A Massive Production to the Era of Technology by Social Bots Combating Fake News on Digital Platforms
Keywords:
Social bots, social media, deceptive information, semantic web, social networking, ClaimBusterAbstract
Social networks have revolutionized communication, enabling individuals to connect with a broader audience and express their opinions freely. However, this unprecedented accessibility also opens doors to potential challenges, such as the unintentional spread of misinformation. In this study, we delve into the mechanisms behind the generation of false information and present a thought-provoking vision of a future where social bots autonomously evolve into semantic webs, inundating media platforms with fabricated content. The study begins by acknowledging the power of social networks as a valuable tool for expanding overall exposure. It emphasizes how anyone can utilize these platforms to share their ideas, but also highlights the lurking presence of social bots. These automated entities, often driven by hidden agendas, can exploit the open nature of social media to disseminate misinformation on a large scale. Ultimately, this study serves as a call to action for researchers, policymakers, and technology companies to address the evolving challenges posed by the spread of misinformation on social media. By understanding the methods employed by social bots in generating false information, we can strive to develop robust countermeasures that protect the public’s right to accurate and reliable information, fostering a healthier and more informed digital society.
References
Palen L, Hughes AL. Social media in disaster communication. In: Handbook of disaster research; New York, NY, USA: Springer; 2018. pp. 497–518. doi: 10.1007/978-3-319-63254-4_24.
Verma P, Khanday AM, Rabani ST, Hussain MH, Jamwal DS. Twitter sentiment analysis on Indian government project using R. Int J Recent Technol Eng. 2019; 8 (3): 8338–8341. doi: 10.35940/ijrte.C6612.098319.
Barron L. (2018). US soldiers are accidentally revealing sensitive locations by mapping their exercise routes. [Online] Available at https://time.com/5122495/strava-heatmap-military-bases/
Horton H. (2016). Microsoft deletes’teen girl’AI after it became a Hitler-loving sex robot within 24 hours. [Online] The Telegraph. Available at https://www.telegraph.co.uk/technology/
/03/24/microsofts-teen-girl-ai-turns-into-a-hitler-loving-sex-robot-wit/
Ellison NB, Steinfield C, Lampe C. The benefits of Facebook “friends:” social capital and college students’ use of online social network sites. J Comput Mediated Commun. 2007; 12 (4): 1143–1168. doi: 10.1111/j.1083-6101.2007.00367.x.
Allcott H, Gentzkow M. Social media and fake news in the 2016 election. J Econ Perspect. 2017; 31 (2): 211–236. doi: 10.1257/jep.31.2.211.
Bessi A, Ferrara E. Social bots distort the 2016 US Presidential election online discussion. First Monday. 2016; 21: 11–17.
Suwajanakorn S, Seitz SM, Kemelmacher-Shlizerman I. Synthesizing Obama: learning lip sync from audio. ACM Trans Graph (ToG). 2017; 36 (4): 1–13. doi: 10.1145/3072959.3073640.
Wang P, Angarita R, Renna I. Is this the era of misinformation yet: combining social bots and fake news to deceive the masses. In: Proceedings of the Web conference; 2018. [Online] Available at https://dl.acm.org/doi/fullHtml/10.1145/3184558.3191610
Myers SA, Zhu C, Leskovec J. Information diffusion and external influence in networks. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 2012 August; New York, NY, USA: ACM Digital Library. 2012. 33–41 pp. doi: 10.1145/2339530.2339540.
Kucharski A. Post-truth: Study epidemiology of fake news. Nature. 2016; 540 (7634): 525. doi: 10.1038/540525a, PMID 30905947.
Saha K, Yousuf A, Hickman L, Gupta P, Tay L, De Choudhury M. A social media study on demographic differences in perceived job satisfaction. Proc ACM Hum Comput Interact. 2021; 5: 1–29.
Gottfried J, Shearer E. (2016). News use across social media platforms. [Online] Pew Research Center. [Online] Available at http://www.journalism.org/2016/05/26/news-use-across-social-media-platforms-2016/
Kaplan AM, Haenlein M. Users of the world, unite! The challenges and opportunities of social media. Bus Horiz. 2010; 53 (1): 59–68. doi: 10.1016/j.bushor.2009.09.003.
Elliott D, Culver C. Defining and analyzing journalistic deception. J Mass Media Ethics. 1992; 7 (2): 69–84. doi: 10.1207/s15327728jmme0702_1.
Shao C, Ciampaglia GL, Varol O, Yang KC, Flammini A, Menczer F. The spread of low-credibility content by social bots. Nat Commun. 2018; 9 (1): 4787. doi: 10.1038/s41467-018-06930-7, PMID 30459415.
Pang B, Lee L. Opinion mining and sentiment analysis. Found Trends Inf Retr. 2008; 2 (1–2): 1–135. doi: 10.1561/1500000011.
Rubin VL, Chen Y, Conroy NK. Deception detection for news: three types of fakes. Proc Assoc Inf Sci Technol. 2015; 52 (1): 1–4. doi: 10.1002/pra2.2015.145052010083.
Thies J, Zollhofer M, Stamminger M, Theobalt C, Niessner M. Face2Face: real-time face capture and reenactment of RGB videos. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 2016 June 27–30; Las Vegas, NV, USA: IEEE; 2016; 2387–2395 pp. doi: 10.1109/CVPR.2016.262.
Alegre F, Amehraye A, Evans N. Spoofing countermeasures to protect automatic speaker verification from voice conversion. In: IEEE International Conference on Acoustics, Speech and Signal Processing; Vol. 2013. IEEE Publications; 2013 May; Vancouver, BC, Canada: IEEE; 2013. 3068–3072 pp. doi: 10.1109/ICASSP.2013.6638222.
Siddharthan A, Reiter E, Dale R. Building natural language generation systems. Nat Lang Eng. 2000; 7 (3): 271–274.
Vannucci A, Flannery KM, Ohannessian CM. Social media use and anxiety in emerging adults. J Affect Disord. 2017; 207: 163–166. doi: 10.1016/j.jad.2016.08.040, PMID 27723539.
Verma P, Jamwal S. Mining public opinion on Indian government policies using R. Int J Innov Technol Exp Eng. 2020; 9 (3): 1310–1315. doi: 10.35940/ijitee.C8150.019320.
Cole S. (2017). AI-assisted fake porn is here and we’re all fucked. [Online] Available at https://www.vice.com/en/article/gydydm/gal-gadot-fake-ai-porn
Guille A, Hacid H, Favre C, Zighed DA. Information diffusion in online social networks: A survey. SIGMOD Rec. 2013; 42 (2): 17–28. doi: 10.1145/2503792.2503797.
O’Keeffe GS, Clarke-Pearson K. Council on Communications and Media: the impact of social media on children, adolescents, and families. Pediatrics. 2011; 127 (4): 800–804. doi: 10.1542/peds.2011-0054, PMID 21444588.
Grodzinsky FS, Miller KW, Wolf MJ. The ethics of designing artificial agents. Ethics Inf Technol. 2008; 10 (2–3): 115–121. doi: 10.1007/s10676-008-9163-9.
Perrot P, Aversano G, Chollet G. Voice disguise and automatic detection: review and perspectives. In: Progress in Nonlinear Speech Processing; 2007. 101–117 pp. doi: 10.1007/978-3-540-71505-4_7.
Griffith E. (2018). Progun Russian bots flood twitter after parkland shooting. [Online] Wired. Available at https://www.wired.com/story/pro-gun-russian-bots-flood-twitter-after-parkland-shooting/
Ferrara E, Varol O, Davis C, Menczer F, Flammini A. The rise of social bots. Commun ACM. 2016; 59 (7): 96–104. doi: 10.1145/2818717.
Hassan N, Arslan F, Li C, Tremayne M. 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; 2017 August; New York, NY, USA: ACM Digital Library; 2017. 1803–1812 pp. doi: 10.1145/3097983.3098131.
