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This research investigates how cues describing the authors of user-generated online science articles in blogs, and indications about whether the articles are 1-sided or 2-sided, affect others' decision about which content to read. It extended the elaboration likelihood model (ELM; Petty & Cacioppo, 1986), to predict whether better-quality arguments and individuals' need for cognition affected their content selections. In 2 experiments, 121 parents were asked to search for information on a blog concerning the effects of violent media. Results showed a general preference for texts composed by users with greater expertise and for 2-sided messages. Need for cognition magnified the effect of message sidedness, suggesting that the ELM is relevant for blogs and the selection of user-generated science stories.
Winter et al. (Mon,) studied this question.