Learning Invariant Representations of Social Media Users

Attention Is All You Need

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

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Semi-supervised classification with graph convolutional networks

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Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftPreprint

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Convolutional Neural Networks for Sentence Classification

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Deep Contextualized Word Representations

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node2vec: Scalable Feature Learning for Networks

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ArcFace: Additive Angular Margin Loss for Deep Face Recognition

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Clustering by Passing Messages Between Data Points

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LINE: Large-scale Information Network Embedding

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Approximate nearest neighbors: towards removing the curse of dimensionality

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Automated Hate Speech Detection and the Problem of Offensive Language

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SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK

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Understanding inverse document frequency: on theoretical arguments for IDF

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Learning Fine-Grained Image Similarity with Deep Ranking

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V-Measure: A Conditional Entropy-Based External Cluster Evaluation Measure

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A survey of modern authorship attribution methods

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Convolutional Neural Networks for Sentence ClassificationPreprint

Kim, Y. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1408.5882 · Cited by 1,112 · see citing works

Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions

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Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates

Kudo, T. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/p18-1007 · Cited by 1,021 · see citing works

The MegaFace Benchmark: 1 Million Faces for Recognition at Scale

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SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter

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Understanding the Demographics of Twitter Users

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SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)

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Deep Learning is Robust to Massive Label Noise

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Approximate Nearest Neighbors: Towards Removing the Curse of Dimensionality

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The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition

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Developing Age and Gender Predictive Lexica over Social Media

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node2vec: Scalable Feature Learning for Networks

Grover, A., & Leskovec, J. (2016) · PubMed · doi:10.48550/arxiv.1607.00653 · Cited by 229 · see citing works

Determining if two documents are written by the same author

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Smokey: Automatic Recognition of Hostile Messages

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Tweet2Vec: Character-Based Distributed Representations for Social Media

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Radicalization and the Use of Social Media

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Convolutional Neural Networks for Authorship Attribution of Short Texts

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Smokey: automatic recognition of hostile messages

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Carmen: A Twitter Geolocation System with Applications to Public Health

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Inferring Latent User Properties from Texts Published in Social Media

Volkova, S., Bachrach, Y., Armstrong, M., & Sharma, V. (2015) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v29i1.9271 · Cited by 151 · see citing works

Text-Based Twitter User Geolocation Prediction

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Predicting the Demographics of Twitter Users from Website Traffic Data

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Authorship Attribution for Twitter in 140 Characters or Less

Layton, R., Watters, P., & Dazeley, R. (2010) · Cybercrime and Trustworthy Computing Workshop (CTC) · doi:10.1109/ctc.2010.17 · Cited by 139 · see citing works

Tweet2Vec

Vosoughi, S., Vijayaraghavan, P., & Roy, D. (2016) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/2911451.2914762 · Cited by 136 · see citing works

Deep Learning for User Comment Moderation

Pavlopoulos, J., Malakasiotis, P., & Androutsopoulos, I. (2017) · Workshop on Abusive Language Online (ALW) · doi:10.18653/v1/w17-3004 · Cited by 124 · see citing works

Identifying Authorship by Byte-Level N-Grams: The Source Code Author Profile (SCAP) Method.

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Multiple Account Identity Deception Detection in Social Media Using Nonverbal Behavior

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User Migration in Online Social Networks: A Case Study on Reddit During a Period of Community Unrest

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Caveat emptor, computational social science: Large-scale missing data in a widely-published Reddit corpus

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Detecting the Hate Code on Social Media

Magu, R., Joshi, K., & Luo, J. (2017) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v11i1.14921 · Cited by 93 · see citing works

Learning Multiview Embeddings of Twitter Users

Benton, A., Arora, R., & Dredze, M. H. (2016) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/p16-2003 · Cited by 87 · see citing works

Predicting age groups of Twitter users based on language and metadata features

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Hunting for Troll Comments in News Community Forums

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Author Profiling for Abuse Detection

Mishra, P., Tredici, M. D., Yannakoudakis, H., & Shutova, E. (2018) · UvA-DARE (University of Amsterdam) · Cited by 70 · see citing works

Detection of Promoted Social Media Campaigns

Ferrara, E., Varol, O., Menczer, F., & Flammini, A. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v10i1.14772 · Cited by 68 · see citing works

A Case Study of Sockpuppet Detection in Wikipedia

Solorio, T., Hasan, R., & Mizan, M. (2013) · Cited by 65 · see citing works

Generalists and Specialists: Using Community Embeddings to Quantify Activity Diversity in Online Platforms

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Tweet2Vec: Learning Tweet Embeddings Using Character-level CNN-LSTM Encoder-Decoder

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Blogs, Twitter Feeds, and Reddit Comments: Cross-domain Authorship Attribution

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How to Manipulate Social Media: Analyzing Political Astroturfing Using Ground Truth Data from South Korea

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Topic or style? Exploring the most useful features for authorship attribution

Sari, Y. A. P., Stevenson, M., & Vlachos, A. (2018) · Apollo (University of Cambridge) · doi:10.17863/cam.78746 · Cited by 48 · see citing works

Authorship attribution on micro-messages

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Classification of Instant Messaging Communications for Forensics Analysis

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Authorship Attribution Using a Neural Network Language Model

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Overview of PAN 2018

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Sockpuppet Detection in Wikipedia: A Corpus of Real-World Deceptive Writing for Linking Identities

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Authorship Attribution in Greek Tweets Using Author's Multilevel N-Gram Profiles

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Modeling Trolling in Social Media ConversationsPreprint

Mojica, L. G. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1612.05310 · Cited by 25 · see citing works

Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities

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Native Language Identification with User Generated Content

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805

Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates

Kudo, T. (2018) · arXiv · doi:10.48550/arxiv.1804.10959

Deep Learning for User Comment Moderation

Pavlopoulos, J., Malakasiotis, P., & Androutsopoulos, I. (2017) · arXiv · doi:10.48550/arxiv.1705.09993

Modeling Trolling in Social Media Conversations

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A taxonomy and review of generalization research in NLPPreprint

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Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges

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Learning Universal Authorship Representations

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Exploiting Behavioral Consistence for Universal User Representation

Gu, J., Wang, F., Sun, Q., Ye, Z., Xu, X., Chen, J., & Zhang, J. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i5.16527 · Cited by 26 · see citing works

TVShowGuess: Character Comprehension in Stories as Speaker Guessing

Sang, Y., Mou, X., Yu, M., Yao, S., Li, J., & Stanton, J. M. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.317 · Cited by 13 · see citing works

A Deep Metric Learning Approach to Account Linking

Khan, A., Fleming, E., Schofield, N., Bishop, M., & Andrews, N. (2021) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2021.naacl-main.415 · Cited by 14 · see citing works

Learning Interpretable Style Embeddings via Prompting LLMs

Patel, A., Rao, D., Kothary, A., McKeown, K., & Callison-Burch, C. (2023) · arXiv · doi:10.48550/arxiv.2305.12696 · Cited by 10 · see citing works

Learning Interpretable Style Embeddings via Prompting LLMs

Patel, A., Rao, D., Kothary, A., McKeown, K. R., & Callison-Burch, C. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.1020 · Cited by 20 · see citing works

ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer

Horvitz, Z., Patel, A., Callison-Burch, C., Zhou, Y., & McKeown, K. R. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i16.29780 · Cited by 7 · see citing works

SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis

Maneriker, P., He, Y., & Parthasarathy, S. (2021) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2021.emnlp-main.548 · Cited by 8 · see citing works

URM4DMU: An User Representation Model for Darknet Markets Users

Liu, H., Zhao, J., Huo, Y., Wang, Y., Liao, C., Shen, L., Cui, S., & Shi, J. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10096556 · Cited by 4 · see citing works

Can Authorship Representation Learning Capture Stylistic Features?

Wang, A., Aggazzotti, C., Kotula, R., Soto, R. A. R., Bishop, M., & Andrews, N. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00610 · Cited by 27 · see citing works

Interest-oriented Universal User Representation via Contrastive LearningPreprint

Sun, Q., Gu, J., Yang, B., Xu, X., Xu, R., Gao, S., Liu, H., & Xu, H. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.08865 · Cited by 5 · see citing works

Learning Interest-oriented Universal User Representation via Self-supervision

Sun, Q., Gu, J., Xu, X., Xu, R., Liu, K., Yang, B., Liu, H., & Xu, H. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548767 · Cited by 3 · see citing works

Learning Universal Authorship Representations

Soto, R. R., Miano, O., & Ordoñez, J. (2021) · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · doi:10.11578/dc.20230216.2 · Cited by 1 · see citing works

Neural Temporal Opinion Modelling for Opinion Prediction on Twitter

Zhu, L., He, Y., & Zhou, D. (2020) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2020.acl-main.352 · Cited by 1 · see citing works

Mean User-Text Agglomeration (MUTA): Practical User Representation and Visualization for Detection of Online Influence Operations

Crothers, E., Viktor, H. L., & Japkowicz, N. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-91434-9_27 · Cited by 1 · see citing works

A Syntax-Aware Encoder for Authorship Attribution

Liu, J., Hu, Z., Zhang, J., Lee, R. K.-W., & Shao, J. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-90888-1_31 · Cited by 1 · see citing works

On the Design of the MITLL Trimodal Dataset for Identity Verification

Singer, E., Borgström, B. J., Alperin, K., Nguyen, T., Dagli, C. K., Dale, M. R., & Ross, A. A. (2023) · International Workshop on Biometrics and Forensics (IWBF) · doi:10.1109/iwbf57495.2023.10157658 · Cited by 1 · see citing works

Similarity ranking using handcrafted stylometric traits in a swedish context

Fernquist, J., Pelzer, B., Lundmark, L., Kaati, L., & Johansson, F. (2021) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/3487351.3492719

Social Media Usage and Mental Health of Teenagers: Exploring the Feminist Undertone

Yakubu, L. C. (2022) · The Nigerian Journal of Sociology and Anthropology · doi:10.36108/njsa/2202.02.0270

You Shall Know a User by the Company It Keeps: Dynamic Representations for Social Media Users in NLP

Tredici, M. D., Marcheggiani, D., Walde, S. S. I., & Fernández, R. (2019) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d19-1477 · Cited by 27 · see citing works

Network Representation Learning in Social Media

Wang, S. (2018)

Representation learning for natural language processing

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UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis

Mireshghallah, F., Shrivastava, V., Shokouhi, M., Berg-Kirkpatrick, T., Sim, R., & Dimitriadis, D. (2022) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2022.naacl-main.252 · Cited by 20 · see citing works

Interpretable belief representation learning on social networks

Li, J. (2025) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)