The fake news factor today, in psychology
Article Sidebar
Main Article Content
Abstract
With this article we pretend to define and understand the central aspects of Fake News. This event has gain attention in personal conversations and in the social media. It is important to understand how this phenome happens and how the receptor is persuaded to believe in the massage,so wecan understand the damage it can cause in the society, for example the elections that have been directly affected for this phenome and establish how to prevent it. Based in studies of other authors we understood the motivations and elements necessary to make and disseminate the information. Since fake news look like real ones its easier for people to believe in them without questioning. Considering the difficult and complexity of the combat of fake news, at the end of this article we analyse a few methods that are been used and highlight the favourable points and possible advances.
Downloads
Article Details
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
References
Abbasi, M. A., & Liu, H. (2013). Measuring user credibility in social media. In International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (pp. 441-448). Springer, Berlin, Heidelberg.
Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of economic perspectives, 31(2), 211-36.
BBC (2016). Students ‘solve’ Facebook’s fake news problem in 36 hours. Disponivel em: http://www.bbc.co.uk/newsbeat/article/38013285/students-solve-facebooks-fake-news-problem-in-36-hours.
Bettencourt, L. M., Cintrón-Arias, A., Kaiser, D. I., & Castillo-Chávez, C. (2006). The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models. Physica A: Statistical Mechanics and its Applications, 364, 513-536.
Cantril, H. (2005). The Invasion from Mars. New York: Routledge, https://doi.org/10.4324/9781315132730
Gottfried, J. & Shearer, E. (2016). News Use Across Social Media Platforms 2016, Pew Research Center Journalism & Media. Retrieved from https://www.journalism.org/2016/05/26/news-use-across-socialmedia-platforms-2016/
Jin, F., Dougherty, E., Saraf, P., Cao, Y., & Ramakrishnan, N. (2013, August). Epidemiological modeling of news and rumors on twitter. In Proceedings of the 7th workshop on social network mining and analysis (pp. 1-9).
Kucharski, A. (2016). Study epidemiology of fake news. Nature, 540(7634), 525-525.
Tandoc Jr, E. C., Lim, Z. W., & Ling, R. (2018). Defining “fake news” A typology of scholarly definitions. Digital journalism, 6(2), 137-153.
Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe report, 27.