Information verification in social networks based on user feedback and news agencies

• Alrubaian M, Al-Qurishi M, Al-Rakhami M, Hassan MM, Alamri A (2017) Reputation-based credibility analysis of Twitter social network users. Concurr Comput Pract Exp 29(7):e3873

  Article  Google Scholar 

• Androutsopoulos I, Prodromos M (2010) A survey of paraphrasing and textual entailment methods. J Artif Intell Res 38:135–187. https://doi.org/10.1613/jair.2985

  Article  MATH  Google Scholar 

• Basak R, Naskar SK, Gelbukh A (2018) A simple hybrid approach to recognizing textual entailment. J Intell Fuzzy Syst 34(4):1–13

  Google Scholar 

• Boididou C, Middleton SE, Jin Z, Papadopoulos S, Dang-Nguyen D-T, Boato G, Kompatsiaris Y (2018) Verifying information with multimedia content on twitter. Multimed Tools Appl 77(12):15545–15571

  Article  Google Scholar 

• Borrajo L, Seara Vieira A, Iglesias EL (2015) TCBR-HMM: an HMM-based text classifier with a CBR system. Appl Soft Comput 26:463–473

  Article  Google Scholar 

• Castillo C, Mendoza M, Poblete B (2011) Information credibility on twitter. In: Proceedings of the 20th international conference on World wide web. ACM, pp 675–684

• Castillo C, Mendoza M, Poblete B (2013) Predicting information credibility in time-sensitive social media. Internet Res 23(5):560–588

  Article  Google Scholar 

• Conroy NJ, Rubin VL, Chen Y (2015) Automatic deception detection: methods for finding fake news. In: Proceedings of the 78th ASIS&T annual meeting: information science with impact: research in and for the community. American Society for Information Science, p 82

• Dagan I, O Glickman (2004) Probabilistic textual entailment: generic applied modeling of language variability. In: PASCAL workshop on learning methods for text understanding and mining. Grenoble

• Derczynski L, Bontcheva K, Liakata M, Procter R, Hoi GW, Zubiaga A (2017) SemEval-2017 Task 8: RumourEval: determining rumour veracity and support for rumours. arXiv:1704.05972v1 [cs.CL] 20 Apr 2017

• Foroozani A, Ebrahimi M (2019) Anomalous information diffusion in social networks: Twitter and Digg. Expert Syst Appl 134:249–266

  Article  Google Scholar 

• Gahirwal M, Moghe S, Kulkarni T, Khakhar D, Bhatia J (2018) Fake news detection. Int J Adv Res Ideas Innov Technol 4(1):817–819

  Google Scholar 

• Gerhart N, Torres R, Negahban A (2017) Combatting fake news: an investigation of individuals’ information verification behaviors on social networking sites. In: Proceedings of the 51st Hawaii international conference on system sciences

• Girard J, Allison M (2008) Information anxiety: fact, fable or fallacy. Electron J Knowl Manag 6(2):111–124

  Google Scholar 

• Guo M, Zhang Y, Zhao D, Liu T (2017) Generating textual entailment using residual LSTMs. In: Chinese computational linguistics and natural language processing based on naturally annotated big data. Springer, Cham, pp 263–272

• Hajli N (2018) Ethical environment in the online communities by information credibility: a social media perspective. J Bus Ethics 149(4):799–810

  Article  Google Scholar 

• Hanselowski A, Zhang H, Li Z, Sorokin D, Schiller B, Schulz C, Gurevych I (2018) Multi-sentence textual entailment for claim verification. In: Proceedings of the first workshop on fact extraction and verification (FEVER), pp 103–108

• Huang G-B (2014) An insight into extreme learning machines: random neurons, random features and kernels. Cognit Comput 6(3):376–390

  Article  Google Scholar 

• Kumar S, Shah N (2018) False information on web and social media: a survey. arXiv:1804.08559v1 [cs.SI] 23 Apr 2018

• Lafferty J, McCallum A, Pereira F (2001) Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the eighteenth international conference on machine learning (ICML-2001)

• Liu L, Huo H, Liu X, Palade V, Peng D, Chen Q (2018) Recognizing textual entailment with attentive reading and writing operations. In: International conference on database systems for advanced applications. Springer, Cham, pp 847–860

• Long Y, Lu Q, Xiang R, Li M, Huang C-R (2017) Fake news detection through multi-perspective speaker profiles. In: Proceedings of the eighth international joint conference on natural language processing, volume 2 short papers, pp 252–256

• Louni A, Subbalakshmi KP (2018) Method and apparatus to identify the source of information or misinformation in large-scale social media networks. U.S. Patent 9,959,365, issued May 1, 2018

• Ma T, Wu C, Xiao C, Sun J (2018) AWE: asymmetric word embedding for textual entailment. arXiv preprint arXiv:1809.04047

• Magnini B, Zanoli R, Dagan I, Eichler K, Neumann G, Noh T-G, Pado S, Stern A, Levy O (2014) The excitement open platform for textual inferences. In: Proceedings of 52nd annual meeting of the association for computational linguistics: system demonstrations, pp 43–48

• Noh T-G, Padó S, Shwartz V, Dagan I, Nastase V, Eichler K, Kotlerman L, Adler M (2015) Multi-level alignments as an extensible representation basis for textual entailment algorithms. In: Proceedings of the fourth joint conference on lexical and computational semantics, pp 193–198

• Oshikawa R, Qian J, Wang VY (2018) A survey on natural language processing for fake news detection. arXiv preprint arXiv:1811.00770

• Padó S, Noh T-G, Stern A, Wang R, Zanoli R (2015) Design and realization of a modular architecture for textual entailment. Nat Lang Eng 21(2):167–200

  Article  Google Scholar 

• Paul M, Sharp R, Surdeanu M (2018) A mostly unlexicalized model for recognizing textual entailment. In: Proceedings of the first workshop on fact extraction and verification (FEVER), pp 166–171

• Pérez-Rosas V, Kleinberg B, Lefevre A, Mihalcea R (2017) Automatic detection of fake news. arXiv preprint arXiv:1708.07104

• Ren H, Li X, Feng W, Wan J (2017) Recognizing textual entailment using inference phenomenon. In: Workshop on Chinese lexical semantics. Springer, Cham, pp 293–302

• Rubin VL, Chen Y, Conroy NJ (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. American Society for Information Science, p 83

• Rubin V, Conroy N, Chen Y, Cornwell S (2016) Fake news or truth? using satirical cues to detect potentially misleading news. In: Proceedings of the second workshop on computational approaches to deception detection, pp 7–17

• Schifferes S, Newman N, Thurman N, Corney D, Göker A, Martin C (2014) Identifying and verifying news through social media: developing a user-centred tool for professional journalists. Digit J 2(3):406–418

  Google Scholar 

• Shen D, Sun J-T, Li H, Yang Q, Chen Z (2007) Document summarization using conditional random fields, IJCAI-07, pp 2862–2867

• Shu K, Sliva A, Wang S, Tang J, Liu H (2017) Fake news detection on social media: a data mining perspective. ACM SIGKDD Explor Newsl 19(1):22–36

  Article  Google Scholar 

• Vedova MD, Tacchini E, Moret S, Ballarin G, DiPierro M, de Alfaro L (2018) Automatic online fake news detection combining content and social signals. In: Proceedings of the 22st conference of open innovations association FRUCT. FRUCT Oy, p 38

• Westerman D, Spence P, Van Der Heide B (2012) A social network as information: the effect of system generated reports of connectedness on credibility on Twitter. Comput Hum Behav 28(1):199–206

  Article  Google Scholar 

• Wurman RS (1989) Information anxiety. Doubleday, New York

  Google Scholar 

• Yin C, Sun Y, Fang Y, Lim K (2018a) Exploring the dual-role of cognitive heuristics and the moderating effect of gender in microblog information credibility evaluation. Inf Technol People 31(3):741–769

  Article  Google Scholar 

• Yin W, Roth D, Schütze H (2018b) End-task oriented textual entailment via deep exploring inter-sentence interactions. arXiv preprint arXiv:1804.08813

• Zanoli R, Colombo S (2017) A transformation-driven approach for recognizing textual entailment. Nat Lang Eng 23(4):507–534

  Article  Google Scholar 

• Zhang X, Ghorbani AA (2019) An overview of online fake news: Characterization, detection, and discussion. Inf Process Manag. https://doi.org/10.1016/j.ipm.2019.03.004

  Article  Google Scholar 

• Zhang C, Gupta A, Kauten C, Deokar AV, Qin X (2019) Detecting fake news for reducing misinformation risks using analytics approaches. Eur J Oper Res 279(3):1036–1052

  Article  Google Scholar 

• Zhao K, Huang L, Ma M (2017) Textual entailment with structured attentions and composition. arXiv preprint arXiv:1701.01126

• Zimmermann M, Jucks R (2018) How experts’ use of medical technical jargon in different types of online health forums affects perceived information credibility: randomized experiment with laypersons. J Med Internet Res 20(1):e30

  Article  Google Scholar 

• Zubiaga A, Aker A, Bontcheva K, Liakata M, Procter R (2017) Detection and resolution of rumours in social media: a survey. arXiv preprint arXiv:1704.00656

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