The Role of Credibility, Technology, and Emotions in Combating Fake News on Social Media

“Fake News on Social Media-Annotated Bibliography.” 

Kim, Antino, et al. “Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings.” Journal of Management Information Systems, vol. 36, no. 3, July 2019, pp. 931–68. EBSCOhost, https://doi.org/10.1080/07421222.2019.1628921. 

In this article, Kim, Moravia, and Dennis explore how rating the reliability of sources can help reduce the spread of fake news on social media. The authors focus on two types of ratings: user ratings, where regular users rate the credibility of sources, and expert ratings, where experts provide their evaluations. The study shows that both types of ratings can influence how people find out news articles, but expert ratings tend to be more trusted and effective in changing opinions.  

The authors conducted experiments to see how these ratings impacted users’ willingness to share news articles. They found that when users see high expert ratings, they are less likely to share news from unreliable sources. The study suggests that combining reputation ratings into social media platform could be a practical way to prevent the overall of false information. 

  This article helps understand how different approaches can be used to address the issue of fake news, and it provides insights for social media companies, policymakers, and researchers interested in improving the accuracy of information shared online. Also, When I do find out information on social media, I always go and search farther to see if it is true. I know for sure that anyone could give out false information. 

This annotation summarizes the article’s key points using straightforward language, making it easy for readers to understand without having technical vocabulary knowledge. It highlights the study’s focus, strategies, and procedures for reducing fake news on social media. 

Singh, Bhuvanesh, and Dilip Kumar Sharma. “Predicting Image Credibility in Fake News over Social Media Using Multi-Modal Approach.” Neural Computing & Applications, vol. 34, no. 24, Dec. 2022, pp. 21503–17. EBSCOhost, https://doi.org/10.1007/s00521-021-06086-4. 

Authors Singh and Sharma authored this article to investigate how to determine whether images shared on social media are trustworthy or part of fake news. The authors propose a “multimodal approach,” (Abstract Paragraph) which means they analyze both the image itself and the text that comes with it to assess credibility. The study highlights that fake news often uses deceive or manipulate images to make false information seem more realistic. By using computer and technology systems, the authors can automatically notice signs that an image might not be credible. These systems and methods look at several factors, for example, its content, how it matches with text and different qualities of images. 

 The authors found that their method was effective in predicting the credibility of images in many cases, which could help social media platforms automatically flag suspicious content before it spreads widely. 

 This article is important for understanding how technology can be used to fight the spread of fake news, especially when images are involved. It is extremely useful for those interested in digital media, social media, and the technical aspects of misinformation detection. These authors created a system that runs the information through programs to figure out if the information is true or false. 
This annotation provides a clear and concise summary of the article, focusing on its goals, methods, and implications, using basic terminology to make it accessible to a wide audience. 
 

Horner, Christy Galletta, et al. “Emotions: The Unexplored Fuel of Fake News on Social Media.” Journal of Management Information Systems, vol. 38, no. 4, Oct. 2021, pp. 1039–66. EBSCOhost, https://doi.org/10.1080/07421222.2021.1990610. 

In this article, “Emotions: The Unexplored Fuel of Fake News on Social Media,” the authors, Horner, Galleta, and Crawford examine the role of emotions cause by fake news on social media. The authors argued that emotional responses are unbearable when it comes from individuals that are excited, fearful, angry, or going through grief. The combination of surveys, investigation, and observation analysis of how emotional engagement content affects users sharing information. Users share the news even if it is not true. By examining emotions like anger, fear, grief, and excitement the study illuminates how this point of view can be overall applied to increase the strengths of fake new stories. Therefore, the news led to widespread false information and circulatory around facts. 

The authors discuss how social media is designed to prioritize high engagement and promote the spread of fake news for emotional responses. I have witnessed this, firsthand especially when you are on Facebook. For example, when a celebrity passes away. The information can be true or false and our emotions change, and we share the information with family, friends, etc.  

This annotation provides information on how to understand the impact of emotions users have when active online. It is a great resource for social media consumers, policymakers, and other scholars who are interested in how emotions affect Fake news on social media.