Bibliography

[1] Mohammad Ali Abbasi and Huan Liu. Measuring user credibility in social media. In

SBP, pages 441–448, Springer, 2013. DOI: 10.1007/978-3-642-37210-0_48 47

[2] Sadia Afroz, Michael Brennan, and Rachel Greenstadt. Detecting hoaxes, frauds, and

deception in writing style online. In ISSP, 2012. DOI: 10.1109/sp.2012.34 17

[3] Anderson, Jonathan. Lix and rix: Variations on a little-known readability index, Journal

of Reading, 26(6), pages 490–496, JSTOR, 1983. 18

[4] Ameeta Agrawal, Aijun An, and Manos Papagelis. Learning emotion-enriched word

representations. In Proc. of the 27th International Conference on Computational Linguistics,

pages 950–961, 2018. 36

[5] Hadeer Ahmed, Issa Traore, and Sherif Saad. Detection of online fake news using n-

gram analysis and machine learning techniques. In International Conference on Intelligent,

Secure, and Dependable Systems in Distributed and Cloud Environments, pages 127–138,

Springer, 2017. DOI: 10.1007/978-3-319-69155-8_9 9

[6] Hunt Allcott and Matthew Gentzkow. Social media and fake news in the 2016 election.

Technical Report, National Bureau of Economic Research, 2017. DOI: 10.3386/w23089

[7] Solomon E. Asch and H. Guetzkow. Eﬀects of group pressure upon the modiﬁcation

and distortion of judgments. Groups, Leadership, and Men, pages 222–236, 1951. 3

[8] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation

by jointly learning to align and translate. ArXiv Preprint ArXiv:1409.0473, 2014. 12, 74

[9] Meital Balmas. When fake news becomes real: Combined exposure to multiple news

sources and political attitudes of ineﬃcacy, alienation, and cynicism. Communication Re-

search, 41(3):430–454, 2014. DOI: 10.1177/0093650212453600 2

[10] Michele Banko, Michael J. Cafarella, Stephen Soderland, Matthew Broadhead, and

Oren Etzioni. Open information extraction from the Web. In IJCAI, 2007. DOI:

10.1145/1409360.1409378 21

[11] Herbert Bay, Tinne Tuytelaars, and Luc Van Gool. Surf: Speeded up robust fea-

tures. In European Conference on Computer Vision, pages 404–417, Springer, 2006. DOI:

10.1007/11744023_32 15

98 BIBLIOGRAPHY

[12] Kristy Beers Fägersten. Who’s swearing now?: e social aspects of conversational swear-

ing, 2012. 28

[13] Omar Benjelloun, Hector Garcia-Molina, David Menestrina, Qi Su, Steven Euijong

Whang, and Jennifer Widom. Swoosh: A generic approach to entity resolution. VLDB,

2009. DOI: 10.1007/s00778-008-0098-x 23

[14] Alessandro Bessi and Emilio Ferrara. Social bots distort the 2016 us presidential election

online discussion. First Monday, 21(11), 2016. DOI: 10.5210/fm.v21i11.7090 4

[15] Mikhail Bilenko and Raymond J. Mooney. Adaptive duplicate detection using learnable

string similarity measures. In KDD, 2003. DOI: 10.1145/956750.956759 23

[16] Prakhar Biyani, Kostas Tsioutsiouliklis, and John Blackmer. 8 amazing secrets for getting

more clicks: Detecting clickbaits in news streams using article informality. In AAAI, 2016.

[17] Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. Freebase:

A collaboratively created graph database for structuring human knowledge. In Proc. of

the ACM SIGMOD International Conference on Management of Data, pages 1247–1250,

2008. DOI: 10.1145/1376616.1376746 23

[18] Paul R. Brewer, Dannagal Goldthwaite Young, and Michelle Morreale. e impact of real

news about “fake news”: Intertextual processes and political satire. International Journal

of Public Opinion Research, 25(3):323–343, 2013. DOI: 10.1093/ijpor/edt015 2

[19] David Guy Brizan and Abdullah Uz Tansel. A survey of entity resolution and record

linkage methodologies. Communications of the IIMA, 2015. 22

[20] Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Van-

dergheynst. Geometric deep learning: Going beyond Euclidean data. IEEE Signal Pro-

cessing Magazine, 34(4):18–42, 2017. DOI: 10.1109/msp.2017.2693418 48

[21] Juan Cao, Junbo Guo, Xirong Li, Zhiwei Jin, Han Guo, and Jintao Li. Automatic rumor

detection on microblogs: A survey. ArXiv Preprint ArXiv:1807.03505, 2018. 14

[22] Carlos Castillo, Marcelo Mendoza, and Barbara Poblete. Information credibility on twit-

ter. In WWW, 2011. DOI: 10.1145/1963405.1963500 25, 37

[23] Fabio Celli and Massimo Poesio. Pr2: A language independent unsupervised tool for

personality recognition from text. ArXiv Preprint ArXiv:1402.2796, 2014. 26

[24] Huimin Chen, Maosong Sun, Cunchao Tu, Yankai Lin, and Zhiyuan Liu. Neural

sentiment classiﬁcation with user and product attention. In EMNLP, 2016. DOI:

10.18653/v1/d16-1171 74

BIBLIOGRAPHY 99

[25] Yimin Chen, Niall J. Conroy, and Victoria L. Rubin. Misleading online content: Rec-

ognizing clickbait as false news. In Proc. of the ACM on Workshop on Multimodal Deception

Detection, pages 15–19, 2015. DOI: 10.1145/2823465.2823467 17

[26] Justin Cheng, Michael Bernstein, Cristian Danescu-Niculescu-Mizil, and Jure Leskovec.

Anyone can become a troll: Causes of trolling behavior in online discussions. In CSCW,

2017. DOI: 10.1145/2998181.2998213 5

[27] Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi

Bougares, Holger Schwenk, and Yoshua Bengio. Learning phrase representations

using RNN encoder-decoder for statistical machine translation. ArXiv Preprint

ArXiv:1406.1078, 2014. DOI: 10.3115/v1/d14-1179 74

[28] Zi Chu, Steven Gianvecchio, Haining Wang, and Sushil Jajodia. Detecting automation

of twitter accounts: Are you a human, bot, or cyborg? IEEE Transactions on Dependable

and Secure Computing, 9(6):811–824, 2012. DOI: 10.1109/tdsc.2012.75 5

[29] Giovanni Luca Ciampaglia, Prashant Shiralkar, Luis M. Rocha, Johan Bollen, Filippo

Menczer, and Alessandro Flammini. Computational fact checking from knowledge net-

works. PloS One, 10(6):e0128193, 2015. DOI: 10.1371/journal.pone.0141938 22, 72

[30] Niall J. Conroy, Victoria L. Rubin, and Yimin Chen. Automatic deception detection:

Methods for ﬁnding fake news. Proc. of the Association for Information Science and Tech-

nology, 52(1):1–4, 2015. DOI: 10.1002/pra2.2015.145052010082 2

[31] Clayton Allen Davis, Onur Varol, Emilio Ferrara, Alessandro Flammini, and Filippo

Menczer. Botornot: A system to evaluate social bots. In Proc. of the 25th International

Conference Companion on World Wide Web, pages 273–274, International World Wide

Web Conferences Steering Committee, 2016. DOI: 10.1145/2872518.2889302 85

[32] Michela Del Vicario, Alessandro Bessi, Fabiana Zollo, Fabio Petroni, Antonio Scala,

Guido Caldarelli, H. Eugene Stanley, and Walter Quattrociocchi. e spreading of mis-

information online. Proc. of the National Academy of Sciences, 113(3):554–559, 2016. DOI:

10.1073/pnas.1517441113 5

[33] Michela Del Vicario, Gianna Vivaldo, Alessandro Bessi, Fabiana Zollo, Antonio Scala,

Guido Caldarelli, and Walter Quattrociocchi. Echo chambers: Emotional contagion and

group polarization on facebook. Scientiﬁc Reports, 6, 2016. DOI: 10.1038/srep37825 5

[34] Nikos Deligiannis, Tien Huu Do, Duc Minh Nguyen, and Xiao Luo. Deep learning for

geolocating social media users and detecting fake news. https://www.sto.nato.int/p

ublications/.../STO-MP-IST-160/MP-IST-160-S3-5.pdf 48

100 BIBLIOGRAPHY

[35] omas Deselaers, Tobias Gass, Philippe Dreuw, and Hermann Ney. Jointly optimising

relevance and diversity in image retrieval. In Proc. of the ACM International Conference on

Image and Video Retrieval, page 39, 2009. DOI: 10.1145/1646396.1646443 16

[36] Xin Luna Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Kevin Murphy,

Shaohua Sun, and Wei Zhang. From data fusion to knowledge fusion. Proc. of the VLDB

Endowment, 7(10):881–892, 2014. DOI: 10.14778/2732951.2732962 23

[37] Mohamed G. Elfeky, Vassilios S. Verykios, and Ahmed K. Elmagarmid. Tailor: A record

linkage toolbox. In ICDE, 2002. DOI: 10.1109/icde.2002.994694 23

[38] Robert M. Entman. Framing: Toward clariﬁcation of a fractured paradigm. Journal of

Communication, 43(4):51–58, 1993. DOI: 10.1111/j.1460-2466.1993.tb01304.x 3

[39] Ivan P. Fellegi and Alan B. Sunter. A theory for record linkage. Journal of the American

Statistical Association, 1969. DOI: 10.2307/2286061 23

[40] Song Feng, Ritwik Banerjee, and Yejin Choi. Syntactic stylometry for deception detec-

tion. In ACL, pages 171–175, Association for Computational Linguistics, 2012. 17,

[41] Emilio Ferrara, Onur Varol, Clayton Davis, Filippo Menczer, and Alessandro Flam-

mini. e rise of social bots. Communications of the ACM, 59(7):96–104, 2016. DOI:

10.1145/2818717 4

[42] Emilio Ferrara and Zeyao Yang. Quantifying the eﬀect of sentiment on information

diﬀusion in social media. PeerJ Computer Science, 1:e26, 2015. DOI: 10.7717/peerj-cs.26

[43] Johannes Fürnkranz. A study using n-gram features for text categorization. Austrian

Research Institute for Artiﬁcial Intelligence, 3(1998):1–10, 1998. 9

[44] Matthew Gentzkow, Jesse M. Shapiro, and Daniel F. Stone. Media bias in the mar-

ketplace: eory. Technical Report, National Bureau of Economic Research, 2014. DOI:

10.3386/w19880 4, 27

[45] Clayton J. Hutto and Eric Gilbert. Vader: A parsimonious rule-based model for senti-

ment analysis of social media text. 8th International AAAI Conference on Weblogs and Social

Media, 2014. 49, 53

[46] Gisel Bastidas Guacho, Sara Abdali, Neil Shah, and Evangelos E. Papalexakis. Semi-

supervised content-based detection of misinformation via tensor embeddings. In

IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

(ASONAM), pages 322–325, 2018. DOI: 10.1109/asonam.2018.8508241 10

BIBLIOGRAPHY 101

[47] Chuan Guo, Juan Cao, Xueyao Zhang, Kai Shu, and Miao Yu. Exploiting emotions for

fake news detection on social media. ArXiv Preprint ArXiv:1903.01728, 2019. 35

[48] Han Guo, Juan Cao, Yazi Zhang, Junbo Guo, and Jintao Li. Rumor detection

with hierarchical social attention network. In Proc. of the 27th ACM International

Conference on Information and Knowledge Management, pages 943–951, 2018. DOI:

10.1145/3269206.3271709 72

[49] Shashank Gupta, Raghuveer irukovalluru, Manjira Sinha, and Sandya Mannar-

swamy. Cimtdetect: A community infused matrix-tensor coupled factorization based

method for fake news detection. In IEEE/ACM International Conference on Ad-

vances in Social Networks Analysis and Mining (ASONAM), pages 278–281, 2018. DOI:

10.1109/asonam.2018.8508408 43, 44

[50] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for

image recognition. In Proc. of the IEEE Conference on Computer Vision and Pattern Recog-

nition, pages 770–778, 2016. DOI: 10.1109/cvpr.2016.90 16

[51] Heylighen, Francis and Dewaele, Jean-Marc. Formality of language: Deﬁnition, mea-

surement and behavioral determinants, Interner Bericht, Center “Leo Apostel,” Vrije Uni-

versiteit Brüssel, Citeseer, 1999. 18

[52] Johannes Hoﬀart, Fabian M. Suchanek, Klaus Berberich, and Gerhard Weikum. Yago2:

A spatially and temporally enhanced knowledge base from Wikipedia. Artiﬁcial Intelli-

gence, 194:28–61, 2013. DOI: 10.1016/j.artint.2012.06.001 23

[53] Seyedmehdi Hosseinimotlagh and Evangelos E. Papalexakis. Unsupervised content-

based identiﬁcation of fake news articles with tensor decomposition ensembles. 2018.

http://snap.stanford.edu/mis2/files/MIS2_paper_2.pdf 10, 63, 64

[54] Xia Hu, Jiliang Tang, Huiji Gao, and Huan Liu. Unsupervised sentiment analysis with

emotional signals. In Proc. of the 22nd WWW, pages 607–618, International World Wide

Web Conferences Steering Committee, 2013. DOI: 10.1145/2488388.2488442 37

[55] Clayton J. Hutto and Eric Gilbert. Vader: A parsimonious rule-based model for senti-

ment analysis of social media text. In 8th International AAAI Conference on Weblogs and

Social Media, 2014. 36, 67

[56] Cherilyn Ireton and Julie Posetti. Journalism, “fake news” and disinformation, 2018.

https://cdn.isna.ir/d/2019/01/19/0/57816097.pdf 95

[57] Zhiwei Jin, Juan Cao, Han Guo, Yongdong Zhang, and Jiebo Luo. Multimodal fu-

sion with recurrent neural networks for rumor detection on microblogs. In Proc.

of the 25th ACM International Conference on Multimedia, pages 795–816, 2017. DOI:

10.1145/3123266.3123454 16

102 BIBLIOGRAPHY

[58] Zhiwei Jin, Juan Cao, Yu-Gang Jiang, and Yongdong Zhang. News credibility evaluation

on microblog with a hierarchical propagation model. In ICDM, pages 230–239, IEEE,

2014. DOI: 10.1109/icdm.2014.91 92

[59] Zhiwei Jin, Juan Cao, Yongdong Zhang, and Jiebo Luo. News veriﬁcation by exploiting

conﬂicting social viewpoints in microblogs. In AAAI, pages 2972–2978, 2016. 2, 25, 39,

40, 49, 72

[60] Zhiwei Jin, Juan Cao, Yongdong Zhang, Jianshe Zhou, and Qi Tian. Novel visual and

statistical image features for microblogs news veriﬁcation. IEEE Transactions on Multi-

media, 19(3):598–608, 2017. DOI: 10.1109/tmm.2016.2617078 14

[61] Daniel Kahneman and Amos Tversky. Prospect theory: An analysis of decision under

risk. Econometrica: Journal of the Econometric Society, pages 263–291, 1979. 3

[62] Jaap Kamps, Maarten Marx, Robert J. Mokken, and Maarten de Rijke. Using wordnet

to measure semantic orientations of adjectives. In Proc. of the 4th International Conference

on Language Resources and Evaluation, (LREC), Lisbon, Portugal, May 26–28, 2004. 36

[63] Jean-Noel Kapferer. Rumors: Uses, Interpretation and Necessity. Routledge, 2017. DOI:

10.4324/9781315128801 3

[64] Hamid Karimi and Jiliang Tang. Learning hierarchical discourse-level structure for fake

news detection. ArXiv Preprint ArXiv:1903.07389, 2019. 11, 12

[65] Jooyeon Kim, Behzad Tabibian, Alice Oh, Bernhard Schölkopf, and Manuel Gomez-

Rodriguez. Leveraging the crowd to detect and reduce the spread of fake news and

misinformation. In Proc. of the 11th ACM International Conference on Web Search and

Data Mining, pages 324–332, 2018. DOI: 10.1145/3159652.3159734 30

[66] Benjamin King. Step-wise clustering procedures. Journal of the American Statistical Asso-

ciation, 62(317):86–101, 1967. DOI: 10.2307/2282912 16

[67] Diederik P. Kingma and Max Welling. Auto-encoding variational Bayes. ArXiv Preprint

ArXiv:1312.6114, 2013. 86

[68] omas N. Kipf and Max Welling. Semi-supervised classiﬁcation with graph convolu-

tional networks. In ICLR, 2017. 48

[69] Angelika Kirilin and Micheal Strube. Exploiting a speaker’s credibility to detect fake

news. In Proc. of Data Science, Journalism and Media Workshop at KDD, (DSJM), 2018. 12

[70] Günter Klambauer, omas Unterthiner, Andreas Mayr, and Sepp Hochreiter. Self-

normalizing neural networks. In Advances in Neural Information Processing Systems,

pages 971–980, 2017. 49

BIBLIOGRAPHY 103

[71] David O. Klein and Joshua R. Wueller. Fake news: A legal perspective. 2017. https:

//papers.ssrn.com/sol3/papers.cfm?abstract_id=2958790 2

[72] Hanna Köpcke and Erhard Rahm. Frameworks for entity matching: A comparison. Data

and Knowledge Engineering, 2010. DOI: 10.1016/j.datak.2009.10.003 23

[73] Danai Koutra, Tai-You Ke, U. Kang, Duen Horng Polo Chau, Hsing-Kuo Kenneth Pao,

and Christos Faloutsos. Unifying guilt-by-association approaches: eorems and fast

algorithms. In Joint European Conference on Machine Learning and Knowledge Discovery

in Databases, pages 245–260, Springer, 2011. DOI: 10.1007/978-3-642-23783-6_16 63

[74] Juhi Kulshrestha, Motahhare Eslami, Johnnatan Messias, Muhammad Bilal Zafar, Sap-

tarshi Ghosh, Krishna P. Gummadi, and Karrie Karahalios. Quantifying search bias:

Investigating sources of bias for political searches in social media. In CSCW, 2017. DOI:

10.1145/2998181.2998321 27

[75] David M. J. Lazer, Matthew A. Baum, Yochai Benkler, Adam J. Berinsky, Kelly M.

Greenhill, Filippo Menczer, Miriam J. Metzger, Brendan Nyhan, Gordon Pennycook,

David Rothschild, et al. e science of fake news. Science, 359(6380):1094–1096, 2018.

DOI: 10.1126/science.aao2998 2

[76] Quoc Le and Tomas Mikolov. Distributed representations of sentences and documents.

In International Conference on Machine Learning, pages 1188–1196, 2014. 44

[77] Tony Lesce. Scan: Deception detection by scientiﬁc content analysis. Law and Order,

38(8):3–6, 1990. 17

[78] Jiwei Li, Minh-ang Luong, and Dan Jurafsky. A hierarchical neural autoen-

coder for paragraphs and documents. ArXiv Preprint ArXiv:1506.01057, 2015. DOI:

10.3115/v1/p15-1107 12

[79] Yaliang Li, Jing Gao, Chuishi Meng, Qi Li, Lu Su, Bo Zhao, Wei Fan, and Jiawei Han.

A survey on truth discovery. ACM SIGKDD Explorations Newsletter, 17(2):1–16, 2016.

DOI: 10.1145/2897350.2897352 23

[80] Yang Liu and Yi-Fang Brook Wu. Early detection of fake news on social media through

propagation path classiﬁcation with recurrent and convolutional networks. In 32nd AAAI

Conference on Artiﬁcial Intelligence, 2018. 50, 60, 61

[81] Yunfei Long, Qin Lu, Rong Xiang, Minglei Li, and Chu-Ren Huang. Fake news de-

tection through multi-perspective speaker proﬁles. In Proc. of the 8th International Joint

Conference on Natural Language Processing (Volume 2: Short Papers), vol. 2, pages 252–256,

2017. 12

104 BIBLIOGRAPHY

[82] David G. Lowe. Distinctive image features from scale-invariant key-

points. International Journal of Computer Vision, 60(2):91–110, 2004. DOI:

10.1023/b:visi.0000029664.99615.94 15

[83] Jiasen Lu, Jianwei Yang, Dhruv Batra, and Devi Parikh. Hierarchical question-image

co-attention for visual question answering. In NIPS, 2016. 76, 77

[84] Amr Magdy and Nayer Wanas. Web-based statistical fact checking of textual documents.

In Proc. of the 2nd International Workshop on Search and Mining User-Generated Contents,

pages 103–110, ACM, 2010. DOI: 10.1145/1871985.1872002 21

[85] Peter V. Marsden and Noah E. Friedkin. Network studies of social inﬂuence. Sociological

Methods and Research, 22(1):127–151, 1993. DOI: 10.4135/9781452243528.n1 41

[86] Robert R. McCrae, Paul T. Costa, Margarida Pedroso de Lima, António Simões, Fritz

Ostendorf, Alois Angleitner, Iris Marušić, Denis Bratko, Gian Vittorio Caprara, Claudio

Barbaranelli, et al. Age diﬀerences in personality across the adult life span: Parallels in ﬁve

cultures. Developmental Psychology, 35(2):466, 1999. DOI: 10.1037/0012-1649.35.2.466

[87] Miller McPherson, Lynn Smith-Lovin, and James M. Cook. Birds of a feather: Ho-

mophily in social networks. Annual Review of Sociology, 27(1):415–444, 2001. DOI:

10.1146/annurev.soc.27.1.415 41

[88] Nicco Mele, David Lazer, Matthew Baum, Nir Grinberg, Lisa Friedland, Kenneth

Joseph, Will Hobbs, and Carolina Mattsson. Combating fake news: An agenda for

research and action, 2017. https://shorensteincenter.org/wp-content/uploads/

2017/05/Combating-Fake-News-Agenda-for-Research-1.pdf 95

[89] Hugo Mercier. How gullible are we? A review of the evidence from psychology and social

science. Review of General Psychology, 21(2):103–122, 2017. DOI: 10.1037/gpr0000111

[90] Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S. Corrado, and Jeﬀ Dean. Distributed

representations of words and phrases and their compositionality. In NIPS, 2013. 11, 37,

[91] Tanushree Mitra and Eric Gilbert. Credbank: A large-scale social media corpus with

associated credibility annotations. In ICWSM, 2015. 80

[92] Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, and Michael M.

Bronstein. Fake news detection on social media using geometric deep learning. ArXiv

Preprint ArXiv:1902.06673, 2019. 48

BIBLIOGRAPHY 105

[93] Subhabrata Mukherjee and Gerhard Weikum. Leveraging joint interactions for credi-

bility analysis in news communities. In CIKM, 2015. DOI: 10.1145/2806416.2806537

[94] Danny Murphy. Fake news 101. Independently Published, 2019. 95

[95] Eni Mustafaraj and Panagiotis Takis Metaxas. e fake news spreading plague: Was it

preventable? ArXiv Preprint ArXiv:1703.06988, 2017. DOI: 10.1145/3091478.3091523

[96] Mark E. J. Newman. Finding community structure in networks using the eigenvectors

of matrices. Physical Review E, 74(3):036104, 2006. DOI: 10.1103/physreve.74.036104

[97] Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich. A review

of relational machine learning for knowledge graphs. Proc. of the IEEE, 104(1):11–33,

2016. DOI: 10.1109/jproc.2015.2483592 23

[98] Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel. Factorizing yago: Scalable

machine learning for linked data. In Proc. of the 21st International Conference on World

Wide Web, pages 271–280, ACM, 2012. DOI: 10.1145/2187836.2187874 23

[99] Raymond S. Nickerson. Conﬁrmation bias: A ubiquitous phenomenon in many guises.

Review of General Psychology, 2(2):175, 1998. DOI: 10.1037/1089-2680.2.2.175 3, 27

[100] Brendan Nyhan and Jason Reiﬂer. When corrections fail: e persistence of political

misperceptions. Political Behavior, 32(2):303–330, 2010. DOI: 10.1007/s11109-010-

9112-2 3

[101] Aude Oliva and Antonio Torralba. Modeling the shape of the scene: A holistic represen-

tation of the spatial envelope. International Journal of Computer Vision, 42(3):145–175,

2001. DOI: 10.1023/A:1011139631724 15

[102] Ray Oshikawa, Jing Qian, and William Yang Wang. A survey on natural language pro-

cessing for fake news detection. ArXiv Preprint ArXiv:1811.00770, 2018. 9

[103] Evangelos E. Papalexakis and Nicholas D. Sidiropoulos. Co-clustering as multi-

linear decomposition with sparse latent factors. In IEEE International Conference

on Acoustics, Speech and Signal Processing, (ICASSP), pages 2064–2067, 2011. DOI:

10.1109/icassp.2011.5946731 65

[104] Christopher Paul and Miriam Matthews. e Russian ﬁrehose of falsehood pro-

paganda model. http://www.intgovforum.org/multilingual/sites/default/fil

es/webform/RAND_PE198.pdf 5

106 BIBLIOGRAPHY

[105] James W. Pennebaker, Ryan L. Boyd, Kayla Jordan, and Kate Blackburn. e de-

velopment and psychometric properties of LIWC2015. Technical Report, 2015. DOI:

10.15781/T29G6Z 11

[106] Jeﬀrey Pennington, Richard Socher, and Christopher Manning. Glove: Global vectors for

word representation. In Proc. of the Conference on Empirical Methods in Natural Language

Processing, (EMNLP), pages 1532–1543, 2014. DOI: 10.3115/v1/d14-1162 44

[107] Verónica Pérez-Rosas, Bennett Kleinberg, Alexandra Lefevre, and Rada Mihalcea. Au-

tomatic detection of fake news. ArXiv Preprint ArXiv:1708.07104, 2017. 9

[108] Bryan Perozzi, Rami Al-Rfou, and Steven Skiena. Deepwalk: Online learning of social

representations. In Proc. of the 20th ACM SIGKDD International Conference on Knowledge

Discovery and Data Mining, pages 701–710, 2014. DOI: 10.1145/2623330.2623732 43

[109] Trung Tin Pham. A study on deep learning for fake news detection. 2018. https:

//150.65.5.203/dspace/bitstream/10119/15196/3/paper.pdf 12

[110] Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, and Gerhard Weikum. De-

clare: Debunking fake news and false claims using evidence-aware deep learning. ArXiv

Preprint ArXiv:1809.06416, 2018. 69, 70

[111] Martin Potthast, Johannes Kiesel, Kevin Reinartz, Janek Bevendorﬀ, and Benno Stein. A

stylometric inquiry into hyperpartisan and fake news. ArXiv Preprint ArXiv:1702.05638,

2017. 2, 9

[112] Feng Qian, Chengyue Gong, Karishma Sharma, and Yan Liu. Neural user response

generator: Fake news detection with collective user intelligence. Proc. of the 27th Inter-

national Joint Conference on Artiﬁcial Intelligence, pages 3834–3840, AAAI Press, 2018.

DOI: 10.24963/ijcai.2018/533 56, 79

[113] Walter Quattrociocchi, Antonio Scala, and Cass R. Sunstein. Echo chambers on Face-

book. SSRN 2795110, 2016. DOI: 10.2139/ssrn.2795110 5

[114] Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, and Yejin Choi. Truth

of varying shades: Analyzing language in fake news and political fact-checking. In Proc.

of the Conference on Empirical Methods in Natural Language Processing, pages 2931–2937,

2017. DOI: 10.18653/v1/d17-1317 11

[115] Benjamin Riedel, Isabelle Augenstein, Georgios P. Spithourakis, and Sebastian Riedel.

A simple but tough-to-beat baseline for the fake news challenge stance detection task.

ArXiv Preprint ArXiv:1707.03264, 2017. 95

BIBLIOGRAPHY 107

[116] Victoria L. Rubin, Yimin Chen, and Niall J. Conroy. Deception detection for news: ree

types of fakes. Proc. of the Association for Information Science and Technology, 52(1):1–4,

2015. DOI: 10.1002/pra2.2015.145052010083 2

[117] Victoria L. Rubin, Niall J. Conroy, Yimin Chen, and Sarah Cornwell. Fake news or

truth? Using satirical cues to detect potentially misleading news. In Proc. of NAACL-

HLT, pages 7–17, 2016. DOI: 10.18653/v1/w16-0802 2

[118] Victoria L. Rubin and Tatiana Lukoianova. Truth and deception at the rhetorical struc-

ture level. Journal of the Association for Information Science and Technology, 66(5):905–917,

2015. DOI: 10.1002/asi.23216 17

[119] Natali Ruchansky, Sungyong Seo, and Yan Liu. CSI: A hybrid deep model for fake news.

ArXiv Preprint ArXiv:1703.06959, 2017. 11, 44, 45, 51

[120] Giovanni C. Santia and Jake Ryland Williams. Buzzface: A news veracity dataset with

Facebook user commentary and egos. In ICWSM, 2018. 80

[121] Maarten Sap, Gregory Park, Johannes Eichstaedt, Margaret Kern, David Stillwell,

Michal Kosinski, Lyle Ungar, and Hansen Andrew Schwartz. Developing age and gen-

der predictive lexica over social media. In EMNLP, 2014. DOI: 10.3115/v1/d14-1121

[122] H. Andrew Schwartz, Johannes C. Eichstaedt, Margaret L. Kern, Lukasz Dziurzynski,

Stephanie M. Ramones, Megha Agrawal, Achal Shah, Michal Kosinski, David Stillwell,

Martin E. P. Seligman, et al. Personality, gender, and age in the language of social me-

dia: e open-vocabulary approach. PloS One, 8(9):e73791, 2013. DOI: 10.1371/jour-

nal.pone.0073791 26

[123] Norbert Schwarz, Eryn Newman, and William Leach. Making the truth stick and the

myths fade: Lessons from cognitive psychology. Behavioral Science and Policy, 2(1):85–95,

2016. DOI: 10.1353/bsp.2016.0009 3

[124] Jingbo Shang, Jiaming Shen, Tianhang Sun, Xingbang Liu, Anja Gruenheid, Flip Korn,

Ádám D. Lelkes, Cong Yu, and Jiawei Han. Investigating rumor news using agreement-

aware search. In Proc. of the 27th ACM International Conference on Information and Knowl-

edge Management, pages 2117–2125, 2018. DOI: 10.1145/3269206.3272020 95

[125] Chengcheng Shao, Giovanni Luca Ciampaglia, Alessandro Flammini, and Filippo

Menczer. Hoaxy: A platform for tracking online misinformation. In WWW, 2016. DOI:

10.1145/2872518.2890098 85, 86, 90

[126] Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kai-Cheng Yang, Alessan-

dro Flammini, and Filippo Menczer. e spread of low-credibility content by social bots.

Nature Communications, 9(1):4787, 2018. DOI: 10.1038/s41467-018-06930-7 6

108 BIBLIOGRAPHY

[127] Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kaicheng Yang, Alessandro

Flammini, and Filippo Menczer. e spread of low-credibility content by social bots.

ArXiv Preprint ArXiv:1707.07592, 2017. DOI: 10.1038/s41467-018-06930-7 49

[128] Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, and Yan Liu.

Combating fake news: A survey on identiﬁcation and mitigation techniques. ArXiv

Preprint ArXiv:1901.06437, 2019. DOI: 10.1145/3305260 79

[129] Baoxu Shi and Tim Weninger. Fact checking in heterogeneous information networks.

In WWW, 2016. DOI: 10.1145/2872518.2889354 22, 23

[130] Prashant Shiralkar, Alessandro Flammini, Filippo Menczer, and Giovanni Luca

Ciampaglia. Finding streams in knowledge graphs to support fact checking. ArXiv

Preprint ArXiv:1708.07239, 2017. DOI: 10.1109/icdm.2017.105 22

[131] Kai Shu, H. Russell Bernard, and Huan Liu. Studying fake news via network analy-

sis: Detection and mitigation. CoRR, abs/1804.10233, 2018. DOI: 10.1007/978-3-319-

94105-9_3 79

[132] Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, and Huan Liu. Defend: Explain-

able fake news detection. In Proc. of the 25th ACM SIGKDD International Conference on

Knowledge Discovery and Data Mining, 2019. 71, 73

[133] Kai Shu, Deepak Mahudeswaran, and Huan Liu. Fakenewstracker: A tool for fake news

collection, detection, and visualization. Computational and Mathematical Organization

eory, pages 1–12, 2018. DOI: 10.1007/s10588-018-09280-3 51, 86, 88

[134] Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, and Huan Liu. Fake-

newsnet: A data repository with news content, social context and dynamic information

for studying fake news on social media. ArXiv Preprint ArXiv:1809.01286, 2018. 26, 79

[135] Kai Shu, Deepak Mahudeswaran, Suhang Wang, and Huan Liu. Hierarchical propa-

gation networks for fake news detection: Investigation and exploitation. ArXiv Preprint

ArXiv:1903.09196, 2019. 49, 53

[136] Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. Fake news detection

on social media: A data mining perspective. ACM SIGKDD Explorations Newsletter,

19(1):22–36, 2017. DOI: 10.1145/3137597.3137600 2, 43, 44, 72

[137] Kai Shu, Suhang Wang, ai Le, Dongwon Lee, and Huan Liu. Deep headline genera-

tion for clickbait detection. In IEEE International Conference on Data Mining, (ICDM),

pages 467–476, 2018. DOI: 10.1109/icdm.2018.00062 17

[138] Kai Shu, Suhang Wang, and Huan Liu. Exploiting tri-relationship for fake news detec-

tion. ArXiv Preprint ArXiv:1712.07709, 2017. 10

BIBLIOGRAPHY 109

[139] Kai Shu, Suhang Wang, and Huan Liu. Understanding user proﬁles on social media

for fake news detection. In IEEE Conference on Multimedia Information Processing and

Retrieval, (MIPR), pages 430–435, 2018. DOI: 10.1109/mipr.2018.00092 26

[140] Kai Shu, Suhang Wang, and Huan Liu. Understanding user proﬁles on social me-

dia for fake news detection. In 1st IEEE International Workshop on “Fake MultiMedia,”

(FakeMM), 2018. DOI: 10.1109/mipr.2018.00092 46

[141] Kai Shu, Suhang Wang, and Huan Liu. Beyond news contents: e role of social context

for fake news detection. In Proc. of the 12th ACM International Conference on Web Search

and Data Mining, pages 312–320, 2019. DOI: 10.1145/3289600.3290994 41, 47

[142] Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, and Huan Liu. e role of user

proﬁles for fake news detection.

ArXiv Preprint ArXiv:2671079

, 2013.

25, 27

[143] Karen Simonyan and Andrew Zisserman. Very deep convolutional networks for large-

scale image recognition. ArXiv Preprint ArXiv:1409.1556, 2014. 16

[144] Kihyuk Sohn, Honglak Lee, and Xinchen Yan. Learning structured output representation

using deep conditional generative models. In Advances in Neural Information Processing

Systems, pages 3483–3491, 2015. 57

[145] Nitish Srivastava, Geoﬀrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan

Salakhutdinov. Dropout: A simple way to prevent neural networks from overﬁtting.

e Journal of Machine Learning Research, 15(1):1929–1958, 2014. 16

[146] Stefan Stieglitz and Linh Dang-Xuan. Emotions and information diﬀusion in social

media—sentiment of microblogs and sharing behavior. Journal of Management Informa-

tion Systems, 29(4):217–248, 2013. DOI: 10.2753/mis0742-1222290408 35

[147] Eugenio Tacchini, Gabriele Ballarin, Marco L. Della Vedova, Stefano Moret, and Luca

de Alfaro. Some like it hoax: Automated fake news detection in social networks. ArXiv

Preprint ArXiv:1704.07506, 2017. 34, 80

[148] Henri Tajfel and John C. Turner. An integrative theory of intergroup conﬂict. e Social

Psychology of Intergroup Relations, 33(47):74, 1979. 3

[149] Henri Tajfel and John C. Turner. e social identity theory of intergroup behavior. 2004.

DOI: 10.4324/9780203505984-16 3

[150] Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, and Qiaozhu Mei. Line:

Large-scale information network embedding. In Proc. of the 24th International Confer-

ence on World Wide Web, pages 1067–1077, International World Wide Web Conferences

Steering Committee, 2015. DOI: 10.1145/2736277.2741093 43

110 BIBLIOGRAPHY

[151] Andreas or and Erhard Rahm. Moma-a mapping-based object matching system. In

CIDR, 2007. 23

[152] Sebastian Tschiatschek, Adish Singla, Manuel Gomez Rodriguez, Arpit Merchant, and

Andreas Krause. Fake news detection in social networks via crowd signals. In WWW,

2018. DOI: 10.1145/3184558.3188722 31, 32

[153] Amos Tversky and Daniel Kahneman. e framing of decisions and the psychology of

choice. Science, 211(4481):453–458, 1981. DOI: 10.1007/978-1-4613-2391-4_2 3

[154] Amos Tversky and Daniel Kahneman. Advances in prospect theory: Cumulative rep-

resentation of uncertainty. Journal of Risk and Uncertainty, 5(4):297–323, 1992. DOI:

10.1017/cbo9780511803475.004 3

[155] Madeleine Udell, Corinne Horn, Reza Zadeh, Stephen Boyd, et al. Generalized low

rank models. Foundations and Trends® in Machine Learning, 9(1):1–118, 2016. DOI:

10.1561/2200000055 10

[156] Udo Undeutsch. Beurteilung der glaubhaftigkeit von aussagen. Handbuch der Psychologie,

11:26–181, 1967. 17

[157] Emily Van Duyn and Jessica Collier. Priming and fake news: e eﬀects of elite discourse

on evaluations of news media. Mass Communication and Society, 22(1):29–48, 2019. DOI:

10.1080/15205436.2018.1511807 3

[158] Andreas Vlachos and Sebastian Riedel. Fact checking: Task deﬁnition and dataset con-

struction. ACL, 2014. DOI: 10.3115/v1/w14-2508 20

[159] Soroush Vosoughi, Deb Roy, and Sinan Aral. e spread of true and false news online.

Science, 359(6380):1146–1151, 2018. DOI: 10.1126/science.aap9559 49

[160] Aldert Vrij. Criteria-based content analysis: A qualitative review of the ﬁrst 37 studies.

Psychology, Public Policy, and Law, 11(1):3, 2005. DOI: 10.1037/1076-8971.11.1.3 17

[161] Meng Wang, Kuiyuan Yang, Xian-Sheng Hua, and Hong-Jiang Zhang. Towards a rel-

evant and diverse search of social images. IEEE Transactions on Multimedia, 12(8):829–

842, 2010. DOI: 10.1109/tmm.2010.2055045 15

[162] Suhang Wang and Huan Liu. Deep learning for feature representation. Fea-

ture Engineering for Machine Learning and Data Analytics, page 279, 2018. DOI:

10.1201/9781315181080-11 16

[163] William Yang Wang. “Liar, liar pants on ﬁre”: A new benchmark dataset for fake news

detection. ArXiv Preprint ArXiv:1705.00648, 2017. DOI: 10.18653/v1/p17-2067 11,

12, 13, 79

BIBLIOGRAPHY 111

[164] Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, and Shiqiang Yang. Commu-

nity preserving network embedding. In AAAI, pages 203–209, 2017. 43

[165] Yaqing Wang, Fenglong Ma, Zhiwei Jin, Ye Yuan, Guangxu Xun, Kishlay Jha, Lu Su,

and Jing Gao. EANN: Event adversarial neural networks for multi-modal fake news

detection. In Proc. of the 24th ACM SIGKDD International Conference on Knowledge Dis-

covery and Data Mining, pages 849–857, 2018. DOI: 10.1145/3219819.3219903 16, 57,

[166] Andrew Ward, L. Ross, E. Reed, E. Turiel, and T. Brown. Naive realism in everyday life:

Implications for social conﬂict and misunderstanding. Values and Knowledge, pages 103–

135, 1997. 3

[167] Gerhard Weikum. What computers should know, shouldn’t know, and shouldn’t believe.

In WWW, 2017. DOI: 10.1145/3041021.3051120 23

[168] Janyce Wiebe, eresa Wilson, and Claire Cardie. Annotating expressions of opinions

and emotions in language. Language Resources and Evaluation, 39(2–3):165–210, 2005.

DOI: 10.1007/s10579-005-7880-9 36

[169] Liang Wu and Huan Liu. Tracing fake-news footprints: Characterizing social media

messages by how they propagate. Proc. of the 11th ACM International Conference on Web

Search and Data Mining, pages 637–645, 2018. DOI: 10.1145/3159652.3159677 44, 50

[170] Liang Wu, Fred Morstatter, and Huan Liu. SlangSD: Building and using a senti-

ment dictionary of slang words for short-text sentiment classiﬁcation. ArXiv Preprint

ArXiv:1608.05129, 2016. 36

[171] You Wu, Pankaj K. Agarwal, Chengkai Li, Jun Yang, and Cong Yu. Toward compu-

tational fact-checking. VLDB, 7(7):589–600, 2014. DOI: 10.14778/2732286.2732295

[172] Caiming Xiong, Victor Zhong, and Richard Socher. Dynamic coattention networks for

question answering. ArXiv Preprint ArXiv:1611.01604, 2016. 76

[173] Wei Xu, Xin Liu, and Yihong Gong. Document clustering based on non-negative

matrix factorization. In Proc. of the 26th Annual International ACM SIGIR Confer-

ence on Research and Development in Informaion Retrieval, pages 267–273, 2003. DOI:

10.1145/860435.860485 10

[174] Shuo Yang, Kai Shu, Suhang Wang, Renjie Gu, Fan Wu, and Huan Liu. Unsupervised

fake news detection on social media: A generative approach. Proc. of 33rd AAAI Conference

on Artiﬁcial Intelligence, 2019. 65, 66

112 BIBLIOGRAPHY

[175] Yang Yang, Lei Zheng, Jiawei Zhang, Qingcai Cui, Zhoujun Li, and Philip S. Yu.

Ti-CNN: Convolutional neural networks for fake news detection. ArXiv Preprint

ArXiv:1806.00749, 2018. 11

[176] Yuting Yang, Juan Cao, Mingyan Lu, Jintao Li, and Chia-Wen Lin. How to write high-

quality news on social network? Predicting news quality by mining writing style. ArXiv

Preprint ArXiv:1902.04231, 2019. 19

[177] Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. Hi-

erarchical attention networks for document classiﬁcation. In Proc. of the Conference of the

North American Chapter of the Association for Computational Linguistics: Human Language

Technologies, pages 1480–1489, 2016. DOI: 10.18653/v1/n16-1174 12, 74

[178] Tom Young, Devamanyu Hazarika, Soujanya Poria, and Erik Cambria. Recent trends in

deep learning based natural language processing. IEEE Computational Intelligence Mag-

azine, 13(3):55–75, 2018. DOI: 10.1109/mci.2018.2840738 11

[179] Reza Zafarani, Mohammad Ali Abbasi, and Huan Liu. Social Media Mining: An Intro-

duction. Cambridge University Press, 2014. DOI: 10.1017/cbo9781139088510 1

[180] Robert B. Zajonc. Attitudinal eﬀects of mere exposure. Journal of Personality and Social

Psychology, 9(2p2):1, 1968. DOI: 10.1037/h0025848 5

[181] Robert B. Zajonc. Mere exposure: A gateway to the subliminal. Current Directions in

Psychological Science, 10(6):224–228, 2001. DOI: 10.1017/cbo9780511618031.026 5

[182] Qiang Zhang, Aldo Lipani, Shangsong Liang, and Emine Yilmaz. Reply-aided detec-

tion of misinformation via Bayesian deep learning. In Companion Proceedings of the Web

Conference, 2019. DOI: 10.1145/3308558.3313718 12

[183] Xichen Zhang and Ali A. Ghorbani. An overview of online fake news: Characteriza-

tion, detection, and discussion. Information Processing and Management, 2019. DOI:

10.1016/j.ipm.2019.03.004 79

[184] Xing Zhou, Juan Cao, Zhiwei Jin, Fei Xie, Yu Su, Dafeng Chu, Xuehui Cao, and

Junqiang Zhang. Real-time news certiﬁcation system on sina weibo. In Proc. of the

24th International Conference on World Wide Web, pages 983–988, ACM, 2015. DOI:

10.1145/2740908.2742571 92, 93

[185] Xinyi Zhou and Reza Zafarani. Fake news: A survey of research, detection methods, and

opportunities. ArXiv Preprint ArXiv:1812.00315, 2018. 3, 22

[186] Xinyi Zhou, Reza Zafarani, Kai Shu, and Huan Liu. Fake news: Fundamental theories,

detection strategies and challenges. In Proc. of the 12th ACM International Conference on

Web Search and Data Mining, pages 836–837, 2019. DOI: 10.1145/3289600.3291382 2

BIBLIOGRAPHY 113

[187] Xinyi Zhou, Reza Zafarani, Kai Shu, and Huan Liu. Fake news: Fundamental theories,

detection strategies and challenges. In WSDM, 2019. DOI: 10.1145/3289600.3291382