Towards High-Fidelity Synthetic Multi-platform Social Media Datasets via Large Language Models | Paper Citation Record

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

Reference 3

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

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

Reference 32

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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