survey

A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities

Authors:

Reza ZafaraniAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 53, Issue 5

Article No.: 109, Pages 1 - 40

https://doi.org/10.1145/3395046

Published: 28 September 2020 Publication History

Abstract

The explosive growth in fake news and its erosion to democracy, justice, and public trust has increased the demand for fake news detection and intervention. This survey reviews and evaluates methods that can detect fake news from four perspectives: the false knowledge it carries, its writing style, its propagation patterns, and the credibility of its source. The survey also highlights some potential research tasks based on the review. In particular, we identify and detail related fundamental theories across various disciplines to encourage interdisciplinary research on fake news. It is our hope that this survey can facilitate collaborative efforts among experts in computer and information sciences, social sciences, political science, and journalism to research fake news, where such efforts can lead to fake news detection that is not only efficient but, more importantly, explainable.

References

[1]

Jacob Abernethy, Olivier Chapelle, and Carlos Castillo. 2010. Graph regularization methods for web spam detection. Machine Learning 81, 2 (2010), 207--225.

Digital Library

[2]

Sadia Afroz, Michael Brennan, and Rachel Greenstadt. 2012. Detecting hoaxes, frauds, and deception in writing style online. In Proceedings of the IEEE Symposium on Security and Privacy (SP’12). IEEE, Los Alamitos, CA, 461--475.

Digital Library

[3]

Hunt Allcott and Matthew Gentzkow. 2017. Social media and fake news in the 2016 election. Journal of Economic Perspectives 31, 2 (2017), 211--236.

[4]

Yasser Altowim, Dmitri V. Kalashnikov, and Sharad Mehrotra. 2014. Progressive approach to relational entity resolution. Proceedings of the VLDB Endowment 7, 11 (2014), 999--1010.

Digital Library

[5]

Sanjeev Arora, Yingyu Liang, and Tengyu Ma. 2017. A simple but tough-to-beat baseline for sentence embeddings. In Proceedings of the 5th International Conference on Learning Representations (ICLR’17).

[6]

Blake E. Ashforth and Fred Mael. 1989. Social identity theory and the organization. Academy of Management Review 14, 1 (1989), 20--39.

[7]

Abolfazl Asudeh, H. V. Jagadish, You Will Wu, and Cong Yu. 2020. On detecting cherry-picked trendlines. Proceedings of the VLDB Endowment 13, 6 (2020), 939--952.

Digital Library

[8]

Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2007. DBpedia: A nucleus for a web of open data. In The Semantic Web. Springer, 722--735.

Digital Library

[9]

Péter Bálint and Géza Bálint. 2009. The Semmelweis-reflex. Orvosi Hetilap 150, 30 (2009), 1430.

[10]

Ramy Baly, Georgi Karadzhov, Dimitar Alexandrov, James Glass, and Preslav Nakov. 2018. Predicting factuality of reporting and bias of news media sources. arXiv:1810.01765.

[11]

Sudipta Basu. 1997. The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics 24, 1 (1997), 3--37.

[12]

Krishna Bharat and Monika R. Henzinger. 1998. Improved algorithms for topic distillation in a hyperlinked environment. In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York, NY, 104--111.

[13]

Indrajit Bhattacharya and Lise Getoor. 2007. Collective entity resolution in relational data. ACM Transactions on Knowledge Discovery from Data 1, 1 (2007), 5.

[14]

Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, and Junzhou Huang. 2020. Rumor detection on social media with bi-directional graph convolutional networks. arXiv:2001.06362.

[15]

Lawrence E. Boehm. 1994. The validity effect: A search for mediating variables. Personality and Social Psychology Bulletin 20, 3 (1994), 285--293.

[16]

Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008. Freebase: A collaboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data. ACM, New York, NY, 1247--1250.

Digital Library

[17]

Gary D. Bond, Rebecka D. Holman, Jamie-Ann L. Eggert, Lassiter F. Speller, Olivia N. Garcia, Sasha C. Mejia, Kohlby W. Mcinnes, Eleny C. Ceniceros, and Rebecca Rustige. 2017. ‘Lyin’ Ted’,‘Crooked Hillary’, and ‘Deceptive Donald’: Language of lies in the 2016 US presidential debates. Applied Cognitive Psychology 31, 6 (2017), 668--677.

[18]

Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Advances in Neural Information Processing Systems. 2787--2795.

[19]

Stephen Boyd, Neal Parikh, Eric Chu, Borja Peleato, and Jonathan Eckstein. 2011. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends® in Machine Learning 3, 1 (2011), 1--122.

Digital Library

[20]

Chiyu Cai, Linjing Li, and Daniel Zeng. 2017. Detecting social bots by jointly modeling deep behavior and content information. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. ACM, New York, NY, 1995--1998.

Digital Library

[21]

Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R. Hruschka Jr., and Tom M. Mitchell. 2010. Toward an architecture for never-ending language learning. In Proceedings of the 24th AAAI Conference on Artificial Intelligence (AAA’10), Vol. 5. 3.

[22]

Sonia Castelo, Thais Almeida, Anas Elghafari, Aécio Santos, Kien Pham, Eduardo Nakamura, and Juliana Freire. 2019. A topic-agnostic approach for identifying fake news pages. In Companion Proceedings of the 2019 World Wide Web Conference. ACM, New York, NY, 975--980.

Digital Library

[23]

Carlos Castillo, Marcelo Mendoza, and Barbara Poblete. 2011. Information credibility on Twitter. In Proceedings of the 20th International Conference on World Wide Web. ACM, New York, NY, 675--684.

Digital Library

[24]

Tianqi Chen and Carlos Guestrin. 2016. XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, 785--794.

Digital Library

[25]

Yimin Chen, Niall J. Conroy, and Victoria L. Rubin. 2015. Misleading online content: Recognizing clickbait as “false news.” In Proceedings of the 2015 ACM Workshop on Multimodal Deception Detection. ACM, New York, NY, 15--19.

[26]

Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv:1406.1078.

[27]

Peter Christen. 2008. Automatic record linkage using seeded nearest neighbour and support vector machine classification. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, 151--159.

Digital Library

[28]

Giovanni Luca Ciampaglia, Prashant Shiralkar, Luis M. Rocha, Johan Bollen, Filippo Menczer, and Alessandro Flammini. 2015. Computational fact checking from knowledge networks. PloS One 10, 6 (2015), e0128193.

[29]

Sarah Cohen, James T. Hamilton, and Fred Turner. 2011. Computational journalism. Communications of the ACM 54, 10 (2011), 66--71.

Digital Library

[30]

Niall J. Conroy, Victoria L. Rubin, and Yimin Chen. 2015. Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology 52, 1 (2015), 1--4.

[31]

Clayton Allen Davis, Onur Varol, Emilio Ferrara, Alessandro Flammini, and Filippo Menczer. 2016. BotOrNot: A system to evaluate social bots. In Proceedings of the 25th International Conference Companion on World Wide Web. 273--274.

Digital Library

[32]

Yong Deng. 2015. Generalized evidence theory. Applied Intelligence 43, 3 (2015), 530--543.

Digital Library

[33]

Morton Deutsch and Harold B. Gerard. 1955. A study of normative and informational social influences upon individual judgment.Journal of Abnormal and Social Psychology 51, 3 (1955), 629.

[34]

Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805.

[35]

Shimin Di, Yanyan Shen, and Lei Chen. 2019. Relation extraction via domain-aware transfer learning. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, 1348--1357.

Digital Library

[36]

Xin Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, Kevin Murphy, Thomas Strohmann, Shaohua Sun, and Wei Zhang. 2014. Knowledge Vault: A web-scale approach to probabilistic knowledge fusion. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, 601--610.

Digital Library

[37]

Xin Luna Dong, Evgeniy Gabrilovich, Kevin Murphy, Van Dang, Wilko Horn, Camillo Lugaresi, Shaohua Sun, and Wei Zhang. 2015. Knowledge-based trust: Estimating the trustworthiness of web sources. Proceedings of the VLDB Endowment 8, 9 (2015), 938--949.

Digital Library

[38]

Zhicheng Dou, Ruihua Song, Xiaojie Yuan, and JiRong Wen. 2008. Are click-through data adequate for learning web search rankings? In Proceedings of the 17th ACM Conference on Information and Knowledge Management. ACM, New York, NY, 73--82.

Digital Library

[39]

Mengnan Du, Ninghao Liu, and Xia Hu. 2018. Techniques for interpretable machine learning. arXiv:1808.00033.

[40]

David Dunning, Dale W. Griffin, James D. Milojkovic, and Lee Ross. 1990. The overconfidence effect in social prediction.Journal of Personality and Social Psychology 58, 4 (1990), 568.

[41]

Song Feng, Ritwik Banerjee, and Yejin Choi. 2012. Syntactic stylometry for deception detection. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). 171--175.

Digital Library

[42]

Manuel Fernández-Delgado, Eva Cernadas, Senén Barro, and Dinani Amorim. 2014. Do we need hundreds of classifiers to solve real world classification problems. Journal of Machine Learning Research 15, 1 (2014), 3133--3181.

Digital Library

[43]

Emilio Ferrara. 2017. Disinformation and social bot operations in the run up to the 2017 French presidential election. First Monday 22, 8 (2017). Available at http://firstmonday.org/ojs/index.php/fm/article/view/8005/6516.

[44]

Emilio Ferrara, Onur Varol, Clayton Davis, Filippo Menczer, and Alessandro Flammini. 2016. The rise of social bots. Communications of the ACM 59, 7 (2016), 96--104.

Digital Library

[45]

William Ferreira and Andreas Vlachos. 2016. Emergent: A novel data-set for stance classification. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 1163--1168.

[46]

Dennis Fetterly, Mark Manasse, and Marc Najork. 2005. Detecting phrase-level duplication on the World Wide Web. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, New York, NY, 170--177.

Digital Library

[47]

Robert J. Fisher. 1993. Social desirability bias and the validity of indirect questioning. Journal of Consumer Research 20, 2 (1993), 303--315.

[48]

Jonathan L. Freedman and David O. Sears. 1965. Selective exposure. In Advances in Experimental Social Psychology. Vol. 2. Elsevier, 57--97.

[49]

Nico H. Frijda. 1986. The Emotions. Cambridge University Press.

[50]

Christie M. Fuller, David P. Biros, and Rick L. Wilson. 2009. Decision support for determining veracity via linguistic-based cues. Decision Support Systems 46, 3 (2009), 695--703.

Digital Library

[51]

Lise Getoor and Ashwin Machanavajjhala. 2012. Entity resolution: Theory, practice 8 open challenges. Proceedings of the VLDB Endowment 5, 12 (2012), 2018--2019.

Digital Library

[52]

Sharad Goel, Ashton Anderson, Jake Hofman, and Duncan J. Watts. 2015. The structural virality of online diffusion. Management Science 62, 1 (2015), 180--196.

[53]

Jennifer Golbeck, Matthew Mauriello, Brooke Auxier, Keval H. Bhanushali, Christopher Bonk, Mohamed Amine Bouzaghrane, Cody Buntain, et al. 2018. Fake news vs satire: A dataset and analysis. In Proceedings of the 10th ACM Conference on Web Science. ACM, New York, NY, 17--21.

Digital Library

[54]

Manish Gupta, Peixiang Zhao, and Jiawei Han. 2012. Evaluating event credibility on Twitter. In Proceedings of the 2012 SIAM International Conference on Data Mining. 153--164.

[55]

Zoltán Gyöngyi, Hector Garcia-Molina, and Jan Pedersen. 2004. Combating web spam with TrustRank. In Proceedings of the 30th International Conference on Very Large Data Bases—Volume 30. 576--587.

Digital Library

[56]

Naeemul Hassan, Fatma Arslan, Chengkai Li, and Mark Tremayne. 2017a. Toward automated fact-checking: Detecting check-worthy factual claims by ClaimBuster. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, 1803--1812.

Digital Library

[57]

Naeemul Hassan, Gensheng Zhang, Fatma Arslan, Josue Caraballo, Damian Jimenez, Siddhant Gawsane, Shohedul Hasan, et al. 2017b. ClaimBuster: The first-ever end-to-end fact-checking system. Proceedings of the VLDB Endowment 10, 12 (2017), 1945--1948.

Digital Library

[58]

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 770--778.

[59]

Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long short-term memory. Neural Computation 9, 8 (1997), 1735--1780.

Digital Library

[60]

Johannes Hoffart, Fabian M. Suchanek, Klaus Berberich, and Gerhard Weikum. 2013. YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia. Artificial Intelligence 194 (2013), 28--61.

Digital Library

[61]

Benjamin D. Horne, Jeppe Nørregaard, and Sibel Adalı. 2019. Different spirals of sameness: A study of content sharing in mainstream and alternative media. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 13. 257--266.

[62]

Carl I. Hovland, O. J. Harvey, and Muzafer Sherif. 1957. Assimilation and contrast effects in reactions to communication and attitude change.Journal of Abnormal and Social Psychology 55, 2 (1957), 244.

[63]

Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger. 2017. Densely connected convolutional networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 4700--4708.

[64]

Kathleen Hall Jamieson and Joseph N. Cappella. 2008. Echo Chamber: Rush Limbaugh and the Conservative Media Establishment. Oxford University Press.

[65]

Zhiwei Jin, Juan Cao, Yu-Gang Jiang, and Yongdong Zhang. 2014. News credibility evaluation on microblog with a hierarchical propagation model. In Proceedings of the IEEE International Conference on Data Mining (ICDM’14). IEEE, Los Alamitos, CA, 230--239.

Digital Library

[66]

Zhiwei Jin, Juan Cao, Yongdong Zhang, and Jiebo Luo. 2016. News verification by exploiting conflicting social viewpoints in microblogs. In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI’16). 2972--2978.

[67]

Zhiwei Jin, Juan Cao, Yongdong Zhang, Jianshe Zhou, and Qi Tian. 2017. Novel visual and statistical image features for microblogs news verification. IEEE Transactions on Multimedia 19, 3 (2017), 598--608.

Digital Library

[68]

Nitin Jindal and Bing Liu. 2008. Opinion spam and analysis. In Proceedings of the 2008 International Conference on Web Search and Data Mining. ACM, New York, NY, 219--230.

Digital Library

[69]

Marcia K. Johnson and Carol L. Raye. 1981. Reality monitoring. Psychological Review 88, 1 (1981), 67.

[70]

Edward E. Jones and Daniel McGillis. 1976. Correspondent inferences and the attribution cube: A comparative reappraisal. New Directions in Attribution Research 1 (1976), 389--420.

[71]

Daniel Kahneman and Amos Tversky. 2013. Prospect theory: An analysis of decision under risk. In Handbook of the Fundamentals of Financial Decision Making: Part I. World Scientific, 99--127.

[72]

Bingyi Kang and Yong Deng. 2019. The maximum Deng entropy. IEEE Access 7, 1 (2019), 120758--120765.

[73]

Hamid Karimi and Jiliang Tang. 2019. Learning hierarchical discourse-level structure for fake news detection. arXiv:1903.07389.

[74]

Seyed Mehran Kazemi and David Poole. 2018. Simple embedding for link prediction in knowledge graphs. In Advances in Neural Information Processing Systems. 4284--4295.

[75]

Yoon Kim. 2014. Convolutional neural networks for sentence classification. arXiv:1408.5882.

[76]

Diederik P. Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv:1412.6980.

[77]

Jon M. Kleinberg. 1999. Authoritative sources in a hyperlinked environment. Journal of the ACM 46, 5 (1999), 604--632.

Digital Library

[78]

Elena Kochkina, Maria Liakata, and Arkaitz Zubiaga. 2018. All-in-one: Multi-task learning for rumour verification. arXiv:1806.03713.

[79]

Sotiris B. Kotsiantis, I. Zaharakis, and P. Pintelas. 2007. Supervised machine learning: A review of classification techniques. Emerging Artificial Intelligence Applications in Computer Engineering 160 (2007), 3--24.

Digital Library

[80]

Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2012. ImageNet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems. 1097--1105.

Digital Library

[81]

Nir Kshetri and Jeffrey Voas. 2017. The economics of “fake news.” IT Professional6 (2017), 8--12.

[82]

Adam Kucharski. 2016. Post-truth: Study epidemiology of fake news. Nature 540, 7634 (2016), 525.

[83]

Timur Kuran and Cass R. Sunstein. 1999. Availability cascades and risk regulation. Stanford Law Review 51, 4 (1999), 683--768.

[84]

Sejeong Kwon, Meeyoung Cha, Kyomin Jung, Wei Chen, and Yajun Wang. 2013. Prominent features of rumor propagation in online social media. In Proceedings of the International Conference on Data Mining. IEEE, Los Alamitos, CA.

[85]

Ni Lao and William W. Cohen. 2010. Relational retrieval using a combination of path-constrained random walks. Machine Learning 81, 1 (2010), 53--67.

Digital Library

[86]

David M. J. Lazer, Matthew A. Baum, Yochai Benkler, Adam J. Berinsky, Kelly M. Greenhill, Filippo Menczer, Miriam J. Metzger, et al. 2018. The science of fake news. Science 359, 6380 (2018), 1094--1096.

[87]

Quoc Le and Tomas Mikolov. 2014. Distributed representations of sentences and documents. In Proceedings of the International Conference on Machine Learning. 1188--1196.

Digital Library

[88]

Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature 521, 7553 (2015), 436.

[89]

Yann LeCun, Bernhard Boser, John S. Denker, Donnie Henderson, Richard E. Howard, Wayne Hubbard, and Lawrence D. Jackel. 1989. Backpropagation applied to handwritten zip code recognition. Neural Computation 1, 4 (1989), 541--551.

Digital Library

[90]

Harvey Leibenstein. 1950. Bandwagon, snob, and Veblen effects in the theory of consumers’ demand. Quarterly Journal of Economics 64, 2 (1950), 183--207.

[91]

Hongtao Lin, Jun Yan, Meng Qu, and Xiang Ren. 2019. Learning dual retrieval module for semi-supervised relation extraction. In Proceedings of the World Wide Web Conference. ACM, New York, NY, 1073--1083.

Digital Library

[92]

Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015. Learning entity and relation embeddings for knowledge graph completion. In Proceedings of the 29th AAAI Conference on Artificial Intelligence.

Digital Library

[93]

Xin Liu, Radoslaw Nielek, Paulina Adamska, Adam Wierzbicki, and Karl Aberer. 2015. Towards a highly effective and robust web credibility evaluation system. Decision Support Systems 79 (2015), 99--108.

Digital Library

[94]

Yang Liu and Yi-Fang Brook Wu. 2018. Early detection of fake news on social media through propagation path classification with recurrent and convolutional networks. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI’18).

[95]

Jing Ma, Wei Gao, and Kam-Fai Wong. 2018. Rumor detection on Twitter with tree-structured recursive neural networks. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 1980--1989.

[96]

Colin MacLeod, Andrew Mathews, and Philip Tata. 1986. Attentional bias in emotional disorders.Journal of Abnormal Psychology 95, 1 (1986), 15.

[97]

Steven A. McCornack, Kelly Morrison, Jihyun Esther Paik, Amy M. Wisner, and Xun Zhu. 2014. Information manipulation theory 2: A propositional theory of deceptive discourse production. Journal of Language and Social Psychology 33, 4 (2014), 348--377.

[98]

Miriam J. Metzger, Ethan H. Hartsell, and Andrew J. Flanagin. 2015. Cognitive dissonance or credibility? A comparison of two theoretical explanations for selective exposure to partisan news. Communication Research (2015), 0093650215613136.

[99]

Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv:1301.3781.

[100]

Tim Miller, Piers Howe, and Liz Sonenberg. 2017. Explainable AI: Beware of inmates running the asylum or: How I learnt to stop worrying and love the social and behavioural sciences. arXiv:1712.00547.

[101]

Tanushree Mitra and Eric Gilbert. 2015. CREDBANK: A large-scale social media corpus with associated credibility annotations. In Proceedings of the 9th International AAAI Conference on Web and Social Media.

[102]

Fred Morstatter, Liang Wu, Tahora H. Nazer, Kathleen M. Carley, and Huan Liu. 2016. A new approach to bot detection: Striking the balance between precision and recall. In Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. IEEE, Los Alamitos, CA, 533--540.

[103]

Ndapandula Nakashole, Gerhard Weikum, and Fabian Suchanek. 2012. PATTY: A taxonomy of relational patterns with semantic types. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. 1135--1145.

Digital Library

[104]

Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich. 2016. A review of relational machine learning for knowledge graphs. Proceedings of the IEEE 104, 1 (2016), 11--33.

[105]

Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel. 2012. Factorizing YAGO: Scalable machine learning for linked data. In Proceedings of the 21st International Conference on World Wide Web. ACM, New York, NY, 271--280.

Digital Library

[106]

Raymond S. Nickerson. 1998. Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology 2, 2 (1998), 175.

[107]

Feng Niu, Ce Zhang, Christopher Ré, and Jude Shavlik. 2012. Elementary: Large-scale knowledge-base construction via machine learning and statistical inference. International Journal on Semantic Web and Information Systems 8, 3 (2012), 42--73.

Digital Library

[108]

Jeppe Nørregaard, Benjamin D. Horne, and Sibel Adalı. 2019. NELA-GT-2018: A large multi-labelled news dataset for the study of misinformation in news articles. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 13. 630--638.

[109]

Alexandros Ntoulas, Marc Najork, Mark Manasse, and Dennis Fetterly. 2006. Detecting spam web pages through content analysis. In Proceedings of the 15th International Conference on World Wide Web. ACM, New York, NY, 83--92.

Digital Library

[110]

Alexandra Olteanu, Carlos Castillo, Fernando Diaz, and Emre Kiciman. 2019. Social data: Biases, methodological pitfalls, and ethical boundaries. Frontiers in Big Data 2 (2019), 13.

[111]

Ray Oshikawa, Jing Qian, and William Yang Wang. 2018. A survey on natural language processing for fake news detection. arXiv:1811.00770.

[112]

Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. 1999. The PageRank Citation Ranking: Bringing Order to the Web. Technical Report. Stanford InfoLab.

[113]

Gabriella Pasi, Marco Viviani, and Alexandre Carton. 2019. A multi-criteria decision making approach based on the Choquet integral for assessing the credibility of user-generated content. Information Sciences 503 (2019), 574--588.

[114]

Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. Glove: Global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP’14). 1532--1543.

[115]

Verónica Pérez-Rosas, Bennett Kleinberg, Alexandra Lefevre, and Rada Mihalcea. 2017. Automatic detection of fake news. arXiv:1708.07104.

[116]

David Pogue. 2017. How to stamp out fake news. Scientific American 316, 2 (2017), 24.

[117]

Martin Potthast, Johannes Kiesel, Kevin Reinartz, Janek Bevendorff, and Benno Stein. 2017. A stylometric inquiry into hyperpartisan and fake news. arXiv:1702.05638.

[118]

Emily Pronin, Justin Kruger, Kenneth Savtisky, and Lee Ross. 2001. You don’t know me, but I know you: The illusion of asymmetric insight.Journal of Personality and Social Psychology 81, 4 (2001), 639.

[119]

K. Rapoza. 2017. Can “fake news” impact the stock market? Forbes. Retrieved August 13, 2020 from https://www.forbes.com/sites/kenrapoza/2017/02/26/can-fake-news-impact-the-stock-market/#4b3542d52fac.

[120]

Paul Resnick, Samuel Carton, Souneil Park, Yuncheng Shen, and Nicole Zeffer. 2014. RumorLens: A system for analyzing the impact of rumors and corrections in social media. In Proceedings of the Computational Journalism Conference, Vol. 5.

[121]

Victoria L. Rubin. 2010. On deception and deception detection: Content analysis of computer-mediated stated beliefs. Proceedings of the Association for Information Science and Technology 47, 1 (2010), 1--10.

Digital Library

[122]

Victoria L. Rubin, Yimin Chen, and Niall J. Conroy. 2015. Deception detection for news: Three types of fakes. In Proceedings of the 78th ASIS&T Annual Meeting: Information Science with Impact: Research in and for the Community. 83.

[123]

Mike Schuster and Kuldip K. Paliwal. 1997. Bidirectional recurrent neural networks. IEEE Transactions on Signal Processing 45, 11 (1997), 2673--2681.

Digital Library

[124]

Chengcheng Shao, Giovanni Luca Ciampaglia, Alessandro Flammini, and Filippo Menczer. 2016. Hoaxy: A platform for tracking online misinformation. In Proceedings of the 25th International Conference Companion on World Wide Web. 745--750.

Digital Library

[125]

Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kai-Cheng Yang, Alessandro Flammini, and Filippo Menczer. 2018. The spread of low-credibility content by social bots. Nature Communications 9, 1 (2018), 4787.

[126]

Baoxu Shi and Tim Weninger. 2016. Discriminative predicate path mining for fact checking in knowledge graphs. Knowledge-Based Systems 104 (2016), 123--133.

Digital Library

[127]

Baoxu Shi and Tim Weninger. 2018. Open-world knowledge graph completion. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence.

[128]

Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, and Huan Liu. 2019a. dEFEND: Explainable fake news detection. In Proceedings of the 26th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’19).

Digital Library

[129]

Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, and Huan Liu. 2018. FakeNewsNet: A data repository with news content, social context and dynamic information for studying fake news on social media. arXiv:1809.01286.

[130]

Kai Shu, Deepak Mahudeswaran, Suhang Wang, and Huan Liu. 2019b. Hierarchical propagation networks for fake news detection: Investigation and exploitation. arXiv:1903.09196.

[131]

Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. 2017. Fake news detection on social media: A data mining perspective. ACM SIGKDD Explorations Newsletter 19, 1 (2017), 22--36.

Digital Library

[132]

Kai Shu, Suhang Wang, and Huan Liu. 2019c. Beyond news contents: The role of social context for fake news detection. In Proceedings of the 12th ACM International Conference on Web Search and Data Mining. ACM, New York, NY, 312--320.

Digital Library

[133]

Michael Siering, Jascha-Alexander Koch, and Amit V. Deokar. 2016. Detecting fraudulent behavior on crowdfunding platforms: The role of linguistic and content-based cues in static and dynamic contexts. Journal of Management Information Systems 33, 2 (2016), 421--455.

[134]

Craig Silverman. 2016. This analysis shows how viral fake election news stories outperformed real news on Facebook. BuzzFeed News 16 (2016). Available at https://www.buzzfeednews.com/article/craigsilverman/viral-fake-election-news-outperformed-real-news-on-facebook.

[135]

Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556.

[136]

Niraj Sitaula, Chilukuri K. Mohan, Jennifer Grygiel, Xinyi Zhou, and Reza Zafarani. 2020. Credibility-based fake news detection. In Disinformation, Misinformation and Fake News in Social Media: Emerging Research Challenges and Opportunities. Springer.

[137]

Alexander Smith and Vladimir Banic. 2016. Fake news: How a partying Macedonian teen earns thousands publishing lies. NBC News 9 (2016). Available at https://www.nbcnews.com/news/world/fake-news-how-partying-macedonian-teen-earns-thousands-publishing-lies-n692451.

[138]

Richard Socher, Danqi Chen, Christopher D. Manning, and Andrew Ng. 2013. Reasoning with neural tensor networks for knowledge base completion. In Advances in Neural Information Processing Systems. 926--934.

[139]

Nikita Spirin and Jiawei Han. 2012. Survey on web spam detection: Principles and algorithms. ACM SIGKDD Explorations Newsletter 13, 2 (2012), 50--64.

Digital Library

[140]

Rebecca C. Steorts, Rob Hall, and Stephen E. Fienberg. 2016. A Bayesian approach to graphical record linkage and deduplication. Journal of the American Statistical Association 111, 516 (2016), 1660--1672.

[141]

Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007. YAGO: A core of semantic knowledge. In Proceedings of the 16th International Conference on World Wide Web. ACM, New York, NY, 697--706.

Digital Library

[142]

Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. 2015. Going deeper with convolutions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1--9.

[143]

Edson C. Tandoc Jr., Zheng Wei Lim, and Richard Ling. 2018. Defining “fake news”: A typology of scholarly definitions. Digital Journalism 6, 2 (2018), 137--153.

[144]

James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018. FEVER: A large-scale dataset for fact extraction and verification. arXiv:1803.05355.

[145]

Rakshit Trivedi, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, Jun Ma, and Hongyuan Zha. 2018. LinkNBed: Multi-graph representation learning with entity linkage. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 252--262.

[146]

Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016. Complex embeddings for simple link prediction. In Proceedings of the International Conference on Machine Learning. 2071--2080.

[147]

Udo Undeutsch. 1967. Beurteilung der glaubhaftigkeit von aussagen. Handbuch der Psychologie 11 (1967), 26--181.

[148]

Onur Varol, Emilio Ferrara, Clayton A. Davis, Filippo Menczer, and Alessandro Flammini. 2017. Online human-bot interactions: Detection, estimation, and characterization. In Proceedings of the 11th International AAAI Conference on Web and Social Media.

[149]

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems. 5998--6008.

[150]

Giulia Vilone and Luca Longo. 2020. Explainable artificial intelligence: A systematic review. arXiv:2006.00093.

[151]

S. Vichy N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, and Karsten M. Borgwardt. 2010. Graph kernels. Journal of Machine Learning Research 11 (April 2010), 1201--1242.

[152]

Marco Viviani and Gabriella Pasi. 2016. A multi-criteria decision making approach for the assessment of information credibility in social media. In Proceedings of the International Workshop on Fuzzy Logic and Applications. 197--207.

[153]

Marco Viviani and Gabriella Pasi. 2017. Credibility in social media: Opinions, news, and health information—A survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 7, 5 (2017), e1209.

[154]

Nguyen Vo and Kyumin Lee. 2018. The rise of guardians: Fact-checking URL recommendation to combat fake news. arXiv:1806.07516.

[155]

Soroush Vosoughi, Deb Roy, and Sinan Aral. 2018. The spread of true and false news online. Science 359, 6380 (2018), 1146--1151.

[156]

Amy B. Wang. 2016. ‘Post-truth’ named 2016 word of the year by Oxford Dictionaries. Washington Post (2016). Available at https://www.washingtonpost.com/news/the-fix/wp/2016/11/16/post-truth-named-2016-word-of-the-year-by-oxford-dictionaries/.

[157]

William Yang Wang. 2017. “Liar, liar pants on fire”: A new benchmark dataset for fake news detection. arXiv:1705.00648.

[158]

Yaqing Wang, Fenglong Ma, Zhiwei Jin, Ye Yuan, Guangxu Xun, Kishlay Jha, Lu Su, and Jing Gao. 2018. EANN: Event adversarial neural networks for multi-modal fake news detection. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, 849--857.

Digital Library

[159]

Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen. 2014. Knowledge graph embedding by translating on hyperplanes. In Proceedings of the 28th AAAI Conference on Artificial Intelligence.

Digital Library

[160]

Andrew Ward, L. Ross, E. Reed, E. Turiel, and T. Brown. 1997. Naive realism in everyday life: Implications for social conflict and misunderstanding. In Values and Knowledge, E. S. Reed, E. Turiel, and T. Brown (Eds.). The Jean Piaget Symposium Series. Lawrence Erlbaum Associates, 103--135.

[161]

Claire Wardle. 2017. Fake news. It’s complicated. First Draft News 16 (2017). Available at https://firstdraftnews.org/latest/fake-news-complicated/.

[162]

Steven Euijong Whang and Hector Garcia-Molina. 2012. Joint entity resolution. In Proceedings of the IEEE 28th International Conference on Data Engineering (ICDE’12). IEEE, Los Alamitos, CA, 294--305.

Digital Library

[163]

Ke Wu, Song Yang, and Kenny Q. Zhu. 2015. False rumors detection on Sina Weibo by propagation structures. In Proceedings of the IEEE 31st International Conference on Data Engineering (ICDE’15). IEEE, Los Alamitos, CA, 651--662.

[164]

Bishan Yang, Wen-Tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2014. Embedding entities and relations for learning and inference in knowledge bases. arXiv:1412.6575.

[165]

Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, and Xia Ben Hu. 2019. XFake: Explainable fake news detector with visualizations. In Proceedings of the World Wide Web Conference. ACM, New York, NY, 3600--3604.

Digital Library

[166]

Junting Ye and Steven Skiena. 2019. MediaRank: Computational ranking of online news sources. arXiv:1903.07581.

[167]

Bowen Yu, Zhenyu Zhang, Tingwen Liu, Bin Wang, Sujian Li, and Quangang Li. 2019. Beyond word attention: Using segment attention in neural relation extraction. In Proceedings of the 28th International Joint Conference on Artificial Intelligence. 5401--5407.

[168]

Reza Zafarani, Mohammad Ali Abbasi, and Huan Liu. 2014. Social Media Mining: An Introduction. Cambridge University Press.

Digital Library

[169]

Reza Zafarani, Xinyi Zhou, Kai Shu, and Huan Liu. 2019. Fake news research: Theories, detection strategies, and open problems. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, 3207--3208.

Digital Library

[170]

Dongsong Zhang, Lina Zhou, Juan Luo Kehoe, and Isil Yakut Kilic. 2016. What online reviewer behaviors really matter? Effects of verbal and nonverbal behaviors on detection of fake online reviews. Journal of Management Information Systems 33, 2 (2016), 456--481.

[171]

Jiawei Zhang, Limeng Cui, Yanjie Fu, and Fisher B. Gouza. 2018. Fake news detection with deep diffusive network model. arXiv:1805.08751.

[172]

Bin Zhou and Jian Pei. 2009. OSD: An online web spam detection system. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’09), Vol. 9.

[173]

Denny Zhou, Olivier Bousquet, Thomas N. Lal, Jason Weston, and Bernhard Schölkopf. 2004a. Learning with local and global consistency. In Advances in Neural Information Processing Systems. 321--328.

[174]

Lina Zhou, Judee K. Burgoon, Jay F. Nunamaker, and Doug Twitchell. 2004b. Automating linguistics-based cues for detecting deception in text-based asynchronous computer-mediated communications. Group Decision and Negotiation 13, 1 (2004), 81--106.

[175]

Xinyi Zhou, Atishay Jain, Vir V. Phoha, and Reza Zafarani. 2019a. Fake news early detection: A theory-driven model. arXiv:1904.11679.

[176]

Xinyi Zhou, Jindi Wu, and Reza Zafarani. 2020. SAFE: Similarity-aware multi-modal fake news detection. In Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining.

[177]

Xinyi Zhou and Reza Zafarani. 2019. Network-based fake news detection: A pattern-driven approach. ACM SIGKDD Explorations Newsletter 21, 2 (2019), 48--60.

Digital Library

[178]

Xinyi Zhou, Reza Zafarani, Kai Shu, and Huan Liu. 2019b. Fake news: Fundamental theories, detection strategies and challenges. In Proceedings of the 12th ACM International Conference on Web Search and Data Mining. ACM, New York, NY, 836--837.

Digital Library

[179]

Arkaitz Zubiaga, Ahmet Aker, Kalina Bontcheva, Maria Liakata, and Rob Procter. 2018. Detection and resolution of rumours in social media: A survey. ACM Computing Surveys 51, 2 (2018), 1--36.

Digital Library

[180]

Miron Zuckerman, Bella M. DePaulo, and Robert Rosenthal. 1981. Verbal and nonverbal communication of deception. In Advances in Experimental Social Psychology. Vol. 14. Elsevier, 1--59.

Cited By

Atchariyachanvanich KSaengkhunthod CKerdnoonwong PChanlekha HCooharojananone N(2024)Improvement of a Machine Learning Model Using a Sentiment Analysis Algorithm to Detect Fake NewsJournal of Cases on Information Technology10.4018/JCIT.34481226:1(1-26)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.4018/JCIT.344812
Ding T(2024)A Rumors Detection Method Using T5-Based Prompt LearningInternational Journal of Data Warehousing and Mining10.4018/IJDWM.34441520:1(1-19)Online publication date: 7-May-2024
https://dl.acm.org/doi/10.4018/IJDWM.344415
Pillai SHu W(2024)Mobile Text Misinformation Identification Using Machine LearningEmerging Technologies and Security in Cloud Computing10.4018/979-8-3693-2081-5.ch010(236-251)Online publication date: 14-Feb-2024
https://doi.org/10.4018/979-8-3693-2081-5.ch010
Show More Cited By

Index Terms

A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities

Recommendations

Fake News Research: Theories, Detection Strategies, and Open Problems
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Fake news has become a global phenomenon due its explosive growth, particularly on social media. The goal of this tutorial is to (1) clearly introduce the concept and characteristics of fake news and how it can be formally differentiated from other ...
Read More
Inroduction on Recent Trends and Perspectives in Fake News Research
Special Issue on Fake News Research
Read More
Fake News, Disinformation, Propaganda, and Media Bias
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management

The rise of Internet and social media changed not only how we consume information, but it also democratized the process of content creation and dissemination, thus making it easily available to anybody. Despite the hugely positive impact, this situation ...
Read More

Comments

Information & Contributors

Information

Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 53, Issue 5

September 2021

782 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3426973

Editor:
Albert Zomaya
University of Sydney, Austraila

Issue’s Table of Contents

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2020

Online AM: 07 May 2020

Accepted: 01 April 2020

Revised: 01 March 2020

Received: 01 December 2018

Published in CSUR Volume 53, Issue 5

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Survey
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

473
Total Citations
View Citations
12,513
Total Downloads

Downloads (Last 12 months)3,301
Downloads (Last 6 weeks)309

Other Metrics

View Author Metrics

Citations

Cited By

Atchariyachanvanich KSaengkhunthod CKerdnoonwong PChanlekha HCooharojananone N(2024)Improvement of a Machine Learning Model Using a Sentiment Analysis Algorithm to Detect Fake NewsJournal of Cases on Information Technology10.4018/JCIT.34481226:1(1-26)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.4018/JCIT.344812
Ding T(2024)A Rumors Detection Method Using T5-Based Prompt LearningInternational Journal of Data Warehousing and Mining10.4018/IJDWM.34441520:1(1-19)Online publication date: 7-May-2024
https://dl.acm.org/doi/10.4018/IJDWM.344415
Pillai SHu W(2024)Mobile Text Misinformation Identification Using Machine LearningEmerging Technologies and Security in Cloud Computing10.4018/979-8-3693-2081-5.ch010(236-251)Online publication date: 14-Feb-2024
https://doi.org/10.4018/979-8-3693-2081-5.ch010
Alghamdi JLin YLuo S(2024)The Power of Context: A Novel Hybrid Context-Aware Fake News Detection ApproachInformation10.3390/info1503012215:3(122)Online publication date: 21-Feb-2024
https://doi.org/10.3390/info15030122
Al-Dulaimi OKurnaz S(2024)A Hybrid CNN-LSTM Approach for Precision Deepfake Image Detection Based on Transfer LearningElectronics10.3390/electronics1309166213:9(1662)Online publication date: 25-Apr-2024
https://doi.org/10.3390/electronics13091662
Soga KYoshida SMuneyasu M(2024)Graph-Based Interpretability for Fake News Detection through Topic- and Propagation-Aware VisualizationComputation10.3390/computation1204008212:4(82)Online publication date: 15-Apr-2024
https://doi.org/10.3390/computation12040082
Danylyk VVysotska V(2024)Information Technology for Detecting Fakes and Propaganda Based on Machine Learning and Sentiment AnalysisQeios10.32388/IZFOXNOnline publication date: 18-Mar-2024
https://doi.org/10.32388/IZFOXN
Pereira MLeithardt V(2024)Fake News Management an Approach Using Collaborative NetworksSSRN Electronic Journal10.2139/ssrn.4807081Online publication date: 2024
https://doi.org/10.2139/ssrn.4807081
Maheshwari HVinay MDogra NPandey S(2024)Machine Learning in the Newsroom: A New Frontier in the Fight Against MisinformationSSRN Electronic Journal10.2139/ssrn.4483866Online publication date: 2024
https://doi.org/10.2139/ssrn.4483866
Davis J(2024)In a Digital World With Generative AI Detection Will Not be EnoughNewhouse Impact Journal10.14305/jn.29960819.2024.1.1.011:1(9-12)Online publication date: 2024
https://doi.org/10.14305/jn.29960819.2024.1.1.01
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Issue’s Table of Contents