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In information-rich environments, the competition for users' attention leadsto a flood of content from which people often find hard to sort out the mostrelevant and useful pieces. Using Twitter as a case study, we applied anattention economy solution to generate the most informative tweets for itsusers. By considering the novelty and popularity of tweets as objectivemeasures of their relevance and utility, we used the Huberman-Wu algorithm toautomatically select the ones that will receive the most attention in the nexttime interval. Their predicted popularity was confirmed by using Twitter datacollected for a period of 2 months.

Deciding what to display: maximizing the information value of social media