Philosophy Dictionary of ArgumentsHome
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| Misinformation: Misinformation is false or misleading assertion that is spread, regardless of whether there is intent to deceive. See also Social Media, Internet, Newspapers, Information, Assertions._____________Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments. | |||
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Rachel E. Kranton on Misinformation - Dictionary of Arguments
Kranton I 421 Misinformation/Fake News/Kranton: ((s) the term “fake news” is not used by the cited authors). Agents’ individual payoffs depend on a collective decision, such as election of a candidate or authorizing the use of a new technology. Collective decision making is modeled as a stylized “vote” that reflects each agent’s expected utility from the decision. Some agents are unbiased and prefer that the decision correctly matches the true state of the world. >Terminology/Kranton). Other agents are biased and prefer a particular decision regardless of the true state. (Such agents might personally benefit, say, from the decision. Agents have prior beliefs as to the true state. One agent, selected at random, possibly receives precise information about the true state. This agent, whose identity is not known, can create a false or true message—a rumor—of the state of the world. Biased agents have the incentive to create a false message. Agents who receive a message make an inference as to the veracity of the message and decide whether or not to pass it along to influence how others will vote on the collective outcome. >Misinformation/Economic Theories. Kranton I 423 In one set of models, opinions spread like diseases; that is, individuals become infected (adopt an opinion) by contact with another agent with that disease (see, e.g., chapter 7 of Jackson, 2008)(1). Such diffusion processes are also studied in computer science, statistical physics, and sociology. In such models, biased agents are always better off when there are more biased agents (…). In a second set of models, opinion formation in social networks builds on DeGroot (1974)(2). Agents, with possibly different initial priors, repeatedly “exchange” their beliefs with their neighbors and adopt some statistic (the weighted average, say) of their neighbors’ opinions. Such agents fail to take into account the repetition of information that can propagate through a network, leading to a persuasion bias as referred to by DeMarzo et al. (2003)(3). Kranton I 436 General Networks/Communication/Bloch/Demange/Kranton: We identify three key simplifying assumptions that render the analysis of the general network similar to the analysis of a tree. 1. If agents transmit a message, they send the message to all their neighbors (except the one from whom they have received a message). Communication is multicast, and agents cannot endogenously choose which route to send the message along. 2. The time it takes a message to travel along a path is proportional to the length of the path. This assumption is needed to guarantee that agents can identify the agents from whom they receive the message the first time as those agents who are at a shortest distance in the network. Absent this assumption, agents would have to make complex computations to identify the set of agents from whom they receive the message the first time. 3. (Most importantly) agents only decide whether or not to transmit the message the first time they receive it; that is, although a message could reach an agent along several paths and an agent could therefore receive several messages, they ignore all messages but the first one. >Network Models/Kranton, >Communication Models/Kranton, >Communication Filters/Kranton, >Misinformation/Economic Theories, >Terminology/Kranton. 1. JACKSON, M., Social and Economic Networks (Princeton: Princeton University Press, 2008). 2. DEGROOT,M. H., “Reaching a Consensus,” Journal of the American Statistical Association 69 (345) (1974), 118–21. 3. DEMARZO, P. M.,D.VAYANOS, AND J. ZWEIBEL, “Persuasion Bias, Social Influence, and Uni-Dimensional Opinions,” Quarterly Journal of Economics 113 (3) (2003), 909–68. Francis Bloch, Gabrielle Demange & Rachel Kranton, 2018. "Rumors And Social Networks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 421-448._____________Explanation of symbols: Roman numerals indicate the source, arabic numerals indicate the page number. The corresponding books are indicated on the right hand side. ((s)…): Comment by the sender of the contribution. Translations: Dictionary of Arguments The note [Concept/Author], [Author1]Vs[Author2] or [Author]Vs[term] resp. "problem:"/"solution:", "old:"/"new:" and "thesis:" is an addition from the Dictionary of Arguments. If a German edition is specified, the page numbers refer to this edition. |
Kranton I Rachel E. Kranton Francis Bloch Gabrielle Demange, Rumors And Social Networks 2018 Kranton II Rachel E. Kranton George A. Akerlof Identity Economics: How Our Identities Shape Our Work, Wages, and Well-Being Princeton 2011 |
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> Counter arguments against Kranton
> Counter arguments in relation to Misinformation
Ed. Martin Schulz, access date 2024-04-28