2,150 research outputs found
Cascades: A view from Audience
Cascades on online networks have been a popular subject of study in the past
decade, and there is a considerable literature on phenomena such as diffusion
mechanisms, virality, cascade prediction, and peer network effects. However, a
basic question has received comparatively little attention: how desirable are
cascades on a social media platform from the point of view of users? While
versions of this question have been considered from the perspective of the
producers of cascades, any answer to this question must also take into account
the effect of cascades on their audience. In this work, we seek to fill this
gap by providing a consumer perspective of cascade.
Users on online networks play the dual role of producers and consumers.
First, we perform an empirical study of the interaction of Twitter users with
retweet cascades. We measure how often users observe retweets in their home
timeline, and observe a phenomenon that we term the "Impressions Paradox": the
share of impressions for cascades of size k decays much slower than frequency
of cascades of size k. Thus, the audience for cascades can be quite large even
for rare large cascades. We also measure audience engagement with retweet
cascades in comparison to non-retweeted content. Our results show that cascades
often rival or exceed organic content in engagement received per impression.
This result is perhaps surprising in that consumers didn't opt in to see tweets
from these authors. Furthermore, although cascading content is widely popular,
one would expect it to eventually reach parts of the audience that may not be
interested in the content. Motivated by our findings, we posit a theoretical
model that focuses on the effect of cascades on the audience. Our results on
this model highlight the balance between retweeting as a high-quality content
selection mechanism and the role of network users in filtering irrelevant
content
Precision medicine for suicidality: from universality to subtypes and personalization
Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a âliquid biopsyâ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator
Localizability of Wireless Sensor Networks: Beyond Wheel Extension
A network is called localizable if the positions of all the nodes of the
network can be computed uniquely. If a network is localizable and embedded in
plane with generic configuration, the positions of the nodes may be computed
uniquely in finite time. Therefore, identifying localizable networks is an
important function. If the complete information about the network is available
at a single place, localizability can be tested in polynomial time. In a
distributed environment, networks with trilateration orderings (popular in real
applications) and wheel extensions (a specific class of localizable networks)
embedded in plane can be identified by existing techniques. We propose a
distributed technique which efficiently identifies a larger class of
localizable networks. This class covers both trilateration and wheel
extensions. In reality, exact distance is almost impossible or costly. The
proposed algorithm based only on connectivity information. It requires no
distance information
Moments of the Proton F2 Structure Function at Low Q2
The Q^2 dependence of inclusive electron-proton scattering F_2 structure
function data in both the nucleon resonance region and the deep inelastic
region, at momentum transfers below 5 (GeV/c)^2, is investigated. Moments of
F_2 are constructed, down to momentum transfers of Q^2 ~ 0.1 (GeV/c)^2. The
second moment is only slowly varying with Q^2 down to Q^2 ~ 1 (GeV/c)^2, which
is a reflection of duality. Below Q^2 of 1 (GeV/c)^2, the Q^2 dependence of the
moments is predominantly governed by the elastic contribution, whereas the
inelastic channels still seem governed by local duality.Comment: 11 page paper, 1 LaTeX file, 10 postscript figure file
Parton-Hadron Duality in Unpolarised and Polarised Structure Functions
We study the phenomenon of parton-hadron duality in both polarised and
unpolarised electron proton scattering using the HERMES and the Jefferson Lab
data, respectively. In both cases we extend a systematic perturbative QCD based
analysis to the integrals of the structure functions in the resonance region.
After subtracting target mass corrections and large x resummation effects, we
extract the remaining power corrections up to order 1/Q^2. We find a sizeable
suppression of these terms with respect to analyses using deep inelastic
scattering data. The suppression appears consistently in both polarised and
unpolarised data, except for the low Q^2 polarised data, where a large negative
higher twist contribution remains. Possible scenarios generating this behavior
are discussed.Comment: 17 pages, 9 figure
Local Duality Predictions for x ~ 1 Structure Functions
Recent data on the proton F_2 structure function in the resonance region
suggest that local quark-hadron duality works remarkably well for each of the
low-lying resonances, including the elastic, to rather low values of Q^2. We
derive model-independent relations between structure functions at x ~ 1 and
elastic electromagnetic form factors, and predict the x -> 1 behavior of
nucleon polarization asymmetries and the neutron to proton structure function
ratios from available data on nucleon electric and magnetic form factors.Comment: 10 pages, 2 figures, typos in Eq. (2) correcte
Pedagogic model for Deeply Virtual Compton Scattering with quark-hadron duality
We show how quark-hadron duality can emerge for valence spin averaged
structure functions, and for the non-forward distributions of Deeply Virtual
Compton Scattering. Novel factorisations of the non-forward amplitudes are
proposed. Some implications for large angle scattering and deviations from the
quark counting rules are illustrated.Comment: Version accepted by Phys. Rev.
Subprocess Size in Hard Exclusive Scattering
The interaction region of hard exclusive hadron scattering can have a large
transverse size due to endpoint contributions, where one parton carries most of
the hadron momentum. The endpoint region is enhanced and can dominate in
processes involving multiple scattering and quark helicity flip. The endpoint
Fock states have perturbatively short lifetimes and scatter softly in the
target. We give plausible arguments that endpoint contributions can explain the
apparent absence of color transparency in fixed angle exclusive scattering and
the dimensional scaling of transverse rho photoproduction at high momentum
transfer, which requires quark helicity flip. We also present a quantitative
estimate of Sudakov effects.Comment: 16 pages, 4 figures, JHEP style; v2: quantitative estimate of Sudakov
effects and more detailed discussion of endpoint behaviour of meson
distribution amplitude added, few other clarifications, version to appear in
Phys. Rev.
Competition and Selection Among Conventions
In many domains, a latent competition among different conventions determines
which one will come to dominate. One sees such effects in the success of
community jargon, of competing frames in political rhetoric, or of terminology
in technical contexts. These effects have become widespread in the online
domain, where the data offers the potential to study competition among
conventions at a fine-grained level.
In analyzing the dynamics of conventions over time, however, even with
detailed on-line data, one encounters two significant challenges. First, as
conventions evolve, the underlying substance of their meaning tends to change
as well; and such substantive changes confound investigations of social
effects. Second, the selection of a convention takes place through the complex
interactions of individuals within a community, and contention between the
users of competing conventions plays a key role in the convention's evolution.
Any analysis must take place in the presence of these two issues.
In this work we study a setting in which we can cleanly track the competition
among conventions. Our analysis is based on the spread of low-level authoring
conventions in the eprint arXiv over 24 years: by tracking the spread of macros
and other author-defined conventions, we are able to study conventions that
vary even as the underlying meaning remains constant. We find that the
interaction among co-authors over time plays a crucial role in the selection of
them; the distinction between more and less experienced members of the
community, and the distinction between conventions with visible versus
invisible effects, are both central to the underlying processes. Through our
analysis we make predictions at the population level about the ultimate success
of different synonymous conventions over time--and at the individual level
about the outcome of "fights" between people over convention choices.Comment: To appear in Proceedings of WWW 2017, data at
https://github.com/CornellNLP/Macro
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