: Representativeness, validity and other methodological pitfalls.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Big questions for social media big data: Representativeness, validity and other methodological pitfalls

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.791182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.423320Z digest=sha256:df3bc3046fbff78d429f3761e472b8877043447da50992510c4c352a6a9e79f9

Observation 875e566a-e3e5-48e1-80b5-dd1191fbf5be · outbound

This paper cites ZeroShotDataAug: Generating and Augmenting Training Data with ChatGPT.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models ZeroShotDataAug: Generating and Augmenting Training Data with ChatGPT

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-16T04:22:35.427235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.427235Z digest=sha256:d0db6f9785cb83b1c738b246f16184e4fa505b69e9b03af1501bc9ced902eb3d

Observation e2cdd483-e81c-48d2-a4fd-36301665ccdb · outbound

This paper cites A multi-platform dataset for detect- ing cyberbullying in social media.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models A multi-platform dataset for detect- ing cyberbullying in social media

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.778463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.431827Z digest=sha256:6fbe1141c6e06ef2f7dee09c1366c93b6a72889dee4aa8416853c50884322898

Observation 327c0768-c919-4201-b835-1c61963aac27 · outbound

This paper cites Happiness and sadness in adolescents’ instagram direct messaging: A neural topic modeling approach.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Happiness and sadness in adolescents’ instagram direct messaging: A neural topic modeling approach

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.765837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.436113Z digest=sha256:bc916d977dc6d4b9e88d91f70dbe0fe407a8fea54bc987f2b612941fa8be4da4

Observation 8bde78c4-a34c-4528-947f-ea9bd71b88d5 · outbound

This paper cites Generating Faithful Synthetic Data with Large Language Models: A Case Study in Computational Social Science.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Generating Faithful Synthetic Data with Large Language Models: A Case Study in Computational Social Science

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-16T04:22:35.439882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.439882Z digest=sha256:abfcfca985992efd994ac8ba601ed33ee1fe5de60e216ecd2595fd0c2ee9e856

Observation 42a7abe1-bead-4303-88aa-c7ce2116e32d · outbound

This paper cites The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-16T04:22:35.443572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.443572Z digest=sha256:cd4f179e0989fa1d231ddbc3426a9293faa08f60118e4d922882454b87157b58

Observation 261ac7a1-5a35-4f25-b6bc-009521e69ea3 · outbound

This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.753455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.447817Z digest=sha256:a39114b0d47e9ff3bf545509f573b1a484d6dd791b8e7f6ddec91ad8c5204539

Observation 63e8b6be-95f9-4ba6-97a0-8dea9f3756c7 · outbound

This paper cites EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-16T04:22:35.451463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:22:35.451463Z digest=sha256:ea5074fa0da2847794760f4fdaf6d9ec370bb7512004c92aed6ce4c8ee48b610

Observation 44e8c180-130d-40e9-a640-7eba4b36eaae · outbound

This paper cites Cross-platform information operations: Mobilizing narratives & building resilience through both ’big’ & ’alt’ tech.

Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models Cross-platform information operations: Mobilizing narratives & building resilience through both ’big’ & ’alt’ tech

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:22:35.742312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-16T04:22:35.455720Z digest=sha256:7d00d0637d40f663165b3653d524a0baccaede036530df4397540329aabd0315

Pith citing papers

No inbound Pith citation observations are available.