Surfing the information waves. Finding, revealing and evaluating information online
Project team: Chris Snijders, Uwe Matzat, Martijn Willemsen
PhD : Marcin Bober
People regularly have to make decisions that affect their quality of life and they need adequate information for doing so. In this “information age” the issue is typically not a scarcity of information. Rather, because of the internet there is an abundance of information, often described as information overload, and people have to find information that is useful for their problem, without spending too much time on the information search (Eppler & Mengis, 2004). Precisely which information is useful, however, is often difficult to judge for the lay user. For instance, in an online shop or on eBay, a buyer has to find out whether the information about a product given by a seller is true (Snijders & Zijdeman, 2004). A patient suffering from a chronic head pain has to decide whether he should trust a fellow sufferer's advice about a seemingly useful new therapy in a medical online support group (Eysenbach et al., 2004). A woman trying to find a relationship on a social networking site has to decide to what extent a potential partner is exaggerating his willingness for a serious commitment (Whitty, 2002; Thelwall, 2008). Evaluating the information as 'useful' or 'true' in these cases often means trusting the information provider. The decision to trust someone else whom you know only through several pieces of information revealed online is a difficult one, and people nowadays have to make this decision more often than ever.
In the offline world usually much more information is available for such a decision. For example, specific types of behaviour, usage of symbols and certificates, or subtle emotional cues can function as signals about the honesty of someone’s dating partner or the competence of a physician (Frank, 1988). And, even if we hardly have any visible cues at hand, in many situations we can trust our interaction partner because of reputation mechanisms (Raub & Weesie, 1990). Our new business partner does not overtly cheat as long as he knows we are able to damage his reputation by using informal networks linking us to his other business partners. Our new acquaintance will not be dishonest as long we have common friends whose sheer existence facilitates the maintenance of behavioural norms.
At the core of this project lies the question how people deal with the reliability of information on the Internet, to what extent the formal and informal mechanisms that facilitate reliable exchange of information offline have online equivalents and to what extent new online mechanisms and tools are and can be developed to facilitate reliable information exchange.
Dealing with the reliability of information and the trustworthiness of the partner is essentially different in the online world. Face-to-face interaction between all communication partners is impossible – besides the physical distance there are simply too many persons involved. Nevertheless, in some online communities a limited amount of offline interaction between smaller groups of members may reduce problems of trust for all members (Matzat, 2006). As an alternative, some communities on the internet use formalized reputation systems to signal trustworthiness (e.g., eBay or Amazon) and product review sites collect massive feedback of consumers (e.g., Vergelijk.nl, Amazon). Still other communities rely on administrators who signal through their own actions what kind of behaviour is to be expected from members (Preece, 2004).
While there are many different systems of social control, it is largely unknown which systems work best in what social contexts. To make matters even more complicated, in most systems users can to some extent pretend to be trustworthy in ways that are difficult to detect. Hence, we need to understand more about what drives users to reveal correct or incorrect information. Under which conditions do they reveal information for strategic purposes and what type of information is more revealing? This implies several sub questions to our original research question:
How do people discern useful and reliable information from useless and unreliable information in online settings?
How can we present information in such a way that users can find the useful and reliable pieces of information more easily?
How can users be motivated to provide reliable information and how can the provision of unreliable information be minimized?
To what extent do the answers to the first three questions depend on the kind of online setting?
That the last question is a non-trivial one, might need some explanation. Just as in the offline case, the extent to which group members are involved in online groups partially determines the kind of behavior that is socially acceptable. An online self-help group has different implicit and explicit rules of conduct than an economic “community” of eBay users (Blank & Adams-Bloknieks, 2007). It is therefore likely that ways to improve the exchange of reliable information and in general appropriate conduct, differ across various communities (Matzat 2008). Factors that play a role are whether the group is formal or informal, whether members are extrinsically or intrinsically motivated, and the frequency of offline and online interaction between members.
For the project we anticipate doing research in several areas of application, of which we name a few. The first field of application is ‘medical information’. There exist a large variety of sites and groups offering medical help (see Eysenbach et al, 2004). This varies from sites with one or more “online physicians”, who offer consulting through the Internet, to self-help groups and user-forums where patients and others interested to exchange information about particular diseases. As medical information is often pivotal to a person’s well-being, the issue of trying to find or having to find reliable information plays an important role.
The second area is that of the social networking sites (Boyd & Ellison, 2007). There are many sites on which one can virtually “connect” to others, either as friends (Hyves, Facebook, Twitter, etc), potential dates (Fubar, OkCupid, etc) or as business contacts (LinkedIn, Plaxo, Xing, etc). Such networks can have positive effects: you can become connected to people you would otherwise not be able to connect to (Valkenburg, Peter, & Schouten, 2006). However, as long as relations remain online, it is relatively easy to mislead others, which can be detrimental to the whole idea of the social network (Lampe, Ellison, & Steinfield, 2007). If the risk that you are becoming connected to someone who you would never want to connect to offline is too large then a social networking site is likely to fail.
The third area is that of general economic and consumer sites, such as that of eBay, Amazon, but also Vergelijk, Kieskeurig, and Dinnersite. These sites rely strongly on the premise that users evaluate products, services and other users. This in itself is already a mystery because it is not clear what people motivates to actually contribute to the collective good here. Some people just want to help people, others want to brag or moan about their product choices (Beffers, 2007). Moreover, the way in which people deal with this information also shows peculiarities. People would say to be influenced more by negative information, and also tend to read more negative than positive reviews (Beffers, 2007), but are more likely to write positive reviews, and also rate positive reviews to be more helpful on amazon.
Beffers, T. (2007) Evaluating online information. Master’s Thesis. TIW, TM, Technische Universiteit Eindhoven.
Blank, T. O. & Adams-Blodnieks, M. (2007). The who and the what of usage of two cancer online communities. Computers in Human Behavior, 23, 1249-1257.
Boyd, D. M. & Ellison, N. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13, 210-230.
Eppler, M. J. & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting marketing, MIS, and related disciplines. The Information Society, 20, 325-344.
Eysenbach, G., Powell, J., Englesakis, M., Rizo, C., & Stern, A. (2004). Health related virtual communities and electronic support groups: systematic review of the effects of online peer to peer interactions. British Medical Journal, 328, 1166-1170.
Frank, R. H. (1988). Passions within reason. The strategic role of the emotions. New York, London: W.W. Norton & Company.
Lampe, C. A. C., Ellison, N., & Steinfield, C. (2007). A familiar face(book): profile elements as signals in an online social network. In Proceedings of the SIGCHI conference on Human factors in computing systems, 435-444.
Matzat, U. (2006). Knowledge Management in a Virtual Organization: Are embedded online communities of practice more successful than exclusively virtual ones? Report for NWO, project number 014-43-618.
Matzat, U. (2008) A theory of relational signals in online-groups. New Media & Society, (in press).
Preece, J. (2004). Etiquette online: From nice to necessary. Communications of the Association of computing Machinery (ACM), 47, 56-61.
Raub, W. & Weesie, J. (1990). Reputation and efficiency in social interactions: An example of network effects. American Journal of Sociology, 96, 626-654.
Snijders, C. & Zijdemann, R. (2004). Reputation and Internet Auctions: EBay and beyond. Analyse & Kritik, 26, 158-184.
Thelwall, M. (2008). Social networks, gender, and friending: An analysis of MySpace user profiles. Journal of the American Society for Information Science and Technology, (in press).
Valkenburg, P. M., Peter, J., & Schouten, A. P. (2006). Friend networking sites and their relationship to adolescents' well-being and social self-esteem. Cyberpsychology & Behavior, 9, 584-590.
Whitty, M. T. (2002). Liar, liar! An examination of how open, supportive and honest people are in chat rooms. Computers in Human Behavior, 18, 343-352.