298 research outputs found
Collective emotions online and their influence on community life
E-communities, social groups interacting online, have recently become an
object of interdisciplinary research. As with face-to-face meetings, Internet
exchanges may not only include factual information but also emotional
information - how participants feel about the subject discussed or other group
members. Emotions are known to be important in affecting interaction partners
in offline communication in many ways. Could emotions in Internet exchanges
affect others and systematically influence quantitative and qualitative aspects
of the trajectory of e-communities? The development of automatic sentiment
analysis has made large scale emotion detection and analysis possible using
text messages collected from the web. It is not clear if emotions in
e-communities primarily derive from individual group members' personalities or
if they result from intra-group interactions, and whether they influence group
activities. We show the collective character of affective phenomena on a large
scale as observed in 4 million posts downloaded from Blogs, Digg and BBC
forums. To test whether the emotions of a community member may influence the
emotions of others, posts were grouped into clusters of messages with similar
emotional valences. The frequency of long clusters was much higher than it
would be if emotions occurred at random. Distributions for cluster lengths can
be explained by preferential processes because conditional probabilities for
consecutive messages grow as a power law with cluster length. For BBC forum
threads, average discussion lengths were higher for larger values of absolute
average emotional valence in the first ten comments and the average amount of
emotion in messages fell during discussions. Our results prove that collective
emotional states can be created and modulated via Internet communication and
that emotional expressiveness is the fuel that sustains some e-communities.Comment: 23 pages including Supporting Information, accepted to PLoS ON
A Fast Algorithm Finding the Shortest Reset Words
In this paper we present a new fast algorithm finding minimal reset words for
finite synchronizing automata. The problem is know to be computationally hard,
and our algorithm is exponential. Yet, it is faster than the algorithms used so
far and it works well in practice. The main idea is to use a bidirectional BFS
and radix (Patricia) tries to store and compare resulted subsets. We give both
theoretical and practical arguments showing that the branching factor is
reduced efficiently. As a practical test we perform an experimental study of
the length of the shortest reset word for random automata with states and 2
input letters. We follow Skvorsov and Tipikin, who have performed such a study
using a SAT solver and considering automata up to states. With our
algorithm we are able to consider much larger sample of automata with up to
states. In particular, we obtain a new more precise estimation of the
expected length of the shortest reset word .Comment: COCOON 2013. The final publication is available at
http://link.springer.com/chapter/10.1007%2F978-3-642-38768-5_1
Using a runway paradigm to assess the relative strength of rats' motivations for enrichment objects
Laboratory animals should be provided with enrichment objects in their cages; however, it is first necessary to
test whether the proposed enrichment objects provide benefits that increase the animals’ welfare. The two main
paradigms currently used to assess proposed enrichment objects are the choice test, which is limited to determining
relative frequency of choice, and consumer demand studies, which can indicate the strength of a preference but are complex to design. Here, we propose a third methodology: a runway paradigm, which can be used to assess the strength of an animal’s motivation for enrichment objects, is simpler to use than consumer demand studies, and is faster to complete than typical choice tests. Time spent with objects in a standard choice test was used to rank several enrichment objects in order to compare with the ranking found in our runway paradigm. The rats ran significantly more times, ran faster, and interacted longer with objects with which they had previously spent the most time. It was concluded that this simple methodology is suitable for measuring rats’ motivation to reach enrichment objects. This can be used to assess the preference for different types of enrichment objects or to measure reward system processes
Emotional persistence in online chatting communities
How do users behave in online chatrooms, where they instantaneously read and
write posts? We analyzed about 2.5 million posts covering various topics in
Internet relay channels, and found that user activity patterns follow known
power-law and stretched exponential distributions, indicating that online chat
activity is not different from other forms of communication. Analysing the
emotional expressions (positive, negative, neutral) of users, we revealed a
remarkable persistence both for individual users and channels. I.e. despite
their anonymity, users tend to follow social norms in repeated interactions in
online chats, which results in a specific emotional "tone" of the channels. We
provide an agent-based model of emotional interaction, which recovers
qualitatively both the activity patterns in chatrooms and the emotional
persistence of users and channels. While our assumptions about agent's
emotional expressions are rooted in psychology, the model allows to test
different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure
Positivity of the English language
Over the last million years, human language has emerged and evolved as a
fundamental instrument of social communication and semiotic representation.
People use language in part to convey emotional information, leading to the
central and contingent questions: (1) What is the emotional spectrum of natural
language? and (2) Are natural languages neutrally, positively, or negatively
biased? Here, we report that the human-perceived positivity of over 10,000 of
the most frequently used English words exhibits a clear positive bias. More
deeply, we characterize and quantify distributions of word positivity for four
large and distinct corpora, demonstrating that their form is broadly invariant
with respect to frequency of word use.Comment: Manuscript: 9 pages, 3 tables, 5 figures; Supplementary Information:
12 pages, 3 tables, 8 figure
Wetting films on chemically heterogeneous substrates
Based on a microscopic density functional theory we investigate the
morphology of thin liquidlike wetting films adsorbed on substrates endowed with
well-defined chemical heterogeneities. As paradigmatic cases we focus on a
single chemical step and on a single stripe. In view of applications in
microfluidics the accuracy of guiding liquids by chemical microchannels is
discussed. Finally we give a general prescription of how to investigate
theoretically the wetting properties of substrates with arbitrary chemical
structures.Comment: 56 pages, RevTeX, 20 Figure
What Goes Around Comes Around: Learning Sentiments in Online Medical Forums
Currently 19%-28% of Internet users participate in online health discussions. A 2011 survey of the US population estimated that 59% of all adults have looked online for information about health topics such as a specific disease or treatment. Although empirical evidence strongly supports the importance of emotions in health-related messages, there are few studies of the relationship between a subjective lan-guage and online discussions of personal health. In this work, we study sentiments expressed on online medical forums. As well as considering the predominant sentiments expressed in individual posts, we analyze sequences of sentiments in online discussions. Individual posts are classified into one of five categories. We identified three categories as sentimental (encouragement, gratitude, confusion) and two categories as neutral (facts, endorsement). 1438 messages from 130 threads were annotated manually by two annotators with a strong inter-annotator agreement (Fleiss kappa = 0.737 and 0.763 for posts in se-quence and separate posts respectively). The annotated posts were used to analyse sentiments in consec-utive posts. In four multi-class classification problems, we assessed HealthAffect, a domain-specific af-fective lexicon, as well general sentiment lexicons in their ability to represent messages in sentiment recognition
First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data
Spinning neutron stars asymmetric with respect to their rotation axis are potential sources of
continuous gravitational waves for ground-based interferometric detectors. In the case of known pulsars a
fully coherent search, based on matched filtering, which uses the position and rotational parameters
obtained from electromagnetic observations, can be carried out. Matched filtering maximizes the signalto-
noise (SNR) ratio, but a large sensitivity loss is expected in case of even a very small mismatch
between the assumed and the true signal parameters. For this reason, narrow-band analysis methods have
been developed, allowing a fully coherent search for gravitational waves from known pulsars over a
fraction of a hertz and several spin-down values. In this paper we describe a narrow-band search of
11 pulsars using data from Advanced LIGO’s first observing run. Although we have found several initial
outliers, further studies show no significant evidence for the presence of a gravitational wave signal.
Finally, we have placed upper limits on the signal strain amplitude lower than the spin-down limit for 5 of
the 11 targets over the bands searched; in the case of J1813-1749 the spin-down limit has been beaten for
the first time. For an additional 3 targets, the median upper limit across the search bands is below the
spin-down limit. This is the most sensitive narrow-band search for continuous gravitational waves carried
out so far
Relation of exaggerated cytokine responses of CF airway epithelial cells to PAO1 adherence
In many model systems, cystic fibrosis (CF) phenotype airway epithelial cells in culture respond to P. aeruginosa with greater interleukin (IL)-8 and IL-6 secretion than matched controls. In order to test whether this excess inflammatory response results from the reported increased adherence of P. aeruginosa to the CF cells, we compared the inflammatory response of matched pairs of CF and non CF airway epithelial cell lines to the binding of GFP-PAO1, a strain of pseudomonas labeled with green fluorescent protein. There was no clear relation between GFP-PAO1 binding and cytokine production in response to PAO1. Treatment with exogenous aGM1 resulted in greater GFP-PAO1 binding to the normal phenotype compared to CF phenotype cells, but cytokine production remained greater from the CF cell lines. When cells were treated with neuraminidase, PAO1 adherence was equalized between CF and nonCF phenotype cell lines, but IL-8 production in response to inflammatory stimuli was still greater in CF phenotype cells. The polarized cell lines 16HBEo-Sense (normal phenotype) and Antisense (CF phenotype) cells were used to test the effect of disrupting tight junctions, which allows access of PAO1 to basolateral binding sites in both cell lines. IL-8 production increased from CF, but not normal, cells. These data indicate that increased bacterial binding to CF phenotype cells cannot by itself account for excess cytokine production in CF airway epithelial cells, encourage investigation of alternative hypotheses, and signal caution for therapeutic strategies proposed for CF that include disruption of tight junctions in the face of pseudomonas infection
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