Rumor Detection on Social Media: Datasets, Methods and Opportunities

Social media platforms have been used for information and news gathering, and they are very valuable in many applications. However, they also lead to the spreading of rumors and fake news. Many efforts have been taken to detect and debunk rumors on social media by analyzing their content and social context using machine learning techniques. This paper gives an overview of the recent studies in the rumor detection field. It provides a comprehensive list of datasets used for rumor detection, and reviews the important studies based on what types of information they exploit and the approaches they take. And more importantly, we also present several new directions for future research.

[1]  Eugenio Tacchini,et al.  Some Like it Hoax: Automated Fake News Detection in Social Networks , 2017, ArXiv.

[2]  Xiaomo Liu,et al.  Real-time Rumor Debunking on Twitter , 2015, CIKM.

[3]  Huan Liu,et al.  Exploiting Tri-Relationship for Fake News Detection , 2017, ArXiv.

[4]  Yongdong Zhang,et al.  News Verification by Exploiting Conflicting Social Viewpoints in Microblogs , 2016, AAAI.

[5]  Xiaomo Liu,et al.  User Behaviors in Newsworthy Rumors: A Case Study of Twitter , 2021, ICWSM.

[6]  Takao Terano,et al.  Detecting rumor patterns in streaming social media , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[7]  Fan Yang,et al.  Automatic detection of rumor on Sina Weibo , 2012, MDS '12.

[8]  Soroush Vosoughi,et al.  Automatic detection and verification of rumors on Twitter , 2015 .

[9]  Arkaitz Zubiaga,et al.  Detection and Resolution of Rumours in Social Media , 2017, ACM Comput. Surv..

[10]  Jintao Li,et al.  Automatic Rumor Detection on Microblogs: A Survey , 2018, ArXiv.

[11]  Arkaitz Zubiaga,et al.  All-in-one: Multi-task Learning for Rumour Verification , 2018, COLING.

[12]  Wei Gao,et al.  Rumor Detection on Twitter with Tree-structured Recursive Neural Networks , 2018, ACL.

[13]  Luo Si,et al.  Rumor Detection by Exploiting User Credibility Information, Attention and Multi-task Learning , 2019, ACL.

[14]  Arkaitz Zubiaga,et al.  Discourse-aware rumour stance classification in social media using sequential classifiers , 2017, Inf. Process. Manag..

[15]  H. Russell Bernard,et al.  Studying Fake News via Network Analysis: Detection and Mitigation , 2018, Lecture Notes in Social Networks.

[16]  Fenglong Ma,et al.  EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection , 2018, KDD.

[17]  Xiaomo Liu,et al.  Real-Time Novel Event Detection from Social Media , 2017, 2017 IEEE 33rd International Conference on Data Engineering (ICDE).

[18]  Samhaa R. El-Beltagy,et al.  NileTMRG at SemEval-2017 Task 8: Determining Rumour and Veracity Support for Rumours on Twitter. , 2017, *SEMEVAL.

[19]  Kai Niu,et al.  Exploiting the topology property of social network for rumor detection , 2015, 2015 12th International Joint Conference on Computer Science and Software Engineering (JCSSE).

[20]  Arkaitz Zubiaga,et al.  Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads , 2015, PloS one.

[21]  Kenny Q. Zhu,et al.  False rumors detection on Sina Weibo by propagation structures , 2015, 2015 IEEE 31st International Conference on Data Engineering.

[22]  Suhang Wang,et al.  Fake News Detection on Social Media: A Data Mining Perspective , 2017, SKDD.

[23]  Huan Liu,et al.  Beyond News Contents: The Role of Social Context for Fake News Detection , 2017, WSDM.

[24]  Barbara Poblete,et al.  Information credibility on twitter , 2011, WWW.

[25]  Wei Gao,et al.  Detect Rumor and Stance Jointly by Neural Multi-task Learning , 2018, WWW.

[26]  Jiawei Han,et al.  Evaluating Event Credibility on Twitter , 2012, SDM.

[27]  Xiaomo Liu,et al.  Reuters tracer: Toward automated news production using large scale social media data , 2017, 2017 IEEE International Conference on Big Data (Big Data).

[28]  Cunchen Tang,et al.  Spotting Rumors via Novelty Detection , 2016, ArXiv.

[29]  Wei Gao,et al.  Detecting Rumors from Microblogs with Recurrent Neural Networks , 2016, IJCAI.

[30]  Luo Si,et al.  eventAI at SemEval-2019 Task 7: Rumor Detection on Social Media by Exploiting Content, User Credibility and Propagation Information , 2019, *SEMEVAL.

[31]  Yang Liu,et al.  Early Detection of Fake News on Social Media Through Propagation Path Classification with Recurrent and Convolutional Networks , 2018, AAAI.

[32]  Yongdong Zhang,et al.  Multimodal Fusion with Recurrent Neural Networks for Rumor Detection on Microblogs , 2017, ACM Multimedia.

[33]  Reza Zafarani,et al.  Fake News: A Survey of Research, Detection Methods, and Opportunities , 2018, ArXiv.

[34]  Chiew Tong Lau,et al.  Behavior deviation: An anomaly detection view of rumor preemption , 2016, 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON).

[35]  Snehasish Banerjee,et al.  Linguistic Predictors of Rumor Veracity on the Internet , 2016 .

[36]  Isabelle Augenstein,et al.  Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM , 2017, *SEMEVAL.

[37]  M. Cha,et al.  Rumor Detection over Varying Time Windows , 2017, PloS one.

[38]  Huan Liu,et al.  FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media , 2018, ArXiv.

[39]  Anupam Joshi,et al.  Faking Sandy: characterizing and identifying fake images on Twitter during Hurricane Sandy , 2013, WWW.

[40]  Dragomir R. Radev,et al.  Rumor has it: Identifying Misinformation in Microblogs , 2011, EMNLP.

[41]  Quan Z. Sheng,et al.  Extreme User and Political Rumor Detection on Twitter , 2016, ADMA.

[42]  Xiaomo Liu,et al.  Reuters Tracer: A Large Scale System of Detecting & Verifying Real-Time News Events from Twitter , 2016, CIKM.

[43]  Chengkai Li,et al.  Toward Automated Fact-Checking: Detecting Check-worthy Factual Claims by ClaimBuster , 2017, KDD.

[44]  Wei Gao,et al.  Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning , 2017, ACL.

[45]  Huan Liu,et al.  FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media , 2018, Big Data.

[46]  Kyomin Jung,et al.  Prominent Features of Rumor Propagation in Online Social Media , 2013, 2013 IEEE 13th International Conference on Data Mining.