199 research outputs found
When is it Biased? Assessing the Representativeness of Twitter's Streaming API
Twitter has captured the interest of the scientific community not only for
its massive user base and content, but also for its openness in sharing its
data. Twitter shares a free 1% sample of its tweets through the "Streaming
API", a service that returns a sample of tweets according to a set of
parameters set by the researcher. Recently, research has pointed to evidence of
bias in the data returned through the Streaming API, raising concern in the
integrity of this data service for use in research scenarios. While these
results are important, the methodologies proposed in previous work rely on the
restrictive and expensive Firehose to find the bias in the Streaming API data.
In this work we tackle the problem of finding sample bias without the need for
"gold standard" Firehose data. Namely, we focus on finding time periods in the
Streaming API data where the trend of a hashtag is significantly different from
its trend in the true activity on Twitter. We propose a solution that focuses
on using an open data source to find bias in the Streaming API. Finally, we
assess the utility of the data source in sparse data situations and for users
issuing the same query from different regions
Finding Eyewitness Tweets During Crises
Disaster response agencies have started to incorporate social media as a
source of fast-breaking information to understand the needs of people affected
by the many crises that occur around the world. These agencies look for tweets
from within the region affected by the crisis to get the latest updates of the
status of the affected region. However only 1% of all tweets are geotagged with
explicit location information. First responders lose valuable information
because they cannot assess the origin of many of the tweets they collect. In
this work we seek to identify non-geotagged tweets that originate from within
the crisis region. Towards this, we address three questions: (1) is there a
difference between the language of tweets originating within a crisis region
and tweets originating outside the region, (2) what are the linguistic patterns
that can be used to differentiate within-region and outside-region tweets, and
(3) for non-geotagged tweets, can we automatically identify those originating
within the crisis region in real-time
Conformational perturbation, allosteric modulation of cellular signaling pathways, and disease in P23H rhodopsin
In this investigation we use THz spectroscopy and MD simulation to study the functional dynamics and conformational stability of P23H rhodopsin. The P23H mutation of rod opsin is the most common cause of human binding autosomal dominant retinitis pigmentosa (ADRP), but the precise mechanism by which this mutation leads to photoreceptor cell degeneration has not yet been elucidated. Our measurements confirm conformational instability in the global modes of the receptor and an activestate that uncouples the torsional dynamics of the retinal with protein functional modes, indicating inefficient signaling in P23H and a drastically altered mechanism of activation when contrasted with the wild-type receptor. Further, our MD simulations indicate that P23H rhodopsin is not functional as a monomer but rather, due to the instability of the mutant receptor, preferentially adopts a specific homodimerization motif. The preferred homodimer configuration induces structural changes in the receptor tertiary structure that reduces the affinity of the receptor for the retinal and significantly modifies the interactions of the Meta-II signaling state. We conjecture that the formation of the specific dimerization motif of P23H rhodopsin represents a cellular-wide signaling perturbation that is directly tied with the mechanism of P23H disease pathogenesis. Our results also support a direct role for rhodopsin P23H dimerization in photoreceptor rod death
Multiagentensimulation sozialer Phänomene: eine praktische Einführung
'Simulationen sind Nachbildungen von Abläufen in realen und meist komplexen Systemen. Multiagentensimulationen beschreiben das Verhalten der einzelnen Akteure dieser Systeme. In den Sozialwissenschaften finden Multiagentensimulationen zunehmend Verbreitung (Gilbert & Troitzsch 2005, Gilbert 2007, Miller et al. 2007). Dies ist vor allem durch die fortschreitenden Entwicklungen im Bereich der Homecomputer ermöglicht, da Multiagentensimulationen ohne moderne EDV-Infrastruktur undenkbar wäre. Dieser Artikel gibt im ersten Teil eine Einführung in die Theorie der Modellbildung und Simulation sowie einen Abschnitt zur Simulation als virtuelles Experiment. Der zweite Teil dient der praktischen Einführung in die Simulationsumgebung StarLogo. Simulationsumgebungen werden dabei als inhaltsneutrale, computerbasierte Tools verstanden, in denen komplexe, reale Systeme nachgebildet und simuliert werden können. Ziel des vorliegenden Artikels ist es, Sozialwissenschaftlerinnen und Sozialwissenschaftler ohne Erfahrungen aus dem Bereich der Programmierung in die Programmerstellung von Multiagentensimulationen einzuführen und zur Umsetzung von eigenen Projekten anzuregen und zu motivieren.' (Autorenreferat
Vibrational resonance, allostery, and activation in rhodopsin-like G protein-coupled receptors
G protein-coupled receptors are a large family of membrane proteins activated by a variety of structurally diverse ligands making them highly adaptable signaling molecules. Despite recent advances in the structural biology of this protein family, the mechanism by which ligands induce allosteric changes in protein structure and dynamics for its signaling function remains a mystery. Here, we propose the use of terahertz spectroscopy combined with molecular dynamics simulation and protein evolutionary network modeling to address the mechanism of activation by directly probing the concerted fluctuations of retinal ligand and transmembrane helices in rhodopsin. This approach allows us to examine the role of conformational heterogeneity in the selection and stabilization of specific signaling pathways in the photo-activation of the receptor. We demonstrate that ligand-induced shifts in the conformational equilibrium prompt vibrational resonances in the protein structure that link the dynamics of conserved interactions with fluctuations of the active-state ligand. The connection of vibrational modes creates an allosteric association of coupled fluctuations that forms a coherent signaling pathway from the receptor ligand-binding pocket to the G-protein activation region. Our evolutionary analysis of rhodopsin-like GPCRs suggest that specific allosteric sites play a pivotal role in activating structural fluctuations that allosterically modulate functional signals
Affective and interactional polarization align across countries
Political polarization plays a pivotal and potentially harmful role in a
democracy. However, existing studies are often limited to a single country and
one form of polarization, hindering a comprehensive understanding of the
phenomena. Here we investigate how affective and interactional polarization are
related across nine countries (Canada, France, Germany, Italy, Poland, Spain,
Turkey, UK, USA). First, we show that political interaction networks are
polarized on Twitter. Second, we reveal that out-group interactions, defined by
the network, are more toxic than in-group interactions, meaning that affective
and interactional polarization are aligned. Third, we show that out-group
interactions receive lower engagement than in-group interactions. Finally, we
show that the political right reference lower reliability media than the
political left, and that interactions between politically engaged accounts are
limited and rarely reciprocated. These results hold across countries and
represent a first step towards a more unified understanding of polarization.Comment: 13 pages, 6 figures, 68 reference
This Sample seems to be good enough! Assessing Coverage and Temporal Reliability of Twitter's Academic API
Because of its willingness to share data with academia and industry, Twitter
has been the primary social media platform for scientific research as well as
for the consulting of businesses and governments in the last decade. In recent
years, a series of publications have studied and criticized Twitter's APIs and
Twitter has partially adapted its existing data streams. The newest Twitter API
for Academic Research allows to "access Twitter's real-time and historical
public data with additional features and functionality that support collecting
more precise, complete, and unbiased datasets." The main new feature of this
API is the possibility of accessing the full archive of all historic Tweets. In
this article, we will take a closer look at the Academic API and will try to
answer two questions. First, are the datasets collected with the Academic API
complete? Secondly, since Twitter's Academic API delivers historic Tweets as
represented on Twitter at the time of data collection, we need to understand
how much data is lost over time due to Tweet and account removal from the
platform. Our work shows evidence that Twitter's Academic API can indeed create
(almost) complete samples of Twitter data based on a wide variety of search
terms. We also provide evidence that Twitter's data endpoint v2 delivers better
samples than the previously used endpoint v1.1. Furthermore, collecting Tweets
with the Academic API at the time of studying a phenomenon rather than creating
local archives of stored Tweets, allows for a straightforward way of following
Twitter's developer agreement. Finally, we will also discuss technical
artifacts and implications of the Academic API. We hope that our work can add
another layer of understanding of Twitter data collections leading to more
reliable studies of human behavior via social media data
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