Five Lessons from an Agent-Based Approach to Privacy in Social Media

2013 ◽  
pp. 49-53
Author(s):  
Paola Tubaro ◽  
Antonio A. Casilli ◽  
Yasaman Sarabi
Keyword(s):  
Social Media ◽  
Agent Based

scholarly journals Diffusion and persistence of false rumors in social media networks: implications of searchability on rumor self-correction on Twitter

2021 ◽  
Author(s):  
Kathrin Eismann
Keyword(s):  
Social Media ◽  
Agent Based ◽  
Social Media Networks ◽  
Agent Based Simulations

AbstractSocial media networks (SMN) such as Facebook and Twitter are infamous for facilitating the spread of potentially false rumors. Although it has been argued that SMN enable their users to identify and challenge false rumors through collective efforts to make sense of unverified information—a process typically referred to as self-correction—evidence suggests that users frequently fail to distinguish among rumors before they have been resolved. How users evaluate the veracity of a rumor can depend on the appraisals of others who participate in a conversation. Affordances such as the searchability of SMN, which enables users to learn about a rumor through dedicated search and query features rather than relying on interactions with their relational connections, might therefore affect the veracity judgments at which they arrive. This paper uses agent-based simulations to illustrate that searchability can hinder actors seeking to evaluate the trustworthiness of a rumor’s source and hence impede self-correction. The findings indicate that exchanges between related users can increase the likelihood that trustworthy agents transmit rumor messages, which can promote the propagation of useful information and corrective posts.

scholarly journals Agent Based Model of Anti-Vaccination Movements: Simulations and Comparison with Empirical Data

Vaccines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 809
Author(s):  
Pawel Sobkowicz ◽  
Antoni Sobkowicz
Keyword(s):  
Social Media ◽  
Critical Parameters ◽  
Rational Approach ◽  
The Internet ◽  
High Temporal Resolution ◽  
Nonlinear Feedback ◽  
Agent Based Model ◽  
Linear Processes ◽  
Agent Based ◽  
The Social

Background: A realistic description of the social processes leading to the increasing reluctance to various forms of vaccination is a very challenging task. This is due to the complexity of the psychological and social mechanisms determining the positioning of individuals and groups against vaccination and associated activities. Understanding the role played by social media and the Internet in the current spread of the anti-vaccination (AV) movement is of crucial importance. Methods: We present novel, long-term Big Data analyses of Internet activity connected with the AV movement for such different societies as the US and Poland. The datasets we analyzed cover multiyear periods preceding the COVID-19 pandemic, documenting the behavior of vaccine related Internet activity with high temporal resolution. To understand the empirical observations, in particular the mechanism driving the peaks of AV activity, we propose an Agent Based Model (ABM) of the AV movement. The model includes the interplay between multiple driving factors: contacts with medical practitioners and public vaccination campaigns, interpersonal communication, and the influence of the infosphere (social networks, WEB pages, user comments, etc.). The model takes into account the difference between the rational approach of the pro-vaccination information providers and the largely emotional appeal of anti-vaccination propaganda. Results: The datasets studied show the presence of short-lived, high intensity activity peaks, much higher than the low activity background. The peaks are seemingly random in size and time separation. Such behavior strongly suggests a nonlinear nature for the social interactions driving the AV movement instead of the slow, gradual growth typical of linear processes. The ABM simulations reproduce the observed temporal behavior of the AV interest very closely. For a range of parameters, the simulations result in a relatively small fraction of people refusing vaccination, but a slight change in critical parameters (such as willingness to post anti-vaccination information) may lead to a catastrophic breakdown of vaccination support in the model society, due to nonlinear feedback effects. The model allows the effectiveness of strategies combating the anti-vaccination movement to be studied. An increase in intensity of standard pro-vaccination communications by government agencies and medical personnel is found to have little effect. On the other hand, focused campaigns using the Internet and social media and copying the highly emotional and narrative-focused format used by the anti-vaccination activists can diminish the AV influence. Similar effects result from censoring and taking down anti-vaccination communications by social media platforms. The benefit of such tactics might, however, be offset by their social cost, for example, the increased polarization and potential to exploit it for political goals, or increased ‘persecution’ and ‘martyrdom’ tropes.

scholarly journals The Dynamic Evolution Mechanism of Heterogeneous OWOM—An Improved Viral Marketing Model

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 140
Author(s):  
Mengjie Liao ◽  
Lin Qi ◽  
Jian Zhang
Keyword(s):  
Social Media ◽  
Negative Impact ◽  
Viral Marketing ◽  
Dynamic Visualization ◽  
Agent Based ◽  
Marketing Model ◽  
Online Word Of Mouth ◽  
The Social ◽  
Huge Impact ◽  
Multi Agent

The negative impact of brand negative online word-of-mouth (OWOM) on social images in social media is far greater than the promotion of positive OWOM. Thus, how to optimize brand image by improving the positive OWOM effect and slowing the negative OWOM communication has turned into an urgent problem for brand enterprises. On this basis, we analyze the evolution process of the OWOM communication group of the social media brand network based on the SOR (stimulus-organism-response) theory of psychology. Through constructing the heterogeneous brand OWOM communication dynamic model and conducting the multi-agent-based simulation experiment, the dynamic visualization of brand OWOM communication effect combined the thinking model of viral marketing is realized. Experiments show that the ability of brand communicators to persuade has a direct impact on the persistence and breadth of brand communication. When the acceptance of the consumer market is high, the negative OWOM of the brand has a relatively huge impact on consumers.

Using Social Media to Predict Future Events with Agent-Based Markets

2010 ◽  
Vol 25 (6) ◽  
pp. 50-58 ◽  
Author(s):  
Efthimios Bothos ◽  
Dimitris Apostolou ◽  
Gregoris Mentzas
Keyword(s):  
Social Media ◽  
Agent Based ◽  
Future Events

A Web Agent Based on Exploratory Event Mining in Social Media

2012 ◽  
Author(s):  
Norifumi Hirata ◽  
Hiroyuki Sano ◽  
Robin M.E. Swezey ◽  
Shun Shiramatsu ◽  
Tadachika Ozono ◽  
...  
Keyword(s):  
Social Media ◽  
Agent Based ◽  
Event Mining
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