Partisan Asymmetries in Online Political Activity

We examine partisan differences in the behavior, communication patterns and social interactions of more than 18,000 politically-active Twitter users to produce evidence that points to changing levels of partisan engagement with the American online political landscape. Analysis of a network defined by the communication activity of these users in proximity to the 2010 midterm congressional elections reveals a highly segregated, well clustered partisan community structure. Using cluster membership as a high-fidelity (87% accuracy) proxy for political affiliation, we characterize a wide range of differences in the behavior, communication and social connectivity of left- and right-leaning Twitter users. We find that in contrast to the online political dynamics of the 2008 campaign, right-leaning Twitter users exhibit greater levels of political activity, a more tightly interconnected social structure, and a communication network topology that facilitates the rapid and broad dissemination of political information.Comment: 17 pages, 10 figures, 6 table

A Group-Based Yule Model for Bipartite Author-Paper Networks

This paper presents a novel model for author-paper networks, which is based on the assumption that authors are organized into groups and that, for each research topic, the number of papers published by a group is based on a success-breeds-success model. Collaboration between groups is modeled as random invitations from a group to an outside member. To analyze the model, a number of different metrics that can be obtained in author-paper networks were extracted. A simulation example shows that this model can effectively mimic the behavior of a real-world author-paper network, extracted from a collection of 900 journal papers in the field of complex networks.Comment: 13 pages (preprint format), 7 figure

Inference with interference between units in an fMRI experiment of motor inhibition

An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference between units within an experimental subject is likely, in part because the stimuli follow one another quickly and in part because human subjects learn or become experienced or primed or bored as the experiment proceeds. We use a recent fMRI experiment concerned with the inhibition of motor activity to illustrate and further develop recently proposed methodology for inference in the presence of interference. A simulation evaluates the power of competing procedures.Comment: Published by Journal of the American Statistical Association at http://www.tandfonline.com/doi/full/10.1080/01621459.2012.655954 . R package cin (Causal Inference for Neuroscience) implementing the proposed method is freely available on CRAN at https://CRAN.R-project.org/package=ci

Spin measurements for 147Sm+n resonances: Further evidence for non-statistical effects

We have determined the spins J of resonances in the 147Sm(n,gamma) reaction by measuring multiplicities of gamma-ray cascades following neutron capture. Using this technique, we were able to determine J values for all but 14 of the 140 known resonances below En = 1 keV, including 41 firm J assignments for resonances whose spins previously were either unknown or tentative. These new spin assignments, together with previously determined resonance parameters, allowed us to extract separate level spacings and neutron strength functions for J = 3 and 4 resonances. Furthermore, several statistical test of the data indicate that very few resonances of either spin have been missed below En = 700eV. Because a non-statistical effect recently was reported near En = 350 eV from an analysis of 147Sm(n,alpha) data, we divided the data into two regions; 0 < En < 350 eV and 350 < En < 700 eV. Using neutron widths from a previous measurement and published techniques for correcting for missed resonances and for testing whether data are consistent with a Porter-Thomas distribution, we found that the reduced-neutron-width distribution for resonances below 350 eV is consistent with the expected Porter-Thomas distribution. On the other hand, we found that reduced-neutron-width data in the 350 < En < 700 eV region are inconsistent with a Porter-Thomas distribution, but in good agreement with a chi-squared distribution having two or more degrees of freedom. We discuss possible explanations for these observed non-statistical effects and their possible relation to similar effects previously observed in other nuclides.Comment: 40 pages, 13 figures, accepted by Phys. Rev.

A meta-analysis of state-of-the-art electoral prediction from Twitter data

Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightforward and the prevailing view is overly optimistic. This is problematic because while simple approaches are assumed to be good enough, core problems are not addressed. Thus, this paper aims to (1) provide a balanced and critical review of the state of the art; (2) cast light on the presume predictive power of Twitter data; and (3) depict a roadmap to push forward the field. Hence, a scheme to characterize Twitter prediction methods is proposed. It covers every aspect from data collection to performance evaluation, through data processing and vote inference. Using that scheme, prior research is analyzed and organized to explain the main approaches taken up to date but also their weaknesses. This is the first meta-analysis of the whole body of research regarding electoral prediction from Twitter data. It reveals that its presumed predictive power regarding electoral prediction has been rather exaggerated: although social media may provide a glimpse on electoral outcomes current research does not provide strong evidence to support it can replace traditional polls. Finally, future lines of research along with a set of requirements they must fulfill are provided.Comment: 19 pages, 3 table

Movement and Habitat Selection by Invasive Asian Carps in a Large River

We evaluated the habitat use and movements of 50 adult bighead carp Hypophthalmichthys nobilis and 50 silver carp H. molitrix by means of ultrasonic telemetry during spring–summer 2004 and 2005 to gain insight into the conditions that facilitate their establishment, persistence, and dispersal in the lower Illinois River (river kilometer 0–130). Movement and habitat use were monitored with stationary receivers and boat-mounted tracking. The relative availability of four macrohabitat categories (main channel, island side channel, channel border, and connected backwater) was quantified to determine selection; discriminant function analysis was used to evaluate changes in physical characteristics within each category. A flood pulse occurred in spring through early summer of 2004 but not 2005. Movement rates (km/week) of both species were positively correlated with flow but not with temperature. Including data from stationary receivers greatly increased estimates of daily movement. During low summer flow, both species typically selected channel borders and avoided the main channel and backwaters. Both species rarely occupied depths over 4 m, regardless of abiotic conditions. Flood pulses appear to trigger dispersal, while habitat use is only specific during low summer flow. Thus, movement prevention efforts (e.g., dispersal barriers) will require particular vigilance during late-winter or spring flooding, and controlled removal (e.g., harvest) should be directed toward selected habitats during summer

Environmental variables, habitat discontinuity and life history shaping the genetic structure of Pomatoschistus marmoratus

Coastal lagoons are semi-isolated ecosystems exposed to wide fluctuations of environmental conditions and showing habitat fragmentation. These features may play an important role in separating species into different populations, even at small spatial scales. In this study, we evaluate the concordance between mitochondrial (previous published data) and nuclear data analyzing the genetic variability of Pomatoschistus marmoratus in five localities, inside and outside the Mar Menor coastal lagoon (SE Spain) using eight microsatellites. High genetic diversity and similar levels of allele richness were observed across all loci and localities, although significant genic and genotypic differentiation was found between populations inside and outside the lagoon. In contrast to the FST values obtained from previous mitochondrial DNA analyses (control region), the microsatellite data exhibited significant differentiation among samples inside the Mar Menor and between lagoonal and marine samples. This pattern was corroborated using Cavalli-Sforza genetic distances. The habitat fragmentation inside the coastal lagoon and among lagoon and marine localities could be acting as a barrier to gene flow and contributing to the observed genetic structure. Our results from generalized additive models point a significant link between extreme lagoonal environmental conditions (mainly maximum salinity) and P. marmoratus genetic composition. Thereby, these environmental features could be also acting on genetic structure of coastal lagoon populations of P. marmoratus favoring their genetic divergence. The mating strategy of P. marmoratus could be also influencing our results obtained from mitochondrial and nuclear DNA. Therefore, a special consideration must be done in the selection of the DNA markers depending on the reproductive strategy of the species

Linking Adult Reproduction and Larval Density of Invasive Carp in a Large River

Identifying how temporal variation in the environment affects reproductive success of invasive alien species will aid in predicting future establishment and tracking dynamics of established populations. Asian carp Hypophthalmichthys spp. have become a nuisance in recent years in the Mississippi River basin. Their populations are apparently expanding, indicating favorable conditions for reproduction. During 2004 and 2005, we quantified mean density of Asian carp larvae, mean monthly gonadosomatic index (GSI) of adult males and females, and number of eggs within mature females in the lower Illinois River, a major tributary of the Mississippi River. A flood (water velocity ≥ 0.7 m/s) and drought (\u3c0.2 m/s) occurred during apparent spawning in 2004 and 2005, respectively. During 2004, Asian carp larvae were found during 32% of sampling weeks; mean GSI and fecundity were relatively low for adults, probably reflecting partially spawned individuals and perhaps low reproductive investment. During the drought of 2005, larval stages were present during only one (5%) of the sampling weeks, whereas mean GSI and fecundity of adults were high through summer. Females resorbed their eggs instead of spawning during this year. Spawning conditions during low water periods appear to be unsuitable for Asian carps, inhibiting adult spawning and yielding few larvae. Spawning conditions during 2004 were better but still yielded low densities of larvae relative to native fishes. Reproduction in the lower Illinois River appears to be linked to river flow and its impact on adult spawning decisions, but conditions for strong year-class production (i.e., high larval densities) may be rarer than previously expected

Inheritance patterns in citation networks reveal scientific memes

Memes are the cultural equivalent of genes that spread across human culture by means of imitation. What makes a meme and what distinguishes it from other forms of information, however, is still poorly understood. Our analysis of memes in the scientific literature reveals that they are governed by a surprisingly simple relationship between frequency of occurrence and the degree to which they propagate along the citation graph. We propose a simple formalization of this pattern and we validate it with data from close to 50 million publication records from the Web of Science, PubMed Central, and the American Physical Society. Evaluations relying on human annotators, citation network randomizations, and comparisons with several alternative approaches confirm that our formula is accurate and effective, without a dependence on linguistic or ontological knowledge and without the application of arbitrary thresholds or filters.Comment: 8 two-column pages, 5 figures; accepted for publication in Physical Review

Computational fact checking from knowledge networks

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation