Helping to judge an information source

Wikis enable users to perform very influential and drastic changes to the whole environment and its community-generated shared artefacts (Kimmerle, Moskaliuk, Oeberst, & Cress, 2015). Controversial discussions can be used as an extended or supplemental knowledge base to the original article they are related to, but it can be a Sisyphean task to filter what is a good and relevant contribution for oneself, due to the ever-growing base of discussion threads and replies. Therefore, it seems

crucially important that contributors’ expertise be easily recognisable for new users. Similarly, contributors’ credibility as seen by the wiki community should be visi- ble. Yet, there are no indications of an author’s expertise in a certain domain or general expertise represented in wikis. This can become especially relevant if users perceive controversies that are of potential interest for them and want to assess the arguments of one or all the parties involved in the discussion. The lack of effective guidance probably leads a considerable number of users to the decision of leav- ing the discussion or even the wiki, because they get frustrated with the environ- ment and therefore do not learn or contribute anything new (Capdeferro & Romero, 2012). Wikis are social media platforms with a distinct focus on creating and pre- serving knowledge, but there are virtually no social components prevalent except for showing user names in discussions and revisions and the possibility to maintain an individual user page. There are no further affordances included in the system to easily assess individual contributions to socially shared artefacts (Notari et al., 2016). The establishment of mutual trust through credibility based on expertise can lead to externalisation of specialised knowledge (Zheng, 2012). It can further enable users to engage in deeper elaborations on materials and as well challenge the opin- ions of others (Edmondson, 1999). Such challenges of established schemata can be desirable for constructive controversies to occur that might induce socio-cognitive conflicts (Mugny, Butera, Sanchez-Mazas, & Perez, 1995). It is often useful or even necessary to filter down to what could be most valuable and thus to reduce the com- plexity of information that computer-based media offer. A valuable addition for not getting lost in the bulky information space of wiki talks is to generate easily un- derstandable visualisations based on collaborative filtering mechanisms (Bobadilla, Serradilla, & Hernando, 2009; Konstan & Riedl, 2003).

Research has shown that media users prefer low level strategies of finding “best fits” over high level strategies for the assessment of source credibility, meaning they often prefer quick and easy solutions over more complex processes of weighing and comparing (Cheng, Liang, & Tsai, 2013; Flanagin & Metzger, 2000; Lucassen & Schraagen, 2012). In online media sources, another low level and very effective filtering strategy is the implementation of social recommendation representations (e.g., star ratings for product quality) (Winter & Krämer, 2014). While blogs repre- sent a form of user-generated and participatory websites, they largely differ from wikis in the kind of content creation. In a blog, a single author writes an article that others can comment on, while in wikis all content like articles and related dis- cussions is collaboratively created. An addition of visual support to increase the salience of users who are experts in a controversial discussion could help the pro- cessing of one’s own socio-cognitive conflicts and furthermore support the resolu- tion of a continuing controversy in the form of a consensus. Such supplemental information could be very valuable for new and inexperienced users since most wiki contributors are often not experts in the field they are reading and writing about (Notari et al., 2016). For user-generated content sites like blogs, research sug- gests that social recommendations can predict which source would be read first and followed further. Users’ subjective assessments suggested that social recommenda- tion cues did not guide their source selection preferences (Winter, Metzger, & Flana- gin, 2016). In contrast to that, objective log data showed that highly recommended sources are selected earlier, more frequently and read more intensively. These find- ings consistently suggest that media users are not willing to invest much time and resources for the validity of an information or source in terms of credibility, trust- worthiness, and expertise.

Over-reliance in trust and credibility without effective use of expertise informa- tion can be counterproductive for members of a community (Zheng, 2012). This is possible to occur when users are not able to accurately understand the level of expertise of an individual contributor. In other related research on wiki talk page discussions, the focus lay on analyses of direct and indirect effects of minimal obtru- sive representations on learning outcomes and on the quality of wiki contributions. This research showed promising positive results of representations tacitly guiding users towards relevant discussions on a subject matter (Heimbuch & Bodemer, 2017; Trocky & Buckley, 2016). Building on this line of research, interest arose in explor- ing further variables that are directly related to processes of selecting an appropriate source and thus are related to further processes of knowledge construction in wikis. Specifically, the influencing potentials of the Need for Cognitive Closure (Webster & Kruglanski, 1994) seemed to be an obvious choice for further research. This con- struct is closely related to information seeking and its processing and above all how individuals deal with ambiguities, which are prevalent in typical controversial dis- cussions. People who score high on the Need for Cognitive Closure spectrum tend to base their decisions on heuristics, while low Need for Cognitive Closure individ- uals prefer more information in situations of uncertainty (Dreu, Koole, & Oldersma, 1999; Schlink, 2009). The relevance of such heuristics becomes especially important because of the previously discussed processes in the help-seeking framework and MAIN model which both describe the prevalence and reliance of certain heuris- tics when assessing the credibility of information sources. The immediate effects of additional information about authors’ expertise and credibility are described in an experimental study that will be presented in Chapter 3. For this experimental study, visualisations of domain-specific expertise were created as a ranking number embedded in a badge and community-standing of a contributor was visualised as

an approval count. There was specific interest in several aspects of how wiki users perceive and subjectively rate presented controversial discussions and the added information itself. Both types of supplemental information use the text and picture modalities that are predominant on web sites, and they were aimed at assigning agency to the community of wiki users with the potential of cueing heuristics that are likely to be processed otherwise depending on individual differences.