Determinanten der Selektion und Einstellungsbildung bei der Rezeption von Wissenschafts-informationen im Internet

互联网提供了大量有关科学问题的内容。这导致了收集信息的多种可能性，但也可能在确定相关和可信的内容并采取知情立场方面造成困难。在此背景下，该项目研究了外行人如何在博客等Web2.0应用程序中处理与科学相关的信息。基于说服模型(例如，Petty&Ccioppo，1986)和前两个项目阶段的发现，这些研究解决了关于态度形成以及读者评论和评级的影响(由于用户生成的反馈在Web 2.0环境中的重要性增加，见Walther&Jang，2012)的剩余问题。特别是，我们将调查在哪些情况下，相互矛盾的证据和当前科学辩论的复杂性体现在读者的态度上。为此，评估将包括潜在的矛盾心理和态度的确定性(Wagner，Brinol&Petty，2012)。在此背景下，两项实验研究考察了信息复杂性(信息侧性，比较了双面框架和实际的双面性)的影响；用户的认知需求和认识论信念被包括在调节变量中。两项进一步的研究考察了用户评论对正文信息提供反驳的效果。这些评论要么是有个人经历(样本)的评论，后者可能提供关于这个主题的进一步信息，但也可能导致对意见氛围的偏见看法，要么是涉及经验证据的评论。这两种类型的评论的影响是结合其他用户给出的帮助评级进行测试的。基于这些发现，最近提出的在线科学信息选择和处理模型(Krämer和温特提交)将在两个实验中进行扩展和测试，其中有一个新的示范性主题(在考虑不同的阅读目标和额外评估行为意图的情况下)。

The Internet provides a great deal of content on science-related issues. This leads to a multitude of possibilities to collect information, but may also cause difficulties in identifying relevant and credible pieces of content and coming to an informed stance. Against this background, this project examines how laypersons deal with science-related information in Web 2.0 applications such as blogs. Based on models of persuasion (e.g., Petty & Cacioppo, 1986) and findings of the first two project phases, the studies address remaining questions regarding attitude formation and the influence of reader comments and ratings (due to the increased importance of user-generated feedback in Web 2.0 settings, see Walther & Jang, 2012). In particular, we will investigate under which circumstances conflicting evidence and the complexity of current scientific debates are represented in readers' attitudes. For this purpose, the assessment will include potential ambivalence and the certainty of attitudes (Wagner, Brinol & Petty, 2012). In this context, two experimental studies investigate the influence of message complexity (message sidedness, with a comparison of two-sided framing and actual two-sidedness); users' need for cognition and epistemological beliefs are included as moderating variables. Two further studies examine the effects of user comments providing counterarguments against the message of the main article. These are either comments with personal experiences (exemplars), which may offer further information on the topic but may also lead to biased perceptions of the opinion climate, or comments referring to empirical evidence. The influence of these two types of comments is tested in combination with helpfulness ratings given by other users. Based on these findings, a recently suggested model on selection and processing of online science information (Krämer & Winter, submitted) will be extended and tested in two experiments with a new exemplary topic (under consideration of different reading goals and with an additional assessment of behavioral intentions).