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Some fear that personalised communication can lead to information cocoons or filter bubbles. For instance, a personalised news website could give more prominence to conservative or liberal media items, based on the (assumed) political interests of the user. As a result, users may encounter only a limited range of political ideas. We synthesise empirical research on the extent and effects of self-selected personalisation, where people actively choose which content they receive, and pre-selected personalisation, where algorithms personalise content for users without any deliberate user choice. We conclude that at present there is little empirical evidence that warrants any worries about filter bubbles.

Personally managing and protecting online privacy has become an essential part of everyday life. This research draws on the protection motivation theory (PMT) to investigate privacy protective behavior online. A two-wave panel study (N = 928) shows that (1) people rarely to occasionally protect their online privacy and (2) people most often delete cookies and browser history or decline cookies to protect their online privacy. In addition, (3) the perceived threat is high: People perceive the collection, usage, and sharing of personal information as a severe problem to which they are susceptible. The coping appraisal is mixed: Although people do have confidence in some protective measures, they have little confidence in their own efficacy to protect their online privacy. Moreover, privacy protective behavior is affected by perceived severity and response efficacy. These findings emphasize the relevance of the PMT in the context of privacy threats, and have important implications for regulators.

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