Aldayel A, Magdy W (2022) Characterizing the role of bots in polarized stance on social media. Soc Netw Anal Min 12(1):30
Article
Google Scholar
Ali M, Sapiezynski P, Bogen M, Korolova A, Mislove A, Rieke A (2019) Discrimination through optimization: how Facebook’s Ad delivery can lead to biased outcomes. Proc ACM Hum Comput Interact 199(3):1–30
Article
Google Scholar
Allen J, Howland B, Mobius M, Rothschild D, Watts DJ (2020) Evaluating the fake news problem at the scale of the information ecosystem. Sci Adv 6(14):eaay3539
Article
Google Scholar
Analytis PP, Barkoczi D, Herzog SM (2018) Social learning strategies for matters of taste. Nat Hum Behav 2(6):415–424
Article
Google Scholar
Analytis PP, Barkoczi D, Lorenz-Spreen P, Herzog S (2020) The structure of social influence in recommender networks. In: Proceedings of the web conference 2020, 2655–61. WWW ’20. New York, NY, USA: association for computing machinery
Aral S, Eckles D (2019) Protecting elections from social media manipulation. Science 365(6456):858–861
Article
Google Scholar
Bail CA, Argyle LP, Brown TW, Bumpus JP, Haohan Chen MB, Hunzaker F, Lee J, Mann M, Merhout F, Volfovsky A (2018) Exposure to opposing views on social media can increase political polarization. Proc Natl Acad Sci 115(37):9216–9221
Article
Google Scholar
Bail CA, Guay B, Maloney E, Aidan Combs D, Hillygus S, Merhout F, Freelon D, Volfovsky A (2020) Assessing the Russian internet research agency’s impact on the political attitudes and behaviors of American twitter users in late 2017. Proc Natl Acad Sci 117(1):243–250
Article
Google Scholar
Bakshy E, Messing S, Adamic LA (2015) Exposure to ideologically diverse news and opinion on facebook. Science. https://science.sciencemag.org/content/348/6239/1130.abstract?casa_token=93SGKMyFHO4AAAAA:NLLn7cnwU-dniTFvSJ5wC7XUJ30w5AFKxPLDLfWyijbh8Z-NWk0vsYB2zgXtq7EyGRLUhHdYX2fBfQ
Becker J, Brackbill D, Centola D (2017) Network dynamics of social influence in the wisdom of crowds. Proc Natl Acad Sci USA 114(26):E5070–E5076
Article
Google Scholar
Beskow DM, Carley KM (2018) Bot conversations are different: leveraging network metrics for bot detection in twitter. In: 2018 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM), 825–32. ieeexplore.ieee.org
Bessi A and Ferrara E (2016) Social bots distort the 2016 US presidential election online discussion. SSRN 21(11). https://ssrn.com/abstract=2982233
Bonaccio S, Dalal RS (2006) Advice taking and decision-making: an integrative literature review, and implications for the organizational sciences. Organ Behav Hum Decis Process 101(2):127–151
Article
Google Scholar
Broniatowski DA, Jamison AM, Qi S, AlKulaib L, Chen T, Benton A, Quinn SC, Dredze M (2018) Weaponized health communication: twitter bots and russian trolls amplify the vaccine debate. Am J Public Health 108(10):1378–1384
Article
Google Scholar
Carley KM (2020) Social cybersecurity: an emerging science. Comput Math Organ Theory 26(4):365–381
Article
Google Scholar
Dandekar P, Goel A, Lee DT (2013) Biased assimilation, homophily, and the dynamics of polarization. Proc Natl Acad Sci USA 110(15):5791–5796
Article
MathSciNet
MATH
Google Scholar
Das A, Datar M, Garg A and Rajaram S (2007) Google news personalization: scalable online collaborative filtering. In: Proc of the 16th Int Conf on World Wide Web, 271–80
Deffuant G, Neau D, Amblard F, Weisbuch G (2000) Mixing beliefs among interacting agents. Adv Compl Syst A Multidis J 03(4):87–98
Article
Google Scholar
DeGroot MH (1974) Reaching a consensus. J Am Stat Assoc 69(345):118
Article
MATH
Google Scholar
Edelson L, Nguyen M-K, Goldstein I, Goga O, Mccoy D, et al. Understanding engagement with U.S. (mis)information news sources on Facebook. IMC ’21: ACM Internet Measurement Conference, Nov 2021, Virtual Event, France. pp. 444–463. Link available here: https://hal.archives-ouvertes.fr/hal-03440083/file/news-interactions-imc2021.pdf
Endres K, Panagopoulos C (2019) Cross-pressure and voting behavior: evidence from randomized experiments. The J Polit 81(3):1090–1095
Article
Google Scholar
Ferrara E, Varol O, Davis C, Menczer F, Flammini A (2016) The rise of social bots. Commun ACM 59(7):96–104
Article
Google Scholar
Ferreira LN, Hong I, Rutherford A, Cebrian M (2021) The small-world network of global protests. Sci Rep 11(1):19215
Article
Google Scholar
Festinger L, Carlsmith JM (1959) Cognitive consequences of forced compliance. J Abnorm Psychol 58(2):203–210
Google Scholar
Flache A, Mäs M, Feliciani T, Chattoe-Brown E, Deffuant G, Huet S, and Lorenz J (2017) Models of social influence: towards the next frontiers. J Artif Soc Soc Simul. https://doi.org/10.18564/jasss.3521.
Fleming SM, Daw ND (2017) Self-evaluation of decision performance: a general bayesian framework for metacognitive computation. Psychol Rev 124(1):1–59
Article
Google Scholar
Fleming SM, van der Putten EJ, Daw ND (2018) Neural mediators of changes of mind about perceptual decisions. Nat Neurosci 21(4):617–624
Article
Google Scholar
Friedkin NE, Johnsen EC (1990) Social influence and opinions. The J Math Sociol 15(3–4):193–206
Article
MATH
Google Scholar
Friedkin NE and Johnsen EC (2011) Social influence network theory: a sociological examination of small group dynamics. Cambridge University Press
González-Bailón S, De Domenico M (2021) Bots are less central than verified accounts during contentious political events. Proc Natl Acad Sci USA. https://doi.org/10.1073/pnas.2013443118
Article
Google Scholar
Guess A, Nagler J, Tucker J (2019) Less than you think: prevalence and predictors of fake news dissemination on facebook. Sci Adv 5(1):4586
Article
Google Scholar
Hahn U, Oaksford M (2006) A Bayesian approach to informal argument fallacies. Synthese 152(2):207–236
Article
MathSciNet
MATH
Google Scholar
Hahn U, Oaksford M (2007) The rationality of informal argumentation: a Bayesian approach to reasoning fallacies. Psychol Rev 114(3):704–732
Article
Google Scholar
Hannak A, Sapiezynski P, Kakhki AM, Krishnamurthy B, Lazer D, Mislove A, Wilson C (2013) Measuring personalization of web search. In: Proceedings of the 22nd international conference on world wide web, 527–38. WWW ’13. New York, NY, USA: Association for Computing Machinery
Harris AJL, Hahn U, Madsen JK, Hsu AS (2016) The appeal to expert opinion: quantitative support for a Bayesian network approach. Cogn Sci 40(6):1496–1533
Article
Google Scholar
Hegselmann R, Krause U (2015) Opinion dynamics under the influence of radical groups, charismatic leaders, and other constant signals: a simple unifying model. Netw Heterog Media 10(3):477–509
Article
MathSciNet
MATH
Google Scholar
Howard P (2018) How political campaigns weaponize social media bots. IEEE Spectrum Oct
Hunter SD, and Zaman T (2018) Optimizing opinions with stubborn agents under time-varying dynamics. arXiv [cs.SI]. arXiv. http://arxiv.org/abs/1806.11253.
Hurtado S, Ray P and Marculescu R (2019) Bot detection in reddit political discussion. In: Proceedings of the fourth international workshop on social sensing, 30–35. SocialSense’19. New York, NY, USA: Association for Computing Machinery
Kakutani M (2019) The death of truth. Tim Duggan Books
Kalla JL, Broockman DE (2018) The minimal persuasive effects of campaign contact in general elections: evidence from 49 field experiments. The Am Polit Sci Rev 112(1):148–166
Article
Google Scholar
Karan N, Salimi F, Chakraborty S (2018) Effect of zealots on the opinion dynamics of rational agents with bounded confidence. Acta Phys Pol, B 49(1):73
Article
MathSciNet
Google Scholar
Keijzer MA, Mäs M (2021) The strength of weak bots. Online Social Networks and Media 21(January):100106
Article
Google Scholar
Koren Y and Bell R (2015) Advances in collaborative filtering. In: Recommender systems handbook, edited by Francesco Ricci, Lior Rokach, and Bracha Shapira, 77–118. Boston, MA: Springer US
Lazer D (2020) Studying human attention on the internet. Proceedings of the National Academy of Sciences of the United States of America
Lazer D, Baum MA, Benkler Y, Berinsky AJ, Greenhill KM, Menczer F, Metzger MJ et al (2018) The science of fake news. Science 359(6380):1094–1096
Article
Google Scholar
Ledford H (2020) Social scientists battle bots to glean insights from online chatter. Nature 578(7793):17–17
Article
Google Scholar
Lerman K, Yan X, Xin-Zeng Wu (2016) The ‘Majority Illusion’ in social networks. PLoS ONE 11(2):e0147617
Article
Google Scholar
Linvill DL, Warren PL (2018) Troll factories: the internet research agency and state-sponsored agenda building. Resource Centre on Media Freedom in Europe. https://scholar.google.com/scholar?hl=en&q=Brandon+C+Boatwright%2C+Darren+L+Linvill%2C+and+Patrick+L+Warren.+2018.+Troll+factories%3A+The+internet+research+agency+and+statesponsored+agenda+building.+Resource+Centre+on+Media+Freedom+in+Europe+%282018%29
Ma WJ, Beck JM, Latham PE, Pouget A (2006) Bayesian inference with probabilistic population codes. Nat Neurosci 9(11):1432–1438
Article
Google Scholar
Mäs M, Flache A (2013) Differentiation without distancing. Explaining Bi-polarization of opinions without negative influence. PLoS ONE 8(11):e74516
Article
Google Scholar
Mønsted B, Sapieżyński P, Ferrara E, Lehmann S (2017) Evidence of complex contagion of information in social media: an experiment using twitter bots. PLoS ONE 12(9):e0184148
Article
Google Scholar
Moscovici S, Zavalloni M (1969) The group as a polarizer of attitudes. J Pers Soc Psychol 12(2):125–135
Article
Google Scholar
Muller M (2012) Lurking as personal trait or situational disposition: lurking and contributing in enterprise social media. In: Proceedings of the ACM 2012 conference on computer supported cooperative work, 253–56. CSCW ’12. New York, NY, USA: Association for Computing Machinery
Navajas J, Heduan FÁ, Garrido JM, Gonzalez PA, Garbulsky G, Ariely D, Sigman M (2019) Reaching consensus in polarized moral debates. Curr Biol: CB 29(23):4124–29.e6
Article
Google Scholar
Paul, Christopher, and Miriam Matthews. 2016. “The Russian ‘firehose of Falsehood’ Propaganda Model.” Rand Corporation, 2–7.
Penrod SD, Cutler BL (1995) Witness confidence and witness accuracy: assessing their forensic relation. Psychol, Publ Pol, Law: an off Law Rev Univ Arizona College Law Univf Miami School Law 1:817–845
Article
Google Scholar
Pescetelli N, Yeung N (2020a) The role of decision confidence in advice-taking and trust formation. J Exp Psychol Gen. https://doi.org/10.1037/xge0000960
Article
Google Scholar
Pescetelli N, Yeung N (2020b) The effects of recursive communication dynamics on belief updating. Proc Royal Soc b: Biol Sci 287(1931):20200025
Article
Google Scholar
Pescetelli N, Rees G, Bahrami B (2016) The perceptual and social components of metacognition. J Exp Psychol Gen 145(8):949–965
Article
Google Scholar
Price PC, Stone ER (2004) Intuitive evaluation of likelihood judgment producers: evidence for a confidence heuristic. J Behav Decis Mak 17(1):39–57
Article
Google Scholar
Rader CA, Larrick RP, Soll JB (2017) Advice as a form of social influence: informational motives and the consequences for accuracy. Soc Pers Psychol Compass 11(8):e12329
Article
Google Scholar
Resulaj A, Kiani R, Wolpert DM, Shadlen MN (2009) Changes of mind in decision-making. Nature 461:263–266
Article
Google Scholar
Ricci F, Rokach L and Shapira B (2011) Introduction to recommender systems handbook. In: Recommender systems handbook, edited by Ricci F, Rokach L, Shapira B, and Kantor PB, 1–35. Boston, MA: Springer US
Robertson RE, Lazer D, and Wilson C (2018) Auditing the personalization and composition of politically-related search engine results pages. In: Proceedings of the 2018 world wide web conference on World Wide Web - WWW ’18, 955–65. New York, New York, USA: ACM Press
Shao C, Ciampaglia GL, Varol O, Yang K-C, Flammini A, Menczer F (2018) The spread of low-credibility content by social bots. Nat Commun 9(1):4787
Article
Google Scholar
Sherif CW, Sherif MS, Nebergall RE (1965) Attitude and attitude change. W.B. Saunders Company, Philadelphia
Google Scholar
Sniezek JA, Van Swol LM (2001) Trust, confidence, and expertise in a judge-advisor system. Organ Behav Hum Decis Process 84(2):288–307
Article
Google Scholar
Soll JB, Mannes AE (2011) Judgmental aggregation strategies depend on whether the self is involved. Int J Forecast 27(1):81–102
Article
Google Scholar
Stella M, Ferrara E, De Domenico M (2018) Bots increase exposure to negative and inflammatory content in online social systems. Proc Natl Acad Sci USA 115(49):12435–12440
Article
Google Scholar
Stewart LG, Arif A, and Starbird K (2018) Examining trolls and polarization with a retweet network. In: Proc ACM WSDM, workshop on misinformation and misbehavior mining on the web. http://faculty.washington.edu/kstarbi/examining-trolls-polarization.pdf
Stewart AJ, Mosleh M, Diakonova M, Arechar AA, Rand DG, Plotkin JB (2019) Information gerrymandering and undemocratic decisions. Nature 573(7772):117–121
Article
Google Scholar
Sun Z, Müller D (2013) A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models. Environ Model Softw 45(July):15–28
Article
Google Scholar
Sunstein CR (2018) #Republic: divided democracy in the age of social media. Princeton University Press
Tucker JA, Guess A, Barbera P, Vaccari Cr, Siegel A, Sanovich S, Stukal D, Nyhan B (2018) Social media, political polarization, and political disinformation: a review of the scientific literature. SSRN J. https://doi.org/10.2139/ssrn.3144139
Article
Google Scholar
Vosoughi S, Roy D, Aral S (2018) The spread of true and false news online. Science 359(6380):1146–1151
Article
Google Scholar
Whittaker J, Looney S, Reed A, Votta F (2021) Recommender systems and the amplification of extremist content. Internet Policy Rev. https://doi.org/10.14763/2021.2.1565
Article
Google Scholar
Yanardag P, Cebrian M, Rahwan I (2021) Shelley: a crowd-sourced collaborative horror writer. Creat Cognit. https://doi.org/10.1145/3450741.3465251
Article
Google Scholar
Yaniv I (2004) Receiving other people’s advice: influence and benefit. Organ Behav Hum Decis Process 93(1):1–13
Article
Google Scholar
Yildiz E, Ozdaglar A, Acemoglu D, Saberi A, Scaglione A (2013) Binary opinion dynamics with stubborn agents. ACM Trans Econ Comput 19,1(4):1–30
Article
Google Scholar
Zaller JR (1992) The nature and origins of mass opinion. Cambridge University Press
Book
Google Scholar