mlsanityData to 7 Oct 2026

Twitter Topic Classification

arXiv 2209.09824 ↗First posted 20 Sep 2022cs.CLcited by 22

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Abstract (arXiv)

Social media platforms host discussions about a wide variety of topics that arise everyday. Making sense of all the content and organising it into categories is an arduous task. A common way to deal with this issue is relying on topic modeling, but topics discovered using this technique are difficult to interpret and can differ from corpus to corpus. In this paper, we present a new task based on tweet topic classification and release two associated datasets. Given a wide range of topics covering the most important discussion points in social media, we provide training and testing data from recent time periods that can be used to evaluate tweet classification models. Moreover, we perform a quantitative evaluation and analysis of current general- and domain-specific language models on the task, which provide more insights on the challenges and nature of the task.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 14 of its 72 references that are in the map. First posted on arXiv 20 Sep 2022.

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14 of 72 references.

References · 14

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  3. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,201
  4. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  5. 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 779
  6. 2020BERTweet: A pre-trained language model for English Tweetscited by 346
  7. 2021Mind the Gap: Assessing Temporal Generalization in Neural Language Modelscited by 226
  8. 2017Advances in Pre-Training Distributed Word Representationscited by 207
  9. 2022TimeLMs: Diachronic Language Models from Twittercited by 129
  10. 2020Top2Vec: Distributed Representations of Topicscited by 124
  11. 2022TweetNLP: Cutting-Edge Natural Language Processing for Social Mediacited by 71
  12. 2020A large-scale COVID-19 Twitter chatter dataset for open scientific research -- an international collaborationcited by 33
2 more
  1. 2016Tweet2Vec: Character-Based Distributed Representations for Social Mediacited by 9
  2. 2018Election campaigning on social media: Politicians, audiences and the mediation of political communication on Facebook and Twittercited by 4

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Citing papers per year: 2022: 1; 2023: 14; 2024: 2; 2025: 2; 2026: 3.

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  3. 2023Robust Hate Speech Detection in Social Media: A Cross-Dataset Empirical Evaluationcited by 28
  4. 2022Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal Shiftscited by 27
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  10. 2023Tweet Insights: A Visualization Platform to Extract Temporal Insights from Twittercited by 3
  11. 2023MetRoBERTa: Leveraging Traditional Customer Relationship Management Data to Develop a Transit-Topic-Aware Language Modelcited by 3
  12. 2024FAQ-Gen: An automated system to generate domain-specific FAQs to aid content comprehensioncited by 2
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  4. 2026Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curationcited by 1
  5. 2023Curating corpora with classifiers: A case study of clean energy sentiment onlinecited by 0
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  7. 2025Uncertainty-driven Embedding Convolutioncited by 0
  8. 2025TopiCLEAR: Adaptive embedding clustering for interpretable topic discovery from short textscited by 0
  9. 2026Recommender system in X inadvertently profiles ideological positions of userscited by 0
  10. 2026Improving Topic Modeling by Distilling Soft Labels from Language Modelscited by 0