#Bigbirds never die: Understanding social dynamics of emergent hashtag

We examine the growth, survival, and context of 256 novel hashtags during the 2012 U.S. presidential debates. Our analysis reveals the trajectories of hashtag use fall into two distinct classes: “winners” that emerge more quickly and are sustained for longer periods of time than other “also-rans” hashtags. We propose a “conversational vibrancy” framework to capture dynamics of hashtags based on their topicality, interactivity, diversity, and prominence. Statistical analyses of the growth and persistence of hashtags reveal novel relationships between features of this framework and the relative success of hashtags. Specifically, retweets always contribute to faster hashtag adoption, replies extend the life of “winners” while having no effect on “also-rans.” This is the first study on the lifecycle of hashtag adoption and use in response to purely exogenous shocks. We draw on theories of uses and gratification, organizational ecology, and language evolution to discuss these findings and their implications for understanding social influence and collective action in social media more generally

Superaging correlation function and ergodicity breaking for Brownian motion in logarithmic potentials

We consider an overdamped Brownian particle moving in a confining asymptotically logarithmic potential, which supports a normalized Boltzmann equilibrium density. We derive analytical expressions for the two-time correlation function and the fluctuations of the time-averaged position of the particle for large but finite times. We characterize the occurrence of aging and nonergodic behavior as a function of the depth of the potential, and support our predictions with extensive Langevin simulations. While the Boltzmann measure is used to obtain stationary correlation functions, we show how the non-normalizable infinite covariant density is related to the super-aging behavior.Comment: 16 pages, 6 figure

Generalized Arcsine Law and Stable Law in an Infinite Measure Dynamical System

Limit theorems for the time average of some observation functions in an infinite measure dynamical system are studied. It is known that intermittent phenomena, such as the Rayleigh-Benard convection and Belousov-Zhabotinsky reaction, are described by infinite measure dynamical systems.We show that the time average of the observation function which is not the $L^1(m)$ function, whose average with respect to the invariant measure $m$ is finite, converges to the generalized arcsine distribution. This result leads to the novel view that the correlation function is intrinsically random and does not decay. Moreover, it is also numerically shown that the time average of the observation function converges to the stable distribution when the observation function has the infinite mean.Comment: 8 pages, 8 figure

Rising Tides or Rising Stars?

Abstract ''Media events'' generate conditions of shared attention as many users simultaneously tune in with the dual screens of broadcast and social media to view and participate. We examine how collective patterns of user behavior under conditions of shared attention are distinct from other ''bursts'' of activity like breaking news events. Using 290 million tweets from a panel of 193,532 politically active Twitter users, we compare features of their behavior during eight major events during the 2012 U.S. presidential election to examine how patterns of social media use change during these media events compared to ''typical'' time and whether these changes are attributable to shifts in the behavior of the population as a whole or shifts from particular segments such as elites. Compared to baseline time periods, our findings reveal that media events not only generate large volumes of tweets, but they are also associated with (1) substantial declines in interpersonal communication, (2) more highly concentrated attention by replying to and retweeting particular users, and (3) elite users predominantly benefiting from this attention. These findings empirically demonstrate how bursts of activity on Twitter during media events significantly alter underlying social processes of interpersonal communication and social interaction. Because the behavior of large populations within socio-technical systems can change so dramatically, our findings suggest the need for further research about how social media responses to media events can be used to support collective sensemaking, to promote informed deliberation, and to remain resilient in the face of misinformation

Regional mutagenesis of the gene encoding the phage Mu late gene activator C identifies two separate regions important for DNA binding

Lytic development of bacteriophage Mu is controlled by a regulatory cascade and involves three phases of transcription: early, middle and late. Late transcription requires the host RNA polymerase holoenzyme and a 16.5-kDa Mu-encoded activator protein C. Consistent with these requirements, the four late promoters Plys, PI, PP and Pmom have recognizable −10 hexamers but lack typical −35 hexamers. The C protein binds to a 16-bp imperfect dyad-symmetrical sequence element centered at −43.5 and overlapping the −35 region. Based on the crystal structure of the closely related Mor protein, the activator of Mu middle transcription, we predict that two regions of C are involved in DNA binding: a helix-turn-helix region and a β-strand region linking the dimerization and helix-turn-helix domains. To test this hypothesis, we carried out mutagenesis of the corresponding regions of the C gene by degenerate oligonucleotide-directed PCR and screened the resulting mutants for their ability to activate a Plys-galK fusion. Analysis of the mutant proteins by gel mobility shift, β-galactosidase and polyacrylamide gel electrophoresis assays identified a number of amino acid residues important for C DNA binding in both regions

On distributions of functionals of anomalous diffusion paths

Functionals of Brownian motion have diverse applications in physics, mathematics, and other fields. The probability density function (PDF) of Brownian functionals satisfies the Feynman-Kac formula, which is a Schrodinger equation in imaginary time. In recent years there is a growing interest in particular functionals of non-Brownian motion, or anomalous diffusion, but no equation existed for their PDF. Here, we derive a fractional generalization of the Feynman-Kac equation for functionals of anomalous paths based on sub-diffusive continuous-time random walk. We also derive a backward equation and a generalization to Levy flights. Solutions are presented for a wide number of applications including the occupation time in half space and in an interval, the first passage time, the maximal displacement, and the hitting probability. We briefly discuss other fractional Schrodinger equations that recently appeared in the literature.Comment: 25 pages, 4 figure

TGFBR1*6A and Int7G24A variants of transforming growth factor-β receptor 1 in Swedish familial and sporadic breast cancer

Two common variants in transforming growth factor-β receptor 1 (TGFBR1), TGFBR1*6A and Int7G24A, A allele, have been shown to act as low-penetrance tumour susceptibility alleles in several common cancers, including breast cancer. We evaluated the TGFBR1 9A/6A and Int7G24A variant frequencies in two breast cancer cohorts; a population-based cohort of breast cancer with defined family history (n=459) and in breast cancer patients from a familial cancer clinic (n=340) and in 856 controls from the Stockholm region. The familial patients from both cohorts were further divided into high- and low-risk familial breast cancer based on pedigree analysis. There was no overall association with either variant and breast cancer risk. The TGFBR1*6A allelic frequency was, however, higher in low-risk familial breast cancer (0.138), compared to controls (0.106; P=0.04). No significant difference was found in the high-risk familial (0.102) or sporadic cases (0.109; P=0.83 and 0.83, respectively). TGFBR1*6A carrier status was further associated with a high-grade sporadic breast cancer (odds ratio: 2.27; 95% confidence interval: 1.01–5.11; P=0.049). These results indicate that the TGFBR1*6A variant may be associated with an increased risk of low-risk familial breast cancer and might be a marker for poorly differentiated breast cancer. The Int7G24A variant was not associated with breast cancer risk or clinical presentation of the disease including prognosis in our material