We analyze the online response to the preprint publication of a cohort of 4,606 scientific articles submitted to the preprint database arXiv.org between October 2010 and May 2011. We study three forms of responses to these preprints: downloads on the arXiv.org site, mentions on the social media site Twitter, and early citations in the scholarly record. We perform two analyses. First, we analyze the delay and time span of article downloads and Twitter mentions following submission, to understand the temporal configuration of these reactions and whether one precedes or follows the other. Second, we run regression and correlation tests to investigate the relationship between Twitter mentions, arXiv downloads, and article citations. We find that Twitter mentions and arXiv downloads of scholarly articles follow two distinct temporal patterns of activity, with Twitter mentions having shorter delays and narrower time spans than arXiv downloads. We also find that the volume of Twitter mentions is statistically correlated with arXiv downloads and early citations just months after the publication of a preprint, with a possible bias that favors highly mentioned articles.

The widespread adoption of mobile devices that record the communications, social relations, and movements of billions of individuals in great detail presents unique opportunities for the study of social structures and human dynamics at very large scales. This is particularly the case for developing countries where social and economic data can be hard to obtain and is often too sparse for real-time analytics. Here we leverage mobile call log data from Côte d'Ivoire to analyze the relations between its nationwide communications network and the socioeconomic dynamics of its regional economies. We introduce the CallRank indicator to quantify the relative importance of an area on the basis of call records, and show that a region's ratio of in-and outgoing calls can predict its income level. We detect a communication divide between rich and poor regions of Côte d'Ivoire, which corresponds to existing socioeconomic data. Our results demonstrate the potential of mobile communication data to monitor the economic development and social dynamics of low-income developing countries in the absence of extensive econometric and social data. Our work may support efforts to stimulate sustainable economic development and to reduce poverty and inequality.

During the past few decades, the rate of publication retractions has increased dramatically in academia. In this study, we investigate retractions from a quantitative perspective, aiming to answer two fundamental questions. One, how do retractions influence the scholarly impact of retracted papers, authors, and institutions? Two, does this influence propagate to the wider academic community through scholarly associations? Specifically, we analyzed a set of retracted articles indexed in Thomson Reuters Web of Science (WoS), and ran multiple experiments to compare changes in scholarly impact against a control set of nonretracted articles, authors, and institutions. We further applied the Granger Causality test to investigate whether different scientific topics are dynamically affected by retracted papers occurring within those topics. Our results show two key findings: first, the scholarly impact of retracted papers and authors significantly decreases after retraction, and the most severe impact decrease correlates with retractions based on proven, purposeful scientific misconduct; second, this retraction penalty does not seem to spread through the broader scholarly social graph, but instead has a limited and localized effect. Our findings may provide useful insights for scholars or science committees to evaluate the scholarly value of papers, authors, or institutions related to retractions.

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