---
title: "Sociology and Political Science — papers, page 2"
description: "Sociology and Political Science: 221 papers of the Elamur Research library · page 2 of 3 · 26–125, the most cited first — our summary of each, its ideas…"
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---
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# 🤝 Sociology and Political Science

221 papers · page 2 of 3 · 26–125 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Sociology and Political Science is a subfield of Social Sciences in the OpenAlex classification of science. The topics most of its papers here are on: «Misinformation and Its Impacts», «Historical and Linguistic Studies», «Privacy, Security, and Data Protection».

## Papers

[← prev](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/) [1](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/) **2** [3](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/page/3/) [next →](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/page/3/)

26. [**Inference-Time Intervention: Eliciting Truthful Answers from a Language Model**Kenneth Li, Oam Patel, Fernanda Viegas, et al.*2023 · 473 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-inference-time-intervention-eliciting-truthful/)
27. [**Learning Whom to Trust with MACE**Dirk Hovy, Taylor Berg-Kirkpatrick, Ashish Vaswani, et al.*2013 · 472 citations*](https://md.research.elamur.ai/free/en/papers/hovy-2013-learning-whom-trust-mace/)
28. [**GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media**Yi-Ju Lu, Cheng-Te Li*2020 · 468 citations*](https://md.research.elamur.ai/free/en/papers/lu-2020-gcan-graph-aware-co-attention/)
29. [**Defending Against Neural Fake News**Rowan Zellers, Ari Holtzman, Hannah Rashkin, et al.*2019 · 466 citations*](https://md.research.elamur.ai/free/en/papers/zellers-2019-defending-against-neural-fake-news/)
30. [**Emergent: a novel data-set for stance classification**William Ferreira, Andreas Vlachos*2016 · 458 citations*](https://md.research.elamur.ai/free/en/papers/ferreira-2016-emergent-novel-data-set-stance/)
31. [**SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours**Leon Derczynski, Kalina Bontcheva, Maria Liakata, et al.*2017 · 429 citations*](https://md.research.elamur.ai/free/en/papers/derczynski-2017-semeval-2017-task-8-rumoureval/)
32. [**The Internal State of an LLM Knows When It's Lying**Amos Azaria, Tom Mitchell*2023 · 427 citations*](https://md.research.elamur.ai/free/en/papers/azaria-2023-internal-state-llm-knows-when/)
33. [**Deal or No Deal? End-to-End Learning of Negotiation Dialogues**Mike Lewis, Denis Yarats, Yann Dauphin, et al.*2017 · 421 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2017-deal-or-no-deal-end/)
34. [**Multilingual and Multi-Aspect Hate Speech Analysis**Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang, et al.*2019 · 410 citations*](https://md.research.elamur.ai/free/en/papers/ousidhoum-2019-multilingual-multi-aspect-hate-speech/)
35. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 404 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
36. [**DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning**Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, et al.*2018 · 391 citations*](https://md.research.elamur.ai/free/en/papers/popat-2018-declare-debunking-fake-news-false/)
37. [**Fine-Grained Analysis of Propaganda in News Articles**Giovanni Da San Martino, Seunghak Yu, Alberto Barrón-Cedeño, et al.*2019 · 379 citations*](https://md.research.elamur.ai/free/en/papers/martino-2019-fine-grained-analysis-propaganda-news/)
38. [**SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles**Giovanni Da San Martino, Alberto Barrón-Cedeño, Henning Wachsmuth, et al.*2020 · 371 citations*](https://md.research.elamur.ai/free/en/papers/martino-2020-semeval-2020-task-11-detection/)
39. [**Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good**Xuewei Wang, Weiyan Shi, Richard Kim, et al.*2019 · 369 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-persuasion-good-personalized-persuasive-dialogue/)
40. [**Latent Hatred: A Benchmark for Understanding Implicit Hate Speech**Mai ElSherief, Caleb Ziems, David Muchlinski, et al.*2021 · 365 citations*](https://md.research.elamur.ai/free/en/papers/elsherief-2021-latent-hatred-benchmark-understanding-implicit/)
41. [**The Creation and Analysis of a Website Privacy Policy Corpus**Shomir Wilson, Florian Schaub, Aswarth Abhilash Dara, et al.*2016 · 336 citations*](https://md.research.elamur.ai/free/en/papers/wilson-2016-creation-analysis-website-privacy-policy/)
42. [**SemEval-2019 Task 4: Hyperpartisan News Detection**Johannes Kiesel, Maria Mestre, Rishabh Shukla, et al.*2019 · 335 citations*](https://md.research.elamur.ai/free/en/papers/kiesel-2019-semeval-2019-task-4-hyperpartisan/)
43. [**Predicting Factuality of Reporting and Bias of News Media Sources**Ramy Baly, Georgi Karadzhov, Dimitar Alexandrov, et al.*2018 · 335 citations*](https://md.research.elamur.ai/free/en/papers/baly-2018-predicting-factuality-reporting-bias-news/)
44. [**A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection**Aditya Bohra, Deepanshu Vijay, Vinay Singh, et al.*2018 · 333 citations*](https://md.research.elamur.ai/free/en/papers/bohra-2018-dataset-hindi-english-code-mixed/)
45. [**The Fact Extraction and VERification (FEVER) Shared Task**James Thorne, Andreas Vlachos, Oana Cocarascu, et al.*2018 · 322 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-fact-extraction-verification-fever-shared/)
46. [**Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection**Bertie Vidgen, Tristan Thrush, Zeerak Waseem, et al.*2021 · 320 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2021-learning-worst-dynamically-generated-datasets/)
47. [**MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims**Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al.*2019 · 319 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/)
48. [**Overview of the Evalita 2018 Task on Automatic Misogyny Identification (AMI)**Elisabetta Fersini, Debora Nozza, Paolo Rosso*2018 · 315 citations*](https://md.research.elamur.ai/free/en/papers/fersini-2018-overview-evalita-2018-task-automatic/)
49. [**Explainable Automated Fact-Checking for Public Health Claims**Neema Kotonya, Francesca Toni*2020 · 314 citations*](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/)
50. [**Challenges and frontiers in abusive content detection**Bertie Vidgen, Alex Harris, Dong Nguyen, et al.*2019 · 307 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2019-challenges-frontiers-abusive-content-detection/)
51. [**Automated Fact Checking: Task Formulations, Methods and Future Directions**James Thorne, Andreas Vlachos*2018 · 303 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-automated-fact-checking-task-formulations/)
52. [**Multi-step Jailbreaking Privacy Attacks on ChatGPT**Haoran Li, Dadi Guo, Wei Fan, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/)
53. [**Towards Debiasing Fact Verification Models**Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al.*2019 · 296 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-debiasing-fact-verification-models/)
54. [**Evaluating Verifiability in Generative Search Engines**Nelson Liu, Tianyi Zhang, Percy Liang*2023 · 294 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-verifiability-generative-search-engines/)
55. [**A Benchmark Dataset for Learning to Intervene in Online Hate Speech**Jing Qian, Anna Bethke, Yinyin Liu, et al.*2019 · 292 citations*](https://md.research.elamur.ai/free/en/papers/qian-2019-benchmark-dataset-learning-intervene-online/)
56. [**Ethical Research Protocols for Social Media Health Research**Adrian Benton, Glen Coppersmith, Mark Dredze*2017 · 292 citations*](https://md.research.elamur.ai/free/en/papers/benton-2017-ethical-research-protocols-social-media/)
57. [**SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours**Genevieve Gorrell, Elena Kochkina, Maria Liakata, et al.*2019 · 290 citations*](https://md.research.elamur.ai/free/en/papers/gorrell-2019-semeval-2019-task-7-rumoureval/)
58. [**Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 289 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/)
59. [**GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification**Jie Zhou, Xu Han, Cheng Yang, et al.*2019 · 288 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2019-gear-graph-based-evidence-aggregating/)
60. [**Fine-grained Fact Verification with Kernel Graph Attention Network**Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al.*2020 · 282 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-fine-grained-fact-verification-kernel/)
61. [**COVIDLies: Detecting COVID-19 Misinformation on Social Media**Tamanna Hossain, Robert L. Logan IV, Arjuna Ugarte, et al.*2020 · 270 citations*](https://md.research.elamur.ai/free/en/papers/hossain-2020-covidlies-detecting-covid-19-misinformation/)
62. [**UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification**Andreas Hanselowski, Hao Zhang, Zile Li, et al.*2018 · 258 citations*](https://md.research.elamur.ai/free/en/papers/hanselowski-2018-ukp-athene-multi-sentence-textual/)
63. [**L-HSAB: A Levantine Twitter Dataset for Hate Speech and Abusive Language**Hala Mulki, Hatem Haddad, Chedi Bechikh Ali, et al.*2019 · 256 citations*](https://md.research.elamur.ai/free/en/papers/mulki-2019-l-hsab-levantine-twitter-dataset/)
64. [**An Italian Twitter Corpus of Hate Speech against Immigrants**Manuela Sanguinetti, Fabio Poletto, Cristina Bosco, et al.*2018 · 253 citations*](https://md.research.elamur.ai/free/en/papers/sanguinetti-2018-italian-twitter-corpus-hate-speech/)
65. [**Generalizing Word Lattice Translation**Christopher Dyer, Smaranda Muresan, Philip Resnik*2008 · 249 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2008-generalizing-word-lattice-translation/)
66. [**Overview of the EVALITA 2018 Hate Speech Detection Task**Cristina Bosco, Felice Dell'Orletta, Fabio Poletto, et al.*2018 · 248 citations*](https://md.research.elamur.ai/free/en/papers/bosco-2018-overview-evalita-2018-hate-speech/)
67. [**DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 246 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/)
68. [**Factuality Challenges in the Era of Large Language Models**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 242 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/)
69. [**SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification**Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, et al.*2022 · 234 citations*](https://md.research.elamur.ai/free/en/papers/fersini-2022-semeval-2022-task-5-multimedia/)
70. [**A Survey of Hallucination in Large Foundation Models**Vipula Rawte, Amit Sheth, Amitava Das*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-survey-hallucination-large-foundation-models/)
71. [**Identifying Appropriate Support for Propositions in Online User Comments**Joonsuk Park, Claire Cardie*2014 · 222 citations*](https://md.research.elamur.ai/free/en/papers/park-2014-identifying-appropriate-support-propositions-online/)
72. [**HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification**Yichen Jiang, Shikha Bordia, Zheng Zhong, et al.*2020 · 221 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/)
73. [**Reasoning Over Semantic-Level Graph for Fact Checking**Wanjun Zhong, Jingjing Xu, Duyu Tang, et al.*2020 · 221 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/)
74. [**Generating Fact Checking Explanations**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 220 citations*](https://md.research.elamur.ai/free/en/papers/atanasova-2020-generating-fact-checking-explanations/)
75. [**MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets**Shraman Pramanick, Shivam Sharma, Dimitar Dimitrov, et al.*2021 · 212 citations*](https://md.research.elamur.ai/free/en/papers/pramanick-2021-momenta-multimodal-framework-detecting-harmful/)
76. [**CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech**Yi-Ling Chung, Elizaveta Kuzmenko, Serra Sinem Tekiroglu, et al.*2019 · 209 citations*](https://md.research.elamur.ai/free/en/papers/chung-2019-conan-counter-narratives-through-nichesourcing/)
77. [**Toxicity Detection: Does Context Really Matter?**John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon, et al.*2020 · 198 citations*](https://md.research.elamur.ai/free/en/papers/pavlopoulos-2020-toxicity-detection-does-context-really/)
78. [**Where is Your Evidence: Improving Fact-checking by Justification Modeling**Tariq Alhindi, Savvas Petridis, Smaranda Muresan*2018 · 194 citations*](https://md.research.elamur.ai/free/en/papers/alhindi-2018-where-is-your-evidence-improving/)
79. [**That is a Known Lie: Detecting Previously Fact-Checked Claims**Shaden Shaar, Nikolay Babulkov, Giovanni Da San Martino, et al.*2020 · 193 citations*](https://md.research.elamur.ai/free/en/papers/shaar-2020-that-is-known-lie-detecting/)
80. [**Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategies**Anjalie Field, Doron Kliger, Shuly Wintner, et al.*2018 · 193 citations*](https://md.research.elamur.ai/free/en/papers/field-2018-framing-agenda-setting-russian-news/)
81. [**A Just and Comprehensive Strategy for Using NLP to Address Online Abuse**David Jurgens, Libby Hemphill, Eshwar Chandrasekharan*2019 · 189 citations*](https://md.research.elamur.ai/free/en/papers/jurgens-2019-just-comprehensive-strategy-nlp-address/)
82. [**A Survey on Stance Detection for Mis- and Disinformation Identification**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2022 · 187 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2022-survey-stance-detection-mis-disinformation/)
83. [**Multimodal Meme Dataset (MultiOFF) for Identifying Offensive Content in Image and Text**Shardul Suryawanshi, Bharathi Raja Chakravarthi, Mihael Arcan, et al.*2020 · 186 citations*](https://md.research.elamur.ai/free/en/papers/suryawanshi-2020-multimodal-meme-dataset-multioff-identifying/)
84. [**Integrating Stance Detection and Fact Checking in a Unified Corpus**Ramy Baly, Mitra Mohtarami, James Glass, et al.*2018 · 186 citations*](https://md.research.elamur.ai/free/en/papers/baly-2018-integrating-stance-detection-fact-checking/)
85. [**The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task**Rami Aly, Zhijiang Guo, Michael Sejr Schlichtkrull, et al.*2021 · 178 citations*](https://md.research.elamur.ai/free/en/papers/aly-2021-fact-extraction-verification-over-unstructured/)
86. [**On the Risk of Misinformation Pollution with Large Language Models**Yikang Pan, Liangming Pan, Wenhu Chen, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-risk-misinformation-pollution-large-language/)
87. [**Stance Detection in COVID-19 Tweets**Kyle Glandt, Sarthak Khanal, Yingjie Li, et al.*2021 · 173 citations*](https://md.research.elamur.ai/free/en/papers/glandt-2021-stance-detection-covid-19-tweets/)
88. [**Detecting Harmful Memes and Their Targets**Shraman Pramanick, Dimitar Dimitrov, Rituparna Mukherjee, et al.*2021 · 171 citations*](https://md.research.elamur.ai/free/en/papers/pramanick-2021-detecting-harmful-memes-their-targets/)
89. [**COVID-Fact: Fact Extraction and Verification of Real-World Claims on COVID-19 Pandemic**Arkadiy Saakyan, Tuhin Chakrabarty, Smaranda Muresan*2021 · 168 citations*](https://md.research.elamur.ai/free/en/papers/saakyan-2021-covid-fact-fact-extraction-verification/)
90. [**Deduplicating Training Data Mitigates Privacy Risks in Language Models**Nikhil Kandpal, Eric Wallace, Colin Raffel*2022 · 166 citations*](https://md.research.elamur.ai/free/en/papers/kandpal-2022-deduplicating-training-data-mitigates-privacy/)
91. [**MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents**Liyan Tang, Philippe Laban, Greg Durrett*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-minicheck-efficient-fact-checking-llms/)
92. [**FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios**I-Chun Chern, Steffi Chern, Shiqi Chen, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/chern-2023-factool-factuality-detection-generative-ai/)
93. [**CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims**Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, et al.*2020 · 157 citations*](https://md.research.elamur.ai/free/en/papers/diggelmann-2020-climate-fever-dataset-verification-real/)
94. [**Toxic, Hateful, Offensive or Abusive? What Are We Really Classifying? An Empirical Analysis of Hate Speech Datasets**Paula Fortuna, Juan Soler, Leo Wanner*2020 · 157 citations*](https://md.research.elamur.ai/free/en/papers/fortuna-2020-toxic-hateful-offensive-or-abusive/)
95. [**Generating Counter Narratives against Online Hate Speech: Data and Strategies**Serra Sinem Tekiroğlu, Yi-Ling Chung, Marco Guerini*2020 · 153 citations*](https://md.research.elamur.ai/free/en/papers/tekiroglu-2020-generating-counter-narratives-against-online/)
96. [**A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking**Andreas Hanselowski, Christian Stab, Claudia Schulz, et al.*2019 · 147 citations*](https://md.research.elamur.ai/free/en/papers/hanselowski-2019-richly-annotated-corpus-different-tasks/)
97. [**Fact-Checking Complex Claims with Program-Guided Reasoning**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 146 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/)
98. [**Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks**Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, et al.*2022 · 145 citations*](https://md.research.elamur.ai/free/en/papers/mireshghallah-2022-quantifying-privacy-risks-masked-language/)
99. [**Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey Design**Lindia Tjuatja, Valerie Chen, Tongshuang Wu, et al.*2024 · 136 citations*](https://md.research.elamur.ai/free/en/papers/tjuatja-2024-do-llms-exhibit-human-like/)
100. [**A Retrospective Analysis of the Fake News Challenge Stance-Detection Task**Andreas Hanselowski, Avinesh PVS, Benjamin Schiller, et al.*2018 · 133 citations*](https://md.research.elamur.ai/free/en/papers/hanselowski-2018-retrospective-analysis-fake-news-challenge/)
101. [**Evidence-based Fact-Checking of Health-related Claims**Mourad Sarrouti, Asma Ben Abacha, Yassine Mrabet, et al.*2021 · 129 citations*](https://md.research.elamur.ai/free/en/papers/sarrouti-2021-evidence-based-fact-checking-health/)
102. [**Knowledge Unlearning for Mitigating Privacy Risks in Language Models**Joel Jang, Dongkeun Yoon, Sohee Yang, et al.*2022 · 126 citations*](https://md.research.elamur.ai/free/en/papers/jang-2022-knowledge-unlearning-mitigating-privacy-risks/)
103. [**LM vs LM: Detecting Factual Errors via Cross Examination**Roi Cohen, May Hamri, Mor Geva, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/cohen-2023-lm-vs-lm-detecting-factual/)
104. [**Fine-tuning Language Models for Factuality**Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-fine-tuning-language-models-factuality/)
105. [**Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabic**Firoj Alam, Hamdy Mubarak, Wajdi Zaghouani, et al.*2022 · 119 citations*](https://md.research.elamur.ai/free/en/papers/alam-2022-overview-wanlp-2022-shared-task/)
106. [**X-Fact: A New Benchmark Dataset for Multilingual Fact Checking**Ashim Gupta, Vivek Srikumar*2021 · 119 citations*](https://md.research.elamur.ai/free/en/papers/gupta-2021-x-fact-new-benchmark-dataset/)
107. [**Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech**Margherita Fanton, Helena Bonaldi, Serra Sinem Tekiroğlu, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/fanton-2021-human-loop-data-collection-multi/)
108. [**TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification**Wenpeng Yin, Dan Roth*2018 · 114 citations*](https://md.research.elamur.ai/free/en/papers/yin-2018-twowingos-two-wing-optimization-strategy/)
109. [**The Lie Detector: Explorations in the Automatic Recognition of Deceptive Language**Rada Mihalcea, Carlo Strapparava*2009 · 102 citations*](https://md.research.elamur.ai/free/en/papers/mihalcea-2009-lie-detector-explorations-automatic-recognition/)
110. [**DialFact: A Benchmark for Fact-Checking in Dialogue**Prakhar Gupta, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 97 citations*](https://md.research.elamur.ai/free/en/papers/gupta-2022-dialfact-benchmark-fact-checking-dialogue/)
111. [**Fine-grained Hallucination Detection and Editing for Language Models**Abhika Mishra, Akari Asai, Vidhisha Balachandran, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2024-fine-grained-hallucination-detection-editing/)
112. [**Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification**Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/fadeeva-2024-fact-checking-output-large-language/)
113. [**SciFact-Open: Towards open-domain scientific claim verification**David Wadden, Kyle Lo, Bailey Kuehl, et al.*2022 · 93 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2022-scifact-open-open-domain-scientific/)
114. [**Arabic Fake News Detection Based on Deep Contextualized Embedding Models**Ali Bou Nassif, Ashraf Elnagar, Omar Elgendy, et al.*2022 · 90 citations*](https://md.research.elamur.ai/free/en/papers/nassif-2022-arabic-fake-news-detection-based/)
115. [**Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Models**Miaoran Li, Baolin Peng, Michel Galley, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-self-checker-plug-play-modules/)
116. [**Complex Claim Verification with Evidence Retrieved in the Wild**Jifan Chen, Grace Kim, Aniruddh Sriram, et al.*2024 · 84 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-complex-claim-verification-evidence-retrieved/)
117. [**Generating Benchmarks for Factuality Evaluation of Language Models**Dor Muhlgay, Ori Ram, Inbal Magar, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/muhlgay-2024-generating-benchmarks-factuality-evaluation-language/)
118. [**Stance Detection in Fake News A Combined Feature Representation**Bilal Ghanem, Paolo Rosso, Francisco Rangel*2018 · 74 citations*](https://md.research.elamur.ai/free/en/papers/ghanem-2018-stance-detection-fake-news-combined/)
119. [**VeriScore: Evaluating the factuality of verifiable claims in long-form text generation**Yixiao Song, Yekyung Kim, Mohit Iyyer*2024 · 69 citations*](https://md.research.elamur.ai/free/en/papers/song-2024-veriscore-evaluating-factuality-verifiable-claims/)
120. [**Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages**Thomas Mandl, Sandip Modha, Gautam Kishore Shahi, et al.*2021 · 48 citations*](https://md.research.elamur.ai/free/en/papers/mandl-2021-overview-hasoc-subtrack-fire-2021/)
121. [**Large Arabic Twitter Dataset on COVID-19**Sarah Alqurashi, Ahmad Alhindi, Eisa Alanazi*2020 · 46 citations*](https://md.research.elamur.ai/free/en/papers/alqurashi-2020-large-arabic-twitter-dataset-covid/)
122. [**Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in English**Xiangyang Li, Yu Xia, Xiang Long, et al.*2021 · 44 citations*](https://md.research.elamur.ai/free/en/papers/li-2021-exploring-text-transformers-aaai-2021/)
123. [**AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking**Tariq Alhindi, Amal Alabdulkarim, Ali Alshehri, et al.*2021 · 41 citations*](https://md.research.elamur.ai/free/en/papers/alhindi-2021-arastance-multi-country-multi-domain/)
124. [**A Few Topical Tweets are Enough for Effective User Stance Detection**Younes Samih, Kareem Darwish*2021 · 40 citations*](https://md.research.elamur.ai/free/en/papers/samih-2021-few-topical-tweets-are-enough/)
125. [**Dialogue Act-based Breakdown Detection in Negotiation Dialogues**Atsuki Yamaguchi, Kosui Iwasa, Katsuhide Fujita*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/yamaguchi-2021-dialogue-act-based-breakdown-detection/)

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