The global Covid-19 pandemic has shown how important it is to distinguish between quality information and misinformation. In this era, such a skill had true value and could even save lives, as misinformation spread around the world and posed a major threat to public health (Roozenbeek et al., 2020). Due to the quest for fast publication, there was a risk that scientific journals might accept low-quality COVID-related articles, potentially compromising established measures of scientific quality control (Kambakamba et al., 2020). In this situation, the role of Wikipedia has become crucial. As the world’s largest encyclopedia, it has become the main gateway to Covid-related information.
On English-language Wikipedia, more than 4,000 articles have been published about Covid, and the number of views exceeds 240 million (Wikimedia Foundation, 2020). At the same time, Google has begun to use data from Wikipedia in its graphs to show the number of Covid cases in individual countries. Moreover, the community of health experts has spontaneously formed around Wikipedia Coronavirus articles, and has checked these articles for false information (Cohen, 2020). Over a thousand editors and thirteen bots (artificial intelligence algorithms) have edited Coronavirus disease 2019 on English-language Wikipedia and together have made over five thousand edits. The resulting article contains over fifty thousand characters and 600 references (Figure 1). Thus, in terms of scope, it is more similar to a short professional monograph than a brief encyclopedic entry. We use this example to illustrate that Wikipedia is a very influential medium, which also has a significant impact on the dissemination of knowledge.
Wikipedia proclaims itself to be: "a multilingual, web-based, free encyclopedia based on a model of openly editable content.” Wikipedia, however, can be seen as something more than just a common encyclopedia. It affects existing models of the production of and search for information and common knowledge of various topics. It is one of the most widely visited websites in the world according to the Alexa rank. Wikipedia is used not just by common people but also by journalists (Messner & South 2011), students (Selwyn & Gorard, 2016) and even scientists, although they mostly do not cite it in their work: “Wikipedia is influencing roughly one in every ∼830 words in related scientific journal articles (…) scientific articles referenced in Wikipedia receive more citations.” (Thompson & Hanley, 2018). Because of this fact, it is also subjected to various research.
The quality of Wikipedia is often discussed (Fidler and Dejan, 2017; Ingawale at al., 2013) however, a comprehensive manual for quality assurance of information on Wikipedia is infeasible because Information Quality (IQ) is a multi-dimensional concept that combines criteria such as accuracy, reliability, and relevance (Ferretti et al., 2018). In practice, the only definition of IQ quality which is widely accepted is “fitness for use” (Neely, 2005). It is based on the definition of quality itself, which is defined by ISO 8402 as: “the totality of features and characteristics of a product or service that bear on its ability to satisfy stated or implied needs.” Thus, IQ assessment is also very subjective and depends on the specific purpose of use and mainly the criteria that are applied. Also, the application of these criteria on a specific issue is subjective. The same article could be perceived as being of top quality for students of elementary schools but of low quality for a Ph.D. student. There are also different requirements for humanities than there are for medicine. Medicine topics, for example, contain high-impact medical and multidisciplinary journals but social science articles could rely more heavily on books than journals (Jemielniak, Masukume, and Wilamowski, 2019). It is also important to mention that the quality of information on Wikipedia is largely culturally influenced (Jemielniak and Wilamowski, 2017) Therefore, in this research we do not explore the quality of Wikipedia itself; but we analyze articles that are perceived by the Wikipedia community as having better quality than others and describe which quantitative characteristics indicate their quality perception.
Wikipedia is also often used to search for environmental topics. English Wikipedia has indexed more than 33,000 mentions of the keyword “environmental protection”. The article “Global warming” alone has had more than 57,000,000 views since 2007 (Global warming pageviews, 2019). In addition, Wikipedia articles form common knowledge of these topics. Findings of results show that the majority of students (95%) of environmental disciplines use Wikipedia during their studies of environmental issues (Petiška, 2018). The current discussion about fake news (Zhang; Ghorbani, 2019) is relevant also to environmental information on the Web. There is much misinformation and fake news regarding environmental topics on the web (i.e. global warming, genetically modified foods, etc.).
For this reason, perception of the quality of Wikipedia in these issues is important, because the information taken from it is also often used in other sources. And if these sources do not mention Wikipedia as the source, the problem of citogenesis (circular reporting) could arise. Thus if false information from Wikipedia is used by a source that is perceived as respected, that source could be used later also as the reference for information on Wikipedia as occurs in many cases (Wikipedia: List of citogenesis incidents, 2019).
In order to understand the difference in Wikipedia quality perception, we use the concept of indicators. A well-known definition was coined by Bunge (1975): “An indicator is an observable trait of a thing (physical, biological, social or other) that is rightly or wrongly assumed to point to the value of some other trait, usually an unobservable one, of either the same or a different thing.” Thanks to their universality, indicators are also an important tool in measuring different aspects of quality, environmental protection and sustainable development (Hák, Janoušková & Moldan, 2016). There is also an effort to determine indicators of information quality in general as well as specifically on Wikipedia (Petiška, 2019; Wang & Li, 2020).
A better understanding of Wikipedia quality perception could also bring a new impulse to the discussion about the quality of Wikipedia in general. To contribute to this understanding, we have selected the following research questions for this study: What are the quantitative indicators which indicate the best environmental articles (according to Wikipedia quality perception)?