Dataconomy
  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
Subscribe
No Result
View All Result
Dataconomy
  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
Subscribe
No Result
View All Result
Dataconomy
No Result
View All Result

How dangerous news spreads: What makes Twitter users retweet risk-related information

by admin
March 19, 2020
in Case Studies, Data Science
Home Case Studies
Share on FacebookShare on TwitterShare on LinkedInShare on WhatsAppShare on e-mail

Scientists uncover how information related to potential dangers can spread on social media and how this can be prevented.

In Japan, a country prone to various natural and man-made calamities, users often turn to social media to spread information about risks and warnings. However, to avoid spreading rumors, it is crucial to recognize reliable sources of information. In a new study, researchers from Osaka University, Japan have revealed the mechanism by which risk-related information is disseminated on Twitter.

In an Internet-driven world, social media has become the go-to source of all kinds of information. This is especially relevant in crisis-like situations, when warnings and risk-related information are actively circulated on social media. But currently, there is no way of determining the accuracy of the information. This has occasionally resulted in the spread of misinformation, with some readers often bearing the brunt. In a study published in Japanese Psychological Research, scientists at Osaka University, including Prof Asako Miura, found a pattern through which information spreads on social media—which could help prevent the spread of fake news. Prof Miura says, “Dissemination of information through social media is often associated with false rumors. In order to prevent this, we wanted to unravel the underlying mechanisms by digging deeper into how these false rumors spread.”

How dangerous news spreads: What makes Twitter users retweet risk-related information
How dangerous news spreads: What makes Twitter users retweet risk-related information

The scientists focused on Twitter, a popular site where users can disseminate or share information through the “retweet” feature. Conventional models of information diffusion fail to adequately explain the exact transmission route on social media, as they do not take into account individual user characteristics. Therefore, to study these characteristics, the scientists first selected 10 highly retweeted (more than 50 times) risk-related tweets. Based on Slovic’s well-known definition of risk perception, a cognitive model used to assess how people perceive certain risks, they assessed whether users perceived these risks as “dreadful” (related to large-scale events with potentially dire consequences) or “unknown” (when the impact of the event is unknown). They then analyzed the personal networks of the users who tweeted/retweeted particular tweets—specifically the number of followers, followees, and mutual connections.

They found that users with fewer connections tend to spread information arbitrarily, possibly owing to a lack of experience or awareness. But, users with a high number of mutual connections were more emotionally driven—they were more likely to spread dreadful information, possibly intending to share their reactions with the public. Prof Miura explains, “Our study showed the existence of an information diffusion mechanism on social media that cannot be explained by conventional theoretical models. We showed that risk perception has a significant impact on the ‘retweetability’ of tweets.”


Join the Partisia Blockchain Hackathon, design the future, gain new skills, and win!


By identifying the user network characteristics on Twitter, this study potentially offers a solution to prevent fake news dissemination. These characteristics can be leveraged to maximize the spread of accurate information, ensuring that appropriate measures are taken. Prof Miura concludes, “Our research provides an opportunity for people to rethink how false information is spread and to deliver accurate information via social media.”

The article, “Spread of risk information through microblogs: Twitter users with more mutual connections relay news that is more dreadful” was published in Japanese Psychological Research at DOI: https://doi.org/10.1111/jpr.12272.

Authors: Masashi Komori, Asako Miura, Naohiro Matsumura, Kai Hiraishi, and Kazutoshi Maeda

DOI: https://doi.org/10.1111/jpr.12272

Funded by: Japan Society for the Promotion for Science

Related Posts

What is ChatGPT Plus, and how to get it? Learn its features, price, and how to join ChatGPT Plus waitlist. Is it worth it? Keep reading and find out

ChatGPT Plus: How does the paid version work?

February 2, 2023
AI Text Classifier: OpenAI's ChatGPT detector can distinguishes AI-generated text

AI Text Classifier: OpenAI’s ChatGPT detector indicates AI-generated text

February 2, 2023
BuzzFeed ChatGPT integration: Buzzfeed stock surges in enthusiasm over OpenAI

BuzzFeed ChatGPT integration: Buzzfeed stock surges after the OpenAI deal

February 2, 2023
Adversarial machine learning 101: A new frontier in cybersecurity

Adversarial machine learning 101: A new cybersecurity frontier

January 31, 2023
What is the Nvidia Eye Contact AI feature? Learn how to get and use the new Nvidia Broadcast feature. Zoom meetings and streams get easier.

Nvidia Eye Contact AI can be the savior of your online meetings

February 2, 2023
How did ChatGPT passed an MBA exam

How did ChatGPT passed an MBA exam?

February 2, 2023

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

LATEST ARTICLES

Cyberpsychology: The psychological underpinnings of cybersecurity risks

ChatGPT Plus: How does the paid version work?

AI Text Classifier: OpenAI’s ChatGPT detector indicates AI-generated text

A journey worth taking: Shifting from BPM to DPA

BuzzFeed ChatGPT integration: Buzzfeed stock surges after the OpenAI deal

Adversarial machine learning 101: A new cybersecurity frontier

Dataconomy

COPYRIGHT © DATACONOMY MEDIA GMBH, ALL RIGHTS RESERVED.

  • About
  • Imprint
  • Contact
  • Legal & Privacy
  • Partnership
  • Writers wanted

Follow Us

  • News
  • AI
  • Big Data
  • Machine Learning
  • Trends
    • Blockchain
    • Cybersecurity
    • FinTech
    • Gaming
    • Internet of Things
    • Startups
    • Whitepapers
  • Industry
    • Energy & Environment
    • Finance
    • Healthcare
    • Industrial Goods & Services
    • Marketing & Sales
    • Retail & Consumer
    • Technology & IT
    • Transportation & Logistics
  • Events
  • About
    • About Us
    • Contact
    • Imprint
    • Legal & Privacy
    • Newsletter
    • Partner With Us
    • Writers wanted
No Result
View All Result
Subscribe

This website uses cookies. By continuing to use this website you are giving consent to cookies being used. Visit our Privacy Policy.