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SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours

Genevieve Gorrell, Elena Kochkina, Maria Liakata, Ahmet Aker, Arkaitz Zubiaga, Kalina Bontcheva, Leon Derczynski
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
However automated support for rumour verification remains in its infancy.  ...  As in RumourEval 2017 we provided a dataset of dubious posts and ensuing conversations in social media, annotated both for stance and veracity.  ...  RumourEval 2017 vs 2019 RumourEval 2019 furthers progress on stance detection and rumour verification, both still unbested NLP tasks.  ... 
doi:10.18653/v1/s19-2147 dblp:conf/semeval/GorrellABDKLZ19 fatcat:uf2rqj7y3rdo7hfpxbs5n6cxea

RumourEval 2019: Determining Rumour Veracity and Support for Rumours [article]

Genevieve Gorrell, Kalina Bontcheva, Leon Derczynski, Elena Kochkina, Maria Liakata, Arkaitz Zubiaga
2018 arXiv   pre-print
This is the proposal for RumourEval-2019, which will run in early 2019 as part of that year's SemEval event.  ...  We therefore propose a continuation in which the veracity of further rumours is determined, and as previously, supportive of this goal, tweets discussing them are classified according to the stance they  ...  Acknowledgements This work is supported by the European Commissions Horizon 2020 research and innovation programme under grant agreement No. 654024, SoBigData.  ... 
arXiv:1809.06683v1 fatcat:smru2o5hxvajrfrmzhvtas7knu

SINAI-DL at SemEval-2019 Task 7: Data Augmentation and Temporal Expressions

Miguel A. García-Cumbreras, Salud María Jiménez-Zafra, Arturo Montejo-Ráez, Manuel Carlos Díaz-Galiano, Estela Saquete
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
This paper describes the participation of the SINAI-DL team at RumourEval (Task 7 in Se-mEval 2019, subtask A: SDQC).  ...  Given a tweet with several replies, our system classifies each reply into either supporting, denying, questioning or commenting on the underlying rumours.  ...  Acknowledgements This research work is partially supported by a grant from the Ministerio de Educación Cultura y Deporte (MECD -scholarship FPU014/00983), the project REDES (TIN2015-65136-C2-1-R) and a  ... 
doi:10.18653/v1/s19-2196 dblp:conf/semeval/Garcia-Cumbreras19 fatcat:kfvqbxi6uzczbfe2jdslah3lwe

BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers [article]

Martin Fajcik, Lukáš Burget, Pavel Smrz
2019 arXiv   pre-print
This paper describes our system submitted to SemEval 2019 Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours, Subtask A (Gorrell et al., 2019).  ...  We formulate the problem as a stance classification, determining the rumour stance of a post with respect to the previous thread post and the source thread post.  ...  Acknowledgments This work was supported by [Acknowledgments will be filled upon acceptance.]  ... 
arXiv:1902.10126v2 fatcat:7cksnclpebdsbpyfonwcc7u3sq

BLCU_NLP at SemEval-2019 Task 7: An Inference Chain-based GPT Model for Rumour Evaluation

Ruoyao Yang, Wanying Xie, Chunhua Liu, Dong Yu
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
Researchers have been paying increasing attention to rumour evaluation due to the rapid spread of unsubstantiated rumours on social media platforms, including SemEval 2019 task 7.  ...  However, labelled data for learning rumour veracity is scarce, and labels in rumour stance data are highly disproportionate, making it challenging for a model to perform supervised-learning adequately.  ...  Academic Talents Support Program for the Young and Middle-Aged.  ... 
doi:10.18653/v1/s19-2191 dblp:conf/semeval/YangXLY19 fatcat:dxnozobq6bf3xhfib7kjkynhni

BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers

Martin Fajcik, Pavel Smrz, Lukas Burget
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
This paper describes our system submitted to SemEval 2019 Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours, Subtask A (Gorrell et al., 2019).  ...  We formulate the problem as a stance classification, determining the rumour stance of a post with respect to the previous thread post and the source thread post.  ...  Acknowledgments This work was supported by the Czech Ministry of Education, Youth and Sports, subprogram INTER-COST, project code: LTC18054.  ... 
doi:10.18653/v1/s19-2192 dblp:conf/semeval/FajcikSB19 fatcat:husjjqbrwbcc3nbk2ilvm6txoa

AndrejJan at SemEval-2019 Task 7: A Fusion Approach for Exploring the Key Factors pertaining to Rumour Analysis

Andrej Janchevski, Sonja Gievska
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
This paper contributes to the research efforts of automatically determining the veracity of rumourous tweets and classifying their replies according to stance.  ...  , metadata and user profiles could complement the linguistic analysis of the written content for the task at hand.  ...  The same model was used to create our final submission for SemEval Task 7.  ... 
doi:10.18653/v1/s19-2190 dblp:conf/semeval/JanchevskiG19 fatcat:uybh7yo3yrddtazlycliwwmf4u

UPV-28-UNITO at SemEval-2019 Task 7: Exploiting Post's Nesting and Syntax Information for Rumor Stance Classification

Bilal Ghanem, Alessandra Teresa Cignarella, Cristina Bosco, Paolo Rosso, Francisco Manuel Rangel Pardo
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
In the present paper we describe the UPV-28-UNITO system's submission to the Ru-morEval 2019 shared task.  ...  The approach we applied for addressing both the subtasks of the contest exploits both classical machine learning algorithms and word embeddings, and it is based on diverse groups of features: stylistic  ...  Acknowledgments The work of Cristina Bosco was partially funded by Progetto di Ateneo/CSP 2016 (Immigrants, Hate and Prejudice in Social Media, S1618L2BOSC01).  ... 
doi:10.18653/v1/s19-2197 dblp:conf/semeval/GhanemCBRP19 fatcat:feotfy5m4fdwznld6f55tzatyq

Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation Structure [article]

Endang Wahyu Pamungkas, Valerio Basile, Viviana Patti
2019 arXiv   pre-print
Some users take a definite stance, supporting or denying the rumour at issue, while others just comment it, or ask for additional evidence related to the veracity of the rumour.  ...  On this line, a new shared task has been proposed at SemEval-2017 (Task 8, SubTask A), which is focused on rumour stance classification in English tweets.  ...  ACKNOWLEDGEMENTS Endang Wahyu Pamungkas, Valerio Basile and Viviana Patti were partially funded by Progetto di Ateneo/CSP 2016 (Immigrants, Hate and Prejudice in Social Media, S1618_L2_BOSC_01).  ... 
arXiv:1901.01911v1 fatcat:sbqariqvtvhnhfw3vznwziiu6a

Gradual Argumentation Evaluation for Stance Aggregation in Automated Fake News Detection

Neema Kotonya, Francesca Toni
2019 Proceedings of the 6th Workshop on Argument Mining  
The task involves determining the point of view or stance -for or against -a text takes towards a claim.  ...  One very important stage in employing stance detection for fake news detection is the aggregation of multiple stance labels from different text sources in order to compute a prediction for the veracity  ...  RumourEval Task A and Task B Task 8 of SemEval 2017 focused on verifying rumours pertaining to a number of tweets regarding eight contentious topics from current events, captured in the RumourEval dataset  ... 
doi:10.18653/v1/w19-4518 dblp:conf/argmining/KotonyaT19 fatcat:jbaxkihxbjd3pjodnnht2zpdo4

A Survey on Stance Detection for Mis- and Disinformation Identification [article]

Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein
2021 arXiv   pre-print
Stance detection has been framed in different ways in the literature, including (a) as a component of fact-checking, rumour detection, and detecting previously fact-checked claims, or (b) as a task in  ...  While there have been prior efforts to contrast stance detection with other related tasks such as argumentation mining and sentiment analysis, there has been no survey examining the relationship between  ...  features to predict the veracity of the rumour ranking 3rd in stance detection, and 1st in veracity classification (RumourEval '19) .  ... 
arXiv:2103.00242v2 fatcat:5a7uwxjvonhpxaamxobzjvyzm4

FTR-18: Collecting rumours on football transfer news [article]

Danielle Caled, Mário J. Silva
2018 arXiv   pre-print
FTR-18 is suited for rumour classification tasks and allows the research on the linguistic patterns used in sports journalism.  ...  The proposed dataset includes transfer articles written in English, Spanish and Portuguese. It also comprises Twitter reactions related to the transfer rumours.  ...  The PHEME-RSD was employed in the Semantic Evaluation (SemEval) 2017 competition, Task 8 RumourEval 5 [2] .  ... 
arXiv:1812.00778v1 fatcat:5q5w5vezufderbxsfq5a5ppxyy

ReINTEL Challenge 2020: Exploiting Transfer Learning Models for Reliable Intelligence Identification on Vietnamese Social Network Sites [article]

Kim Thi-Thanh Nguyen, Kiet Van Nguyen
2021 arXiv   pre-print
This paper presents the system that we propose for the Reliable Intelligence Indentification on Vietnamese Social Network Sites (ReINTEL) task of the Vietnamese Language and Speech Processing 2020 (VLSP  ...  2020) Shared Task.  ...  Many shared-task to detect rumors were held, such as SemEval-2017 Task 8: Determining rumour veracity and support for rumours (Derczynski et al., 2017) and SemEval-2019 Task 7: RumourEval, Determining  ... 
arXiv:2102.10794v3 fatcat:epvxrfvu4fb6bdagq4jvt2qiry

Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter [article]

Costanza Conforti and Jakob Berndt and Mohammad Taher Pilehvar and Chryssi Giannitsarou and Flavio Toxvaerd and Nigel Collier
2020 arXiv   pre-print
All the annotations are carried out by experts; therefore, the dataset constitutes a high-quality and reliable benchmark for future research in stance detection.  ...  Acknowledgments We thank the anonymous reviewers of this paper for their efforts and for the constructive comments and suggestions.  ...  CC is grateful to NERC DREAM CDT (grant no. 1945246) for partially funding this work. CG and FT are thankful to the Cambridge Endowment for Research in Finance (CERF).  ... 
arXiv:2005.00388v1 fatcat:rkulvqxjvrc4th4njspxnvbtmq

Stance Detection on Social Media: State of the Art and Trends [article]

Abeer AlDayel, Walid Magdy
2020 arXiv   pre-print
Stance detection on social media is an emerging opinion mining paradigm for various social and political applications wheresentiment analysis might be seen sub-optimal.  ...  An exhaustive review of stance detection techniques on social media ispresented, including the task definition, the different types of targets in stance detection, the features set used, and the variousmachine  ...  RumourEval 2019-Task A Claim-based The Veracity of a rumour Tweets Various topics Stance(originating rumourous, tweets reply)= {deny, support, commenting} 5216 train- ing tweets Hyperpartisan  ... 
arXiv:2006.03644v1 fatcat:hw3qqg2k3vbkjodef764c46ajy
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