Xinyi Zhou
Skip Abstract Section
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.
- Jacob Abernethy, Olivier Chapelle, and Carlos Castillo. 2010. Graph regularization methods for web spam detection. Machine Learning 81, 2 (2010), 207--225.Google Scholar
Digital Library
- 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.Google ScholarDigital Library
- Hunt Allcott and Matthew Gentzkow. 2017. Social media and fake news in the 2016 election. Journal of Economic Perspectives 31, 2 (2017), 211--236.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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).Google Scholar
- Blake E. Ashforth and Fred Mael. 1989. Social identity theory and the organization. Academy of Management Review 14, 1 (1989), 20--39.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- Péter Bálint and Géza Bálint. 2009. The Semmelweis-reflex. Orvosi Hetilap 150, 30 (2009), 1430.Google ScholarCross Ref
- 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.Google Scholar
- Sudipta Basu. 1997. The conservatism principle and the asymmetric timeliness of earnings. Journal of Accounting and Economics 24, 1 (1997), 3--37.Google ScholarCross Ref
- 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.Google Scholar
- Indrajit Bhattacharya and Lise Getoor. 2007. Collective entity resolution in relational data. ACM Transactions on Knowledge Discovery from Data 1, 1 (2007), 5.Google Scholar
- 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.Google Scholar
- Lawrence E. Boehm. 1994. The validity effect: A search for mediating variables. Personality and Social Psychology Bulletin 20, 3 (1994), 285--293.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google Scholar
- 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.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- Sarah Cohen, James T. Hamilton, and Fred Turner. 2011. Computational journalism. Communications of the ACM 54, 10 (2011), 66--71.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- Yong Deng. 2015. Generalized evidence theory. Applied Intelligence 43, 3 (2015), 530--543.Google ScholarDigital Library
- 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.Google Scholar
- Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- Mengnan Du, Ninghao Liu, and Xia Hu. 2018. Techniques for interpretable machine learning. arXiv:1808.00033.Google Scholar
- 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.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- Robert J. Fisher. 1993. Social desirability bias and the validity of indirect questioning. Journal of Consumer Research 20, 2 (1993), 303--315.Google ScholarCross Ref
- Jonathan L. Freedman and David O. Sears. 1965. Selective exposure. In Advances in Experimental Social Psychology. Vol. 2. Elsevier, 57--97.Google Scholar
- Nico H. Frijda. 1986. The Emotions. Cambridge University Press.Google Scholar
- 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.Google ScholarDigital Library
- Lise Getoor and Ashwin Machanavajjhala. 2012. Entity resolution: Theory, practice 8 open challenges. Proceedings of the VLDB Endowment 5, 12 (2012), 2018--2019.Google ScholarDigital Library
- Sharad Goel, Ashton Anderson, Jake Hofman, and Duncan J. Watts. 2015. The structural virality of online diffusion. Management Science 62, 1 (2015), 180--196.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- Sepp Hochreiter and Jürgen Schmidhuber. 1997. Long short-term memory. Neural Computation 9, 8 (1997), 1735--1780.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google Scholar
- 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.Google Scholar
- 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.Google ScholarCross Ref
- Kathleen Hall Jamieson and Joseph N. Cappella. 2008. Echo Chamber: Rush Limbaugh and the Conservative Media Establishment. Oxford University Press.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- Marcia K. Johnson and Carol L. Raye. 1981. Reality monitoring. Psychological Review 88, 1 (1981), 67.Google ScholarCross Ref
- 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.Google Scholar
- 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.Google Scholar
- Bingyi Kang and Yong Deng. 2019. The maximum Deng entropy. IEEE Access 7, 1 (2019), 120758--120765.Google ScholarCross Ref
- Hamid Karimi and Jiliang Tang. 2019. Learning hierarchical discourse-level structure for fake news detection. arXiv:1903.07389.Google Scholar
- Seyed Mehran Kazemi and David Poole. 2018. Simple embedding for link prediction in knowledge graphs. In Advances in Neural Information Processing Systems. 4284--4295.Google Scholar
- Yoon Kim. 2014. Convolutional neural networks for sentence classification. arXiv:1408.5882.Google Scholar
- Diederik P. Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv:1412.6980.Google Scholar
- Jon M. Kleinberg. 1999. Authoritative sources in a hyperlinked environment. Journal of the ACM 46, 5 (1999), 604--632.Google ScholarDigital Library
- Elena Kochkina, Maria Liakata, and Arkaitz Zubiaga. 2018. All-in-one: Multi-task learning for rumour verification. arXiv:1806.03713.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- Nir Kshetri and Jeffrey Voas. 2017. The economics of “fake news.” IT Professional6 (2017), 8--12.Google Scholar
- Adam Kucharski. 2016. Post-truth: Study epidemiology of fake news. Nature 540, 7634 (2016), 525.Google Scholar
- Timur Kuran and Cass R. Sunstein. 1999. Availability cascades and risk regulation. Stanford Law Review 51, 4 (1999), 683--768.Google ScholarCross Ref
- 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.Google ScholarCross Ref
- Ni Lao and William W. Cohen. 2010. Relational retrieval using a combination of path-constrained random walks. Machine Learning 81, 1 (2010), 53--67.Google ScholarDigital Library
- 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.Google Scholar
- Quoc Le and Tomas Mikolov. 2014. Distributed representations of sentences and documents. In Proceedings of the International Conference on Machine Learning. 1188--1196.Google ScholarDigital Library
- Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature 521, 7553 (2015), 436.Google Scholar
- 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.Google ScholarDigital Library
- Harvey Leibenstein. 1950. Bandwagon, snob, and Veblen effects in the theory of consumers’ demand. Quarterly Journal of Economics 64, 2 (1950), 183--207.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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).Google Scholar
- 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.Google ScholarCross Ref
- Colin MacLeod, Andrew Mathews, and Philip Tata. 1986. Attentional bias in emotional disorders.Journal of Abnormal Psychology 95, 1 (1986), 15.Google Scholar
- 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.Google ScholarCross Ref
- 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.Google Scholar
- Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv:1301.3781.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- Raymond S. Nickerson. 1998. Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology 2, 2 (1998), 175.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- Ray Oshikawa, Jing Qian, and William Yang Wang. 2018. A survey on natural language processing for fake news detection. arXiv:1811.00770.Google Scholar
- Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. 1999. The PageRank Citation Ranking: Bringing Order to the Web. Technical Report. Stanford InfoLab.Google Scholar
- 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.Google ScholarCross Ref
- 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.Google Scholar
- Verónica Pérez-Rosas, Bennett Kleinberg, Alexandra Lefevre, and Rada Mihalcea. 2017. Automatic detection of fake news. arXiv:1708.07104.Google Scholar
- David Pogue. 2017. How to stamp out fake news. Scientific American 316, 2 (2017), 24.Google ScholarCross Ref
- Martin Potthast, Johannes Kiesel, Kevin Reinartz, Janek Bevendorff, and Benno Stein. 2017. A stylometric inquiry into hyperpartisan and fake news. arXiv:1702.05638.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google Scholar
- Mike Schuster and Kuldip K. Paliwal. 1997. Bidirectional recurrent neural networks. IEEE Transactions on Signal Processing 45, 11 (1997), 2673--2681.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- Baoxu Shi and Tim Weninger. 2016. Discriminative predicate path mining for fact checking in knowledge graphs. Knowledge-Based Systems 104 (2016), 123--133.Google ScholarDigital Library
- Baoxu Shi and Tim Weninger. 2018. Open-world knowledge graph completion. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence.Google Scholar
- 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).Google ScholarDigital Library
- 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.Google Scholar
- Kai Shu, Deepak Mahudeswaran, Suhang Wang, and Huan Liu. 2019b. Hierarchical propagation networks for fake news detection: Investigation and exploitation. arXiv:1903.09196.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google Scholar
- Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- Nikita Spirin and Jiawei Han. 2012. Survey on web spam detection: Principles and algorithms. ACM SIGKDD Explorations Newsletter 13, 2 (2012), 50--64.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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.Google ScholarCross Ref
- James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018. FEVER: A large-scale dataset for fact extraction and verification. arXiv:1803.05355.Google Scholar
- 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.Google ScholarCross Ref
- 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.Google Scholar
- Udo Undeutsch. 1967. Beurteilung der glaubhaftigkeit von aussagen. Handbuch der Psychologie 11 (1967), 26--181.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- Giulia Vilone and Luca Longo. 2020. Explainable artificial intelligence: A systematic review. arXiv:2006.00093.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google ScholarCross Ref
- Nguyen Vo and Kyumin Lee. 2018. The rise of guardians: Fact-checking URL recommendation to combat fake news. arXiv:1806.07516.Google Scholar
- Soroush Vosoughi, Deb Roy, and Sinan Aral. 2018. The spread of true and false news online. Science 359, 6380 (2018), 1146--1151.Google Scholar
- 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/.Google Scholar
- William Yang Wang. 2017. “Liar, liar pants on fire”: A new benchmark dataset for fake news detection. arXiv:1705.00648.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google Scholar
- Claire Wardle. 2017. Fake news. It’s complicated. First Draft News 16 (2017). Available at https://firstdraftnews.org/latest/fake-news-complicated/.Google Scholar
- 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.Google ScholarDigital Library
- 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.Google Scholar
- 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.Google Scholar
- 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.Google ScholarDigital Library
- Junting Ye and Steven Skiena. 2019. MediaRank: Computational ranking of online news sources. arXiv:1903.07581.Google Scholar
- 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. DOI:https://doi.org/10.24963/ijcai.2019/750Google ScholarCross Ref
- Reza Zafarani, Mohammad Ali Abbasi, and Huan Liu. 2014. Social Media Mining: An Introduction. Cambridge University Press.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarCross Ref
- Jiawei Zhang, Limeng Cui, Yanjie Fu, and Fisher B. Gouza. 2018. Fake news detection with deep diffusive network model. arXiv:1805.08751.Google Scholar
- 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.Google Scholar
- 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.Google Scholar
- 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.Google ScholarCross Ref
- Xinyi Zhou, Atishay Jain, Vir V. Phoha, and Reza Zafarani. 2019a. Fake news early detection: A theory-driven model. arXiv:1904.11679.Google Scholar
- 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.Google ScholarCross Ref
- Xinyi Zhou and Reza Zafarani. 2019. Network-based fake news detection: A pattern-driven approach. ACM SIGKDD Explorations Newsletter 21, 2 (2019), 48--60.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google ScholarDigital Library
- 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.Google Scholar
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 MiningFake 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 ...
Inroduction on Recent Trends and Perspectives in Fake News Research
Special Issue on Fake News ResearchFake News, Disinformation, Propaganda, and Media Bias
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge ManagementThe 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 ...
Comments