Introduction
People of the modern world have access to tremendous amounts of information originating from various places online. However, depending on the source, the content of articles, blog posts, media reports, and videos may or may not be reliable. Credibility has become an essential topic for the investigation to help researchers and the general public to differentiate facts from misleading information.
Indeed, different tools and checklists were developed to help individuals sort data they find online, selecting credible articles and excluding the unnecessary ones (Li et al. 3). This paper aims to discuss how to check a source for accuracy, credibility, reasonableness, and proper support. To assess the abovementioned characteristics of information, not only can various intelligent algorithms and tools be utilized, but also the simple checking of the publisher’s or producer’s credentials can help check data.
Credibility of Sources
Although the concept of credibility has become almost a buzzword in academic institutions, its importance should never be underestimated. According to Hosseini and Moeini, this term can be defined as the trustworthiness and plausibility of information coming from a reputable source (3). Notably, the credibility of the latter primarily depends on the quality of messages and reports it provides (Hosseini and Moeini 3). Articles with more details, descriptions, logical structure and few or no contradictions are more reputable than those with multiple discrepancies within them and with other sources.
The understanding of credible data may vary in academia, social media, and the web in general. For instance, when Facebook or Instagram users read posts online, they rate the credibility of that information based on popularity, attractiveness, recency, and believability (Hosseini and Moeini 12). The same parameters may not be sufficient or applicable to scholarly articles because, in research, it is critical to determine the authors’ qualifications, the journal’s credentials, and the accuracy of methodology and results. Web data credibility is judged based on websites’ security settings and the organizations they belong to (Zhao 407). In fact, the trustworthiness of online platforms owned by banks or governmental agencies is greater than, for example, private media with insufficient security and abundant advertisement.
Accuracy of Data
Accuracy is the concept that is often referred to quantitative rather than qualitative data. In research, the precision of measurements and results depends on the sampling techniques, technology used, the experience of researchers, and some external factors that may alter experimental settings (Späti et al. 2). However, when it comes to media sources, information accuracy is rated based on such characteristics as grammar, punctuation, completeness of the content, and objectivity of opinions (Li et al. 6). The reason why these factors are important is that much falsified data is spread online. Fortunately, research has determined what websites and social media apps are prone to distribute misinformation and fake news. For instance, it was found that WeChat spreads inaccurate health-related articles to users, sometimes leading to unfavorable consequences (Li et al. 7). Accuracy and credibility of information may or may not be strictly crucial for celebrity news. However, these two features are vital for medical websites, research magazines, journals, and policymakers.
Reasonableness of Information
As the name suggests, the term reasonableness refers to the objectivity and consistency of presented information. When a post or an article has an excessive number of over-claims, intemperate language, over-emphasizing statements, as well as incoherence between title and text, it is perceived as unreasonable (Li et al. 6). Moreover, bias is inevitable since scientists and authors have a specific inclination to particular beliefs based on the background knowledge they have. Still, the reasonableness of the source is evaluated based on how objectively different viewpoints are assessed (Li et al. 11).
Another essential aspect of reasonable information is the absence of conflict of interest. The latter implies that the presented ideas should originate from the authors, not other interested parties, and if there is an external influence or investment, it should be adequately disclosed (Segal). Another meaning of conflict of interest is when authors have a clash between personal and professional interests (Segal). The source can be considered reasonable if there are no conflicts of interest and significant bias or if they are adequately elaborated.
Support
The support of information means the degree of using citations to verify the validity of presented facts. References used in a scientific paper or blog post should be checked for credibility and accuracy. Some authors use uncited statistical data or claim the information is obtained from a governmental organization but do not provide the link to sources (Li et al. 9). In such cases, it is hard to perceive these sources as well-supported. Indeed, the support is a critical determining factor when deciding whether the information should be trusted.
Methods to Check Credibility and Accuracy of Information
Various tools and techniques were developed to evaluate the parameters discussed above. For instance, the instrument known as CARS, which stands for credibility, accuracy, reasonableness, and support, is often utilized for the assessment of sources (Li et al. 3). The CARS checklist allows one to determine if the online information is trustworthy. Another method for evaluating credibility is the CRAAP test, which checks the currency of a publication, the relevance of data, the authority of authors and publishers, information accuracy, and the purpose (Russo 295). Similarly, the RADAR tool examines the rationale for the article or post, the authority of the source, the date of publication, the accuracy of data, and relevance to the reader’s specific question (Russo 296). These and other tools help students, researchers, and the general population to find valuable and credible sources for their special needs.
Apart from implementing different techniques, it is essential to have common sense and think critically to judge whether the provided information is reliable and unbiased. It is unwise to disregard the source if it was published in the nineteenth century and prefer a more recent one because, in some cases, it is better to read the original works (Russo 296). At the same time, it is advisable to be mindful of one’s background knowledge, values, beliefs, and prejudices in order not to discredit the credible source.
Conclusion
In summary, to determine if information from media or scientific databases can be trusted, it should be appraised for such criteria as credibility, accuracy, reasonableness, and support. Although various methods exist to decide if the source provides trustworthy, precise, unbiased, recent, relevant, and cited data, individuals should remain cognizant of their beliefs and authors’ potential interests. Overall, one can trust the information presented in reputable research journals published recently. However, when it comes to social media or news websites, the source’s credentials should be judged more thoroughly, and presented data must be checked for adequate support.
Works Cited
Hosseini, Monireh, and Fakhereh Moeini. “The Credibility of Information on Social Media: The Study of Iranian Users.” Research Square, 2022, pp. 1-16.
Li, Yuelin, et al. “Recognizing Fake Information Through A Developed Feature Scheme: A User Study of Health Misinformation on Social Media in China.” Information Processing & Management, vol. 59, no. 1, 2022, pp. 1-14.
Russo, Alyssa, et al. “Strategic Source Evaluation: Addressing the Container Conundrum.” Reference Services Review, vol. 47, no. 3, 2019, pp. 294–313.
Segal, Troy. Conflict of Interest Definition. Investopedia, Web.
Späti, Karin, et al. “Benefits of increasing information accuracy in variable rate technologies.” Ecological Economics, vol. 185, 2021, pp. 1–11.
Zhao, Nannan. “Credibility Evaluation of Web Big Data Information Based on Particle Swarm Optimization.” Journal of Web Engineering, 2022, pp. 405–424.