The Dark Side of Bot Farms in the Business World: An Ethical and Economic Threat in the Digital Era
Main Article Content
Abstract
In the digital economy, bot farms have emerged as a controversial tool businesses use to manipulate online visibility and influence consumer perception. While automation offers efficiency, bots' misuse, primarily through coordinated bot farms, poses serious ethical, legal, and economic challenges. This article critically examines the negative impact of bot farms in business practices, focusing on deceptive marketing, unfair competition, consumer misinformation, and the distortion of digital ecosystems. Using qualitative analysis and literature review, this study highlights the urgent need for regulatory frameworks and ethical digital governance to combat the rise of bot-driven manipulation. The findings show that bot farms undermine trust, disrupt market fairness, and erode the integrity of online platforms, calling for cross-sector efforts to mitigate their spread.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Accepted 2025-08-25
Published 2025-11-26
Plaudit
References
E. Ferrara, O. Varol, C. Davis, F. Menczer, and A. Flammini, ‘The rise of social bots’, Commun. ACM, vol. 59, no. 7, pp. 96–104, June 2016, doi: 10.1145/2818717.
S. Cresci, R. Di Pietro, M. Petrocchi, A. Spognardi, and M. Tesconi, ‘Fame for sale: Efficient detection of fake Twitter followers’, Decis. Support Syst., vol. 80, pp. 56–71, Dec. 2015, doi: 10.1016/j.dss.2015.09.003.
F. Mazzella, A. Sundararajan, V. Butt d’Espous, and M. Möhlmann, ‘How Digital Trust Powers the Sharing Economy: The Digitization of Trust’, IESE Insight, no. 30, pp. 24–31, Sept. 2016, doi: 10.15581/002.art-2887.
H. Allcott and M. Gentzkow, ‘Social Media and Fake News in the 2016 Election’, J. Econ. Perspect., vol. 31, no. 2, pp. 211–236, May 2017, doi: 10.1257/jep.31.2.211.
R. Barbado, O. Araque, and C. A. Iglesias, ‘A framework for fake review detection in online consumer electronics retailers’, Inf. Process. Manag., vol. 56, no. 4, pp. 1234–1244, July 2019, doi: 10.1016/j.ipm.2019.03.002.
N. P. Suzor, Lawless. Cambridge University Press, 2019. doi: 10.1017/9781108666428.
G. D. Domenico, J. Sit, A. Ishizaka, and D. Nunan, ‘Fake news, social media and marketing: A systematic review’, J. Bus. Res., vol. 124, pp. 329–341, Jan. 2021, doi: 10.1016/j.jbusres.2020.11.037.
B. Horne and S. Adali, ‘This Just In: Fake News Packs A Lot In Title, Uses Simpler, Repetitive Content in Text Body, More Similar To Satire Than Real News’, Proc. Int. AAAI Conf. Web Soc. Media, vol. 11, no. 1, pp. 759–766, May 2017, doi: 10.1609/icwsm.v11i1.14976.
Y. Li, F. Wang, S. Zhang, and X. Niu, ‘Detection of Fake Reviews Using Group Model’, Mob. Netw. Appl., vol. 26, no. 1, pp. 91–103, Nov. 2020, doi: 10.1007/s11036-020-01688-z.
M. Luca and G. Zervas, ‘Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud’, Manag. Sci., vol. 62, no. 12, pp. 3412–3427, Dec. 2016, doi: 10.1287/mnsc.2015.2304.
B. Edelman, M. Luca, and D. Svirsky, ‘Racial Discrimination in the Sharing Economy: Evidence from a Field Experiment’, Am. Econ. J. Appl. Econ., vol. 9, no. 2, pp. 1–22, Apr. 2017, doi: 10.1257/app.20160213.
R. Gorwa and D. Guilbeault, ‘Unpacking the Social Media Bot: A Typology to Guide Research and Policy’, Policy Internet, vol. 12, no. 2, pp. 225–248, Aug. 2018, doi: 10.1002/poi3.184.
J. Ratkiewicz, M. Conover, M. Meiss, B. Goncalves, A. Flammini, and F. Menczer, ‘Detecting and Tracking Political Abuse in Social Media’, Proc. Int. AAAI Conf. Web Soc. Media, vol. 5, no. 1, pp. 297–304, Aug. 2021, doi: 10.1609/icwsm.v5i1.14127.
D. Freelon and C. Wells, ‘Disinformation as Political Communication’, Polit. Commun., vol. 37, no. 2, pp. 145–156, Feb. 2020, doi: 10.1080/10584609.2020.1723755.
X. Liu, ‘A big data approach to examining social bots on Twitter’, J. Serv. Mark., vol. 33, no. 4, pp. 369–379, Apr. 2019, doi: 10.1108/jsm-02-2018-0049.
N. Chavoshi, H. Hamooni, and A. Mueen, ‘DeBot: Twitter Bot Detection via Warped Correlation’, presented at the 2016 IEEE 16th International Conference on Data Mining (ICDM), IEEE, Dec. 2016. doi: 10.1109/icdm.2016.0096.
K. Shu, A. Sliva, S. Wang, J. Tang, and H. Liu, ‘Fake News Detection on Social Media’, ACM SIGKDD Explor. Newsl., vol. 19, no. 1, pp. 22–36, Sept. 2017, doi: 10.1145/3137597.3137600.
C. Shao et al., ‘Anatomy of an online misinformation network’, PLOS ONE, vol. 13, no. 4, p. e0196087, Apr. 2018, doi: 10.1371/journal.pone.0196087.
U. Khairatun Hisan and M. Miftahul Amri, ’Artificial Intelligence for Human Life: A Critical Opinion from Medical Bioethics Perspective – Part I’, J. Pub. Heal. Sci., vol. 1, no. 02, pp. 100–111, Dec. 2022.
U. Khairatun Hisan and M. Miftahul Amri, ’Artificial Intelligence for Human Life: A Critical Opinion from Medical Bioethics Perspective – Part II’, J. Pub. Heal. Sci., vol. 1, no. 02, pp. 112–130, Dec. 2022.
P. Popiel, ‘Regulating datafication and platformization: Policy silos and tradeoffs in international platform inquiries’, Policy Internet, vol. 14, no. 1, pp. 28–46, Mar. 2022, doi: 10.1002/poi3.283.
A. Iliopoulou-Penot, ‘Governing the “Governors” of online speech: a review of the Digital Services Act’s first steps in regulating social media platforms’, Yearb. Eur. Law, Oct. 2025, doi: 10.1093/yel/yeaf006.