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

因特网提供了大量与科学有关的问题的内容。这导致了收集信息的多种可能性，但也可能导致难以确定相关和可信的内容并形成知情的立场。在此背景下，本项目探讨如何外行处理与科学相关的信息在Web 2.0应用程序，如博客。基于说服模型（例如，Petty & Cacioppo，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和读者评论和评级影响的剩余问题（由于Web 2.0环境中用户生成的反馈越来越重要，见Walther & Jang，2012）。特别是，我们将调查在何种情况下，相互矛盾的证据和当前科学辩论的复杂性在读者的态度。为此，评估将包括潜在的矛盾心理和态度的确定性（瓦格纳，Brinol和Petty，2012年）。在这种情况下，两个实验研究调查的影响，信息的复杂性（信息的片面性，与双边框架和实际的双边性的比较），用户的认知需求和认识论的信念包括作为调节变量。两个进一步的研究探讨了用户评论的影响，提供反驳的主要文章的信息。这些评论要么是个人经历（范例），可能提供关于该主题的进一步信息，但也可能导致对舆论气候的偏见，要么是参考经验证据的评论。这两种类型的评论的影响力进行测试，结合其他用户给出的有用性评级。基于这些发现，最近建议的模型选择和处理的在线科学信息（Krämer和Winter，提交）将扩展和测试在两个实验中的一个新的示例性主题（考虑不同的阅读目标和行为意图的额外评估）。

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).