Abstract
The propagation of fake news may influence a large number of people on a wide range of subjects. Once the spread of fake news reached a critical point, relevant initiatives to fight them have emerged. In this paper, we adapt from English a knowledge graph-based method for fact-checking and propose a new one based on Google search, following content-based strategies for tackling deception in Portuguese, differently from what has been previously done in linguistic-based approaches. Our results are promising and indicate new ways to deal with the deceptive content detection issue.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
The data is available at http://tiny.cc/fum86y.
- 3.
Available at http://tiny.cc/zxm86y.
- 4.
- 5.
- 6.
- 7.
References
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: Dbpedia: a nucleus for a web of open data. In: Proceedings of The Semantic Web: 6th International Semantic Web Conference, pp. 722–735 (2007)
Babakar, M., Moy, W.: The state of automated factchecking. Technical report, Full Fact (2016)
Burgoon, J.K., Buller, D.B., Guerrero, L.K., Afifi, W.A., Feldman, C.M.: Interpersonal deception: Xii. information management dimensions underlying deceptive and truthful messages. Commun. Monogr. 63(1), 50–69 (1996)
Chakraborty, A., Paranjape, B., Kakarla, S., Ganguly, N.: Stop clickbait: detecting and preventing clickbaits in online news media. In: Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 9–16 (2016)
Chesney, S., Liakata, M., Poesio, M., Purver, M.: Incongruent headlines: yet another way to mislead your readers. In: Proceedings of the Empirical Methods in Natural Language Processing Workshop: Natural Language Processing Meets Journalism, pp. 56–61 (2017)
Ciampaglia, G.L., Shiralkar, P., Rocha, L.M., Bollen, J., Menczer, F., Flammini, A.: Computational fact checking from knowledge networks. PloS One 10(6), 1–13 (2015)
Cohen, S., Li, C., Yang, J., Yu, C.: Computational journalism: a call to arms to database researchers. In: Proceedings of the 5th Biennial Conference on Innovative Data Systems Research, pp. 148–151 (2011)
Doddington, G., Mitchell, A., Przybocki, M., Ramshaw, L., Strassel, S., Weischedel, R.: The automatic content extraction (ACE) program - tasks, data, and evaluation. In: Proceedings of the Fourth International Conference on Language Resources and Evaluation, pp. 837–840 (2004)
Eysenbach, G., Köhler, C.: How do consumers search for and appraise health information on the world wide web? qualitative study using focus groups, usability tests, and in-depth interviews. BMJ 324(7337), 573–577 (2002)
Habernal, I., Wachsmuth, H., Gurevych, I., Stein, B.: The argument reasoning comprehension task: identification and reconstruction of implicit warrants. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 1 (Long Papers), pp. 1930–1940 (2018)
Hassan, N., et al.: The quest to automate fact-checking. In: Proceedings of the Computation + Journalism Symposium, pp. 1–5 (2015)
Klein, D., Wueller, J.: Fake news: a legal perspective. J. Internet Law 20(10), 6–13 (2017)
McNamee, P., Dang, H.: Overview of the tac 2009 knowledge base population track. In: Proceedings of the Text Analysis Conference, pp. 111–113 (2009)
Monteiro, R.A., Santos, R.L.S., Pardo, T.A.S., de Almeida, T.A., Ruiz, E.E.S., Vale, O.A.: Contributions to the study of fake news in portuguese: new corpus and automatic detection results. In: Proceedings of the Computational Processing of the Portuguese Language Conference, pp. 324–334 (2018)
Nakashole, N., Mitchell, T.M.: Language-aware truth assessment of fact candidates. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (vol. 1: Long Papers). vol. 1, pp. 1009–1019 (2014)
Pérez-Rosas, V., Mihalcea, R.: Experiments in open domain deception detection. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1120–1125 (2015)
Potthast, M., Kiesel, J., Reinartz, K., Bevendorff, J., Stein, B.: A stylometric inquiry into hyperpartisan and fake news. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (vol. 1: Long Papers), pp. 231–240 (2018)
Rashkin, H., Choi, E., Jang, J.Y., Volkova, S., Choi, Y.: Truth of varying shades: analyzing language in fake news and political fact-checking. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2931–2937 (2017)
Rogerson, K.S.: Fact checking the fact checkers: verification web sites, partisanship and sourcing. In: Proceedings of the American Political Science Association Annual Meeting (2013)
Rubin, V.L., Conroy, N.J., Chen, Y.: Towards news verification: deception detection methods for news discourse. In: Proceedings of the Hawaii International Conference on System Sciences, pp. 5–8 (2015)
Rubin, V.L., Conroy, N.J., Chen, Y., Cornwell, S.: Fake news or truth? using satirical cues to detect potentially misleading news. In: Proceedings of 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 7–17 (2016)
Simas, T., Rocha, L.M.: Distance closures on complex networks. Netw. Sci. 3(2), 227–268 (2015)
Thorne, J., Chen, M., Myrianthous, G., Pu, J., Wang, X., Vlachos, A.: Fake news stance detection using stacked ensemble of classifiers. In: Proceedings of the Empirical Methods in Natural Language Processing Workshop: Natural Language Processing meets Journalism, pp. 80–83 (2017)
Thorne, J., Vlachos, A.: Automated fact checking: task formulations, methods and future directions. In: Proceedings of the 27th International Conference on Computational Linguistics, pp. 3346–3359 (2018)
Vlachos, A., Riedel, S.: Fact checking: task definition and dataset construction. In: Proceedings of the ACL Workshop on Language Technologies and Computational Social Science, pp. 18–22 (2014)
Vlachos, A., Riedel, S.: Identification and verification of simple claims about statistical properties. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 2596–2601 (2015)
Zhou, L.: An empirical investigation of deception behavior in instant messaging. IEEE Trans. Prof. Commun. 48(2), 147–160 (2005)
Zubiaga, A., Aker, A., Bontcheva, K., Liakata, M., Procter, R.: Detection and resolution of rumours in social media: a survey. ACM Comput. Surv. 51, 32:1–32:36 (2018)
Acknowledgments
The authors are grateful to CAPES and USP Research Office (PRP 668) for supporting this work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Santos, R.L.d.S., Pardo, T.A.S. (2020). Fact-Checking for Portuguese: Knowledge Graph and Google Search-Based Methods. In: Quaresma, P., Vieira, R., Aluísio, S., Moniz, H., Batista, F., Gonçalves, T. (eds) Computational Processing of the Portuguese Language. PROPOR 2020. Lecture Notes in Computer Science(), vol 12037. Springer, Cham. https://doi.org/10.1007/978-3-030-41505-1_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-41505-1_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-41504-4
Online ISBN: 978-3-030-41505-1
eBook Packages: Computer ScienceComputer Science (R0)