Behaviors, adverse events, and dispositions: An empirical study of online discretion and information control

Journal of the American Society for Information Science and Technology (JASIST), 04/2010, Volume 61, Issue 7, p.1487-1501, 2010
Behaviors, adverse events, and dispositions: An empirical study of online discretion and information control
Coye Cheshire, Judd Antin, Elizabeth Churchill, Coye Cheshire, Judd Antin, Elizabeth Churchill

The authors develop hypotheses about three key correlates of attitudes about discretionary online behaviors and control over one’s own online information: frequency of engaging in risky online behaviors, experience of an online adverse event, and the disposition to be more or less trusting and cautious of others.

Through an analysis of survey results, they find that online adverse events do not necessarily relate to greater overall Web discretion, but they do significantly associate with users’ perceptions of Web information control.

However, the frequencies with which individuals engage in risky online activities and behaviors significantly associate with both online discretion and information control. In addition, general dispositions to trust and be cautious are strongly related to prudent Internet behavior and attitudes about managing personal online information.

The results of this study have clear consequences for our understanding of behaviors and attitudes that might lead to greater online social intelligence, or the ability to make prudent decisions in the presence of Internet uncertainties and risks. Implications for theory and practice are discussed.

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Reputation and feedback systems in online marketplaces are often biased, making it difficult to ascertain the quality of sellers. We use post-transaction, buyer-to-seller message traffic to detect signals of unsatisfactory transactions on eBay. We posit that a message sent after the item was paid for serves as a reliable indicator that the buyer may be unhappy with that purchase, particularly when the message included words associated with a negative experience. The fraction of a seller's message traffic that was negative predicts whether a buyer who transacts with this seller will stop purchasing on eBay, implying that platforms can use these messages as an additional signal of seller quality.