---
title: "Who cites Tweet Acts: A Speech Act Classifier for Twitter"
description: "19 papers of the Elamur Research library cite «Tweet Acts: A Speech Act Classifier for Twitter», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/vosoughi-2016-tweet-acts-speech-act-classifier/cited-by/"
---
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# Who cites «Tweet Acts: A Speech Act Classifier for Twitter»

19 papers of our library cite it (of the 141,840 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «Tweet Acts: A Speech Act Classifier for Twitter»](https://md.research.elamur.ai/free/en/papers/vosoughi-2016-tweet-acts-speech-act-classifier/)

1. **[Multi-task dialog act and sentiment recognition on Mastodon](https://md.research.elamur.ai/free/en/papers/cerisara-2018-multi-task-dialog-act-sentiment/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Christophe Cerisara, Somayeh Jafaritazehjani, Adedayo Oluokun, et al.*2018 · 66 citations*
2. **[On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition](https://md.research.elamur.ai/free/en/papers/cerisara-2020-effects-using-word2vec-representations-neural/) [Computer Speech & Language](https://md.research.elamur.ai/free/en/venues/computer-speech-language/)**Christophe Cerisara, Pavel Kral, Ladislav Lenc*2017 · 46 citations*
3. **[Towards Sentiment and Emotion aided Multi-modal Speech Act Classification in Twitter](https://md.research.elamur.ai/free/en/papers/saha-2021-sentiment-emotion-aided-multi-modal/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tulika Saha, Apoorva Upadhyaya, Sriparna Saha, et al.*2021 · 43 citations*
4. [**Modeling Speech Acts in Asynchronous Conversations: A Neural-CRF Approach**Shafiq Joty, Tasnim Mohiuddin*2018 · 20 citations*](https://md.research.elamur.ai/free/en/papers/joty-2018-modeling-speech-acts-asynchronous-conversations/)
5. **[Arabic Tweet-Act: Speech Act Recognition for Arabic Asynchronous Conversations](https://md.research.elamur.ai/free/en/papers/algotiml-2019-arabic-tweet-act-speech-act/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Bushra Algotiml, AbdelRahim Elmadany, Walid Magdy*2019 · 18 citations*
6. **[Target Based Speech Act Classification in Political Campaign Text](https://md.research.elamur.ai/free/en/papers/subramanian-2019-target-based-speech-act-classification/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin*2019 · 13 citations*
7. [**Don't get Lost in Negation: An Effective Negation Handled Dialogue Acts Prediction Algorithm for Twitter Customer Service Conversations arXiv:1807.06107**Mansurul Bhuiyan, Amita Misra, Saurabh Tripathy, et al.*2018 · 7 citations*](https://md.research.elamur.ai/free/en/papers/bhuiyan-2018-don-t-get-lost-negation/)
8. [**Arabic Tweet Act: A Weighted Ensemble Pre-Trained Transformer Model for Classifying Arabic Speech Acts on Twitter arXiv:2401.17373**Khadejaa Alshehri, Areej Alhothali, Nahed Alowidi*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alshehri-2024-arabic-tweet-act-weighted-ensemble/)

11 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/vosoughi-2016-tweet-acts-speech-act-classifier/) — Tweet Acts: A Speech Act Classifier for Twitter