Hot Streaks on Social Media

Measuring the impact and success of human performance is common in various disciplines, including art, science, and sports. Quantifying impact also plays a key role on social media, where impact is usually defined as the reach of a user's content as captured by metrics such as the number of views, likes, retweets, or shares. In this paper, we study entire careers of Twitter users to understand properties of impact. We show that user impact tends to have certain characteristics: First, impact is clustered in time, such that the most impactful tweets of a user appear close to each other. Second, users commonly have 'hot streaks' of impact, i.e., extended periods of high-impact tweets. Third, impact tends to gradually build up before, and fall off after, a user's most impactful tweet. We attempt to explain these characteristics using various properties measured on social media, including the user's network, content, activity, and experience, and find that changes in impact are associated with significant changes in these properties. Our findings open interesting avenues for future research on virality and influence on social media.Comment: Accepted as a full paper at ICWSM 2019. Please cite the ICWSM versio

The Distribution of the Asymptotic Number of Citations to Sets of Publications by a Researcher or From an Academic Department Are Consistent With a Discrete Lognormal Model

How to quantify the impact of a researcher's or an institution's body of work is a matter of increasing importance to scientists, funding agencies, and hiring committees. The use of bibliometric indicators, such as the h-index or the Journal Impact Factor, have become widespread despite their known limitations. We argue that most existing bibliometric indicators are inconsistent, biased, and, worst of all, susceptible to manipulation. Here, we pursue a principled approach to the development of an indicator to quantify the scientific impact of both individual researchers and research institutions grounded on the functional form of the distribution of the asymptotic number of citations. We validate our approach using the publication records of 1,283 researchers from seven scientific and engineering disciplines and the chemistry departments at the 106 U.S. research institutions classified as "very high research activity". Our approach has three distinct advantages. First, it accurately captures the overall scientific impact of researchers at all career stages, as measured by asymptotic citation counts. Second, unlike other measures, our indicator is resistant to manipulation and rewards publication quality over quantity. Third, our approach captures the time-evolution of the scientific impact of research institutions.Comment: 20 pages, 11 figures, 3 table

A review of the characteristics of 108 author-level bibliometric indicators

An increasing demand for bibliometric assessment of individuals has led to a growth of new bibliometric indicators as well as new variants or combinations of established ones. The aim of this review is to contribute with objective facts about the usefulness of bibliometric indicators of the effects of publication activity at the individual level. This paper reviews 108 indicators that can potentially be used to measure performance on the individual author level, and examines the complexity of their calculations in relation to what they are supposed to reflect and ease of end-user application.Comment: to be published in Scientometrics, 201

Bright light therapy as part of a multicomponent management program improves sleep and functional outcomes in delirious older hospitalized adults.

ObjectiveDelirium is associated with poor outcomes following acute hospitalization. A specialized delirium management unit, the Geriatric Monitoring Unit (GMU), was established. Evening bright light therapy (2000-3000 lux; 6-10 pm daily) was added as adjunctive treatment, to consolidate circadian activity rhythms and improve sleep. This study examined whether the GMU program improved sleep, cognitive, and functional outcomes in delirious patients.MethodA total of 228 patients (mean age = 84.2 years) were studied. The clinical characteristics, delirium duration, delirium subtype, Delirium Rating Score (DRS), cognitive status (Chinese Mini-Mental State Examination), functional status (modified Barthel Index [MBI]), and chemical restraint use during the initial and predischarge phase of the patient's GMU admission were obtained. Nurses completed hourly 24-hour patient sleep logs, and from these, the mean total sleep time, number of awakenings, and sleep bouts (SB) were computed.ResultsThe mean delirium duration was 6.7 ± 4.6 days. Analysis of the delirium subtypes showed that 18.4% had hypoactive delirium, 30.2% mixed delirium, and 51.3% had hyperactive delirium. There were significant improvements in MBI scores, especially for the hyperactive and mixed delirium subtypes (P < 0.05). Significant improvements were noted on the DRS sleep-wake disturbance subscore, for all delirium-subtypes. The mean total sleep time (7.7 from 6.4 hours) (P < 0.05) and length of first SB (6.0 compared with 5.3 hours) (P < 0.05) improved, with decreased mean number of SBs and awakenings. The sleep improvements were mainly seen in the hyperactive delirium subtype.ConclusionThis study shows initial evidence for the clinical benefits (longer total sleep time, increased first SB length, and functional gains) of incorporating bright light therapy as part of a multicomponent delirium management program. The benefits appear to have occurred mainly in patients with hyperactive delirium, which merits further in-depth, randomized controlled studies

Race and Survival Bias in NBA Data

Cross sectional employment data is not random. Workers who survive to a longer level of tenure tend to have a higher level of productivity than those who exit earlier. Wage equations that use cross sectional data could be biased from the over sampling of high productive workers at long levels of tenure. The survival bias that arises in cross sectional data could possibly bias the coefficients in wage equations. This could lead to false positive conclusions concerning the presence of pay discrimination. Using 1989-2008 NBA data we explore the extent of survival bias in wage regressions in a setting in which worker productivity is extremely well documented through a variety of statistical measures. We then examined whether the survival bias affects the conclusions concerning racial pay discrimination. Key Words: NBA, survival bias, pay discrimination

Sequential Circuit Design for Embedded Cryptographic Applications Resilient to Adversarial Faults

In the relatively young field of fault-tolerant cryptography, the main research effort has focused exclusively on the protection of the data path of cryptographic circuits. To date, however, we have not found any work that aims at protecting the control logic of these circuits against fault attacks, which thus remains the proverbial Achilles’ heel. Motivated by a hypothetical yet realistic fault analysis attack that, in principle, could be mounted against any modular exponentiation engine, even one with appropriate data path protection, we set out to close this remaining gap. In this paper, we present guidelines for the design of multifault-resilient sequential control logic based on standard Error-Detecting Codes (EDCs) with large minimum distance. We introduce a metric that measures the effectiveness of the error detection technique in terms of the effort the attacker has to make in relation to the area overhead spent in implementing the EDC. Our comparison shows that the proposed EDC-based technique provides superior performance when compared against regular N-modular redundancy techniques. Furthermore, our technique scales well and does not affect the critical path delay