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Wednesday, February 9, 2022

How can online communication credibility be determined? (Fogg dimension credibility model and Aggregated Trustworthiness model analysis)

Chapter 1.

Internet Communication

Technology has changed the way we communicate. Consequently, it has also changed the way we conduct business, the way we live personally, and the way we live in our social lives. We can easily communicate with everyone over the world anytime. There is no term “unreachable” or “untouchable” in the internet communication era.

We can say, now we live in a digital era with full dependence on the internet for information, communication, and social interaction. This situation has made us prefer to choose lack of food rather than lack of internet connection. People will be frustrated when the WIFI connection is in the problem rather than other important things.

In the internet era, everyone can access a variety of information, write and share about anything at any given time. How about the quality of the information? Is this true or false, valid or does the Hoax depends entirely on readers? This process is known as credibility perception (Shariff, 2020).

Regarding this condition, it is important for people (internet users) to understand the factors that could help them identify and determine the credibility of online content.  In this short paper, we will define what is credibility, what is the credibility factor and how can online communication credibility be determined. 

Chapter 2.

How can online communication credibility be determined?

Credibility

Fogg and Tseng argue that from the dozen or more elements that contribute to credibility evaluation, there are just two key dimensions of credibility: trustworthiness and expertise (Fogg and Tseng, 1999; Fogg, 2003).

There are two notions of credibility such as trustworthiness and expertise (Rieh & Hilligoss, 2008). Accordingly, trustworthy information is usually defined as real, equal, accurate, and unbiased (Rieh & Hilligoss, 2008) while Fogg (2003, p.124) illustrates expertise as apparent knowledge, skill as well as experience of sources.

Fogg and Tseng’s theory of computer credibility stress that credibility is always a perceived quality and not a property residing in any human or computer product. Fogg defines trustworthiness in the terms well-intentioned and unbiased, and expertise in the terms of perceived knowledge, skill, and experience according to Fogg and Tseng’s theory a high level of credibility incorporates both a high level of trustworthiness and expertise (Jessen & Jorgensen, 2011). With this approach then an online communication form like a Website cannot be considered credible if it does not entail both of these concepts, Perceived trustworthiness, and expertise. Perceived credibility is described in the figure below:

Picture 2.1

Credibility Factors

A. Fogg (Jessen & Jorgensen, 2011) distinguishes credibility into four types of credibility:

-       Presumed credibility, reflects general assumptions held by a reader.

-       Earned credibility, refers to the experience a reader has with a platform.

-       Reputed credibility, is the need for cognition/approval such as links to other reputed websites and other factors.

-       Surface credibility, is connected with the design, and usability of a platform (e.g. online social media, website) and others.

 And How then the credibility assessment results depending on individual differences. Credibility in internet communication refers to how someone perceives the beliefs of media content; this should be beyond any other of its contentions (Greer, 2021).

Fogg and Tseng argue that from the dozen or more elements that contribute to credibility evaluation, there are just two key dimensions of credibility: trustworthiness and expertise (Fogg and Tseng, 1999; Fogg, 2003).

There are two notions of credibility such as trustworthiness and expertise (Rieh & Hilligoss, 2008). Accordingly, trustworthy information is usually defined as real, equal, accurate, and unbiased (Rieh & Hilligoss, 2008) while Fogg (2003, p.124) illustrates expertise as apparent knowledge, skill as well as experience of sources.

B. Shafiza Mohd Shariff based on his research presented in the Review on Credibility Perception of Online Information define the credibility factors below (Shariff S. M., 2020) define credibility factors 1. Source of information 2. Composition of information 3. External source link 4. Interface design layout 5. Readers attributes:

1.     Source of Information

On websites, the reputation and trustworthiness of a source are important features in determining whether online information on pages such as blogs or article posts are credible (Rieh & Hilligoss, 2008) (Sundar, Westerwick, & Hastall, 2007), The source credibility features are, however, different on social media. Researchers found that an author’s profile and social network on Twitter represent a higher credibility indicator regarding the tweet messages the author posted (Castilo & Mendoza, 2011), (Shariff, Zhang, & Sanderson, 2017). The differences in a source’s credibility features between websites and social media are due to the interface design of each platform. On a website, the image and information regarding the author is limited or not available. Readers also consider the site host, such as the name of a news agency or the name of the company, as a source of information if the details of the author are not made available (Sundar, Westerwick, & Hastall, 2007). In contrast, a social media author’s information such as image, gender, location, and whom they are connected with on social media is more accessible and thus gives more confidence to the readers of the online information regarding the credibility of the source and the information posted by the source (Shariff, Zhang, & Sanderson, 2017).

2Composition of Information

The next credibility factor for online information is the information itself. The main feature of credible online information is the level of relatedness of the information to the topic (Rieh & Hilligoss, 2008), (Sundar, Westerwick, & Hastall, 2007). Topic-related information is described as being informative and relevant to the keyword search and title of the post (Flanagin & Metzger, 2000) or having similar information to other online information from different websites regarding the topic or keyword (Sundar, Westerwick, & Hastall, 2007). Although topic-related message posts on social media and on websites is still a prominent feature for credibility as shown in previous studies (Castilo & Mendoza, 2011) language is another credibility feature proposed by researchers as a credibility indicator for information on social media. Since social media is a platform for anyone to post messages about anything, the language used on such posts is informal and contains Internet abbreviations, especially on Twitter due to the limit of characters per post. A post with formal language will be perceived as more credible than one with slang and abbreviations (Sikdar, Kang, Hollerer, & Adal, 2013) A language element that has been proposed is the use of sentiment and semantic words. These words describe the opinion of an author and the positive/negative relation of the post towards the topic. Other than these, social media has special features that can be used as part of the information text that is not found or widely used on the web: hashtags and user mentions. The use of features such as hashtags, which start with the symbol ‘#’, and the user mention indicator which starts with the character ‘@’, also gives an indication of the relation between the information with the topic (Al-Rubaian, Rahman, & Alamri, 2015).

3. External Source Links

The next credibility factor is embedding external sources in the information. Social media users sometimes link external sources on their posts, such as images or links, for example, to other online content. The external sources will give an impression that the information posted is not fabricated (Al-Rubaian, Rahman, & Alamri, 2015). Husin, Thom, and Zhang (2013) (Husin, Thom, & Zhang, 2013) described that social network users access news agency websites for further information by the hyperlink embedded in the news story posts on online social media such as Twitter, a verification act when the readers are deciding the credibility level of the post’s author and evaluating the information (Rieh & Hilligoss, 2008). Meanwhile, the use of external links on web online content, such as blogs, are mostly linked to articles within the same web platform. However, there have been some websites or blogs that have embedded the URL link to the external source, if the article is based on the source such as Wikipedia (Rieh & Hilligoss, 2008). Again, this is an option for readers to do their own verification of the credibility of the information.

 4. Interface Design Layout

Other than information structures, the design or features available on a website and social media platform are another credibility feature contributing to the credibility perceptions of online information. On websites, the layout design of the site gives different credibility perceptions of the online information appearing on those sites (Flanagin & Metzger, 2000). If the design consists of much commercial content such as advertisements, it gives a lower credibility perception than a layout design that shows a real-world feel and ease of use (Fogg, et al., 2001). The time indicator on the website is also a credibility feature as it will show the recency of the online information posted on the website. The time indicator could also ensure the information is consistent with other information posted on other sites within the same time period (Sundar, Westerwick, & Hastall, 2007). The time indicator is also an important design feature on social media. Consistent with (Sundar, Westerwick, & Hastall, 2007), who found the importance of knowing when an article is posted on the website, (Al-Rubaian, Rahman, & Alamri, 2015) and (Kang, Hollerer, & Donovan, 2015) also discovered that if a message posted on social media is dated in the middle of the occurrence of a trending issue, the higher the credibility perception of the message post. Other credibility features for online information based on the social media platform design are propagation and count features. Both give an indicator that other social media users find the message posted to be trustworthy. The users can choose to propagate the message using a sharing method, and the number of shares will be shown (Sikdar, Kang, Hollerer, & Adal, 2013), (Al-Rubaian, Rahman, & Alamri, 2015), (Kang, Hollerer, & Donovan, 2015). Another design feature that has been proposed by Li and Suh (2015) (Li & Suh, 2015) as a credibility indicator on social media is the interaction feature. This feature is the communication between social media users on their own social media page by using the user mention feature in their message post and also in the comment section underneath each message post. Although some researchers argue that the use of user mention is a credibility indicator on the message post as discussed earlier, focus on the use of the user mention in the design of social media as it is what makes social media unique. Generally, the aim of information credibility studies is to find features that make good credibility indicators online. However, there are few studies that consider the reader’s attributes. The studies that relate to readers mostly look at the use of surface features, including the source features. Demographic attributes of readers are also used to differentiate the population and their credibility judgment (Shariff, Zhang, & Sanderson, 2017)

5. Readers’ Attributes

Research on characterizing users and their behavior for credibility perceptions in the online community is important and so is discussed separately in this section. The credibility of information on the Internet is rated higher by experienced and savvy users rather than by less experienced users. In addition, the freedom users have in choosing the information from the source they deem credible based on their experience and verification steps also contributes to the high credit rating of the Internet (Flanagin & Metzger, 2000). 

Chapter 3.

What is “Aggregated trustworthiness”?

Aggregated trustworthiness is the approach/theory to assess online credibility which is developed to remedy the limitation of previous online credibility theory developed by Fogg and Tseng (1999). According to this model perceived credibility (aggregated trustworthiness) is developed by Social validation, Authority & Trustee, and Profiles. It is described in the model below: 

Picture 3.1

Social validation, online information is assessed by the social environment. It is a large–scale verification made by others. For example, in social media (Facebook, Instagram, etc.) social validation of online information or the material that users shared will be validated socially in many different forms view, like, dislike, comment, share, copy, mix, modify, follow, subscribe). Social validation also builds relationships through empathy and the exchange of meaningful experiences. Social validation simply means that the more people acknowledge a certain piece of information the more trustworthy it is perceived (Jessen & Jorgensen, 2011). Below is an example of social validation in social media (likes, comments, etc.)

Profiles: Profile’ provides the baseline for identity online as well as adding a fixture of the evaluation (e.g., LinkedIn profile, Twitter stream, personal Web site or blog) (Jessen & Jorgensen, 2011). Identity is critical and very important when assessing online information. We can assess the credibility of information by assessing the profile/identity as a source of information. 

Authority & trustee: the information which is coming from a trusted source and has the authority to define the level of credibility. For example, the credibility of the news from CNN, and the credibility of the research report from Harvard University. The low trustee example: Wikipedia reference). Below is an example of the authority and trustee which can guarantee the credibility of the information. 

Aggregated trustworthiness provides a more adequate explanation of online credibility. Incorporating social validation, online trustees, and profile-based Web sites, this notion is the first step toward better explaining the processes of credibility evaluation of online information and platforms lacking traditional expert cues (Jessen & Jorgensen, 2011).

References

Al-Rubaian, M.-Q.-R., Rahman, & Alamri. (2015). Multistage credibility analysis model for microblogs. ACM international Conference on Advances in Social networks analysis and mining (pp. 1434-1440). ASONAM.

Castilo, C., & Mendoza, M. B. (2011). Information credibility on twitter. The 20th International conference on world wide web, (pp. 675-684).

Demers, J. (2015, February 19). The Importance Of Social Validation In Online Marketing. Retrieved from Forbes: https://www.forbes.com/sites/jaysondemers/2015/02/19/the-importance-of-social-validation-in-online-marketing/?sh=2cd3a753364d

Flanagin, A., & Metzger, M. (2000). Perceptions of internet information credibility. Journalism & Mass Communication Quarterly vol77, 515-540.

Fogg, B. (2003). Persuasive technology: Using computers to change what we think and do. Boston: Morgan Kaufmann.

Fogg, B. (2003). Prominence interpretation theory: Explaining how people assess credibility online. New York: ACM.

Fogg, B., Marshal, J., Laraki, O., Osipovich, A., Varma, C., Fang, N., . . . Treinan, M. (2001). What make website credible? THE SIGCHI Conference on Human Factor in Computer Systems (pp. 61-68). ACM.

Greer, J. (2021). Evaluating the credibility of online information: A test of source and advertising influence. ResearchGate.

Husin, H. S., Thom, J., & Zhang. (2013). “News recommendation based on web usage and web content mining. ICDE Workshops 2013 (pp. 326-329). Brisbane: IEEE.

Jessen, J., & Jorgensen, A. H. (2011). Aggregated trustworthiness : Redefining online credibilility through social validation. First Monday, Peer-reviewed journal on the internet, 1.

Jessen, J., & Jorgensen, A. H. (2011). Aggregated trustworthiness: Redefining online credibility through social validation. first Monday peer-reviewed journal on the internet, 3.

Kang, B., Hollerer, T., & Donovan, o. (2015). Believe it or not? Analyzing information credibility in microblogs. The 2015 IEEE/ACM International Conference on Advance in social networks analysis and mining (pp. 611-616). ACM Press.

Li, R., & Suh, A. (2015). Factors influencing information credibility on social media platforms; Evidence from Facebook pages. Procedia Computer science, 314-328.

Rieh, S., & Hilligoss, B. (2008). "College students" credibility judgments in the information-seeking process. In Digital Media, Youth, and Credibility (pp. 19-72). Digital Media,.

Shariff, M., Zhang, & Sanderson, M. (2017). On the credibility perception of news on Twitter: Readers, topics and features,. Computers in Human Behavior, 785-796.

Shariff, S. M. (2020). A Review on Credibility Perception of Online Information. Research Gate, 1.

Sikdar, M., Kang, O., Hollerer, T., & Adal, S. (2013). Cutting through the noise: Defining ground truth in information credibility on twitter. Human vol.2, 151-167.

Sundar, S., Westerwick, K., & Hastall, M. (2007). News cues: Information scent and cognitive heuristic. Journal of the association for information science and technology, 366-378.

Tversky, A., & Kahneman, D. (1974). Judgement under uncertainty : Heuristics and Biases. Science Vol.185, 1124-1131.

 

 

 

 


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