137 research outputs found
Emotional agents at the square lattice
We introduce and investigate by numerical simulations a number of models of
emotional agents at the square lattice. Our models describe the most general
features of emotions such as the spontaneous emotional arousal, emotional
relaxation, and transfers of emotions between different agents. Group emotions
in the considered models are periodically fluctuating between two opposite
valency levels and as result the mean value of such group emotions is zero. The
oscillations amplitude depends strongly on probability ps of the individual
spontaneous arousal. For small values of relaxation times tau we observed a
stochastic resonance, i.e. the signal to noise ratio SNR is maximal for a
non-zero ps parameter. The amplitude increases with the probability p of local
affective interactions while the mean oscillations period increases with the
relaxation time tau and is only weakly dependent on other system parameters.
Presence of emotional antenna can enhance positive or negative emotions and for
the optimal transition probability the antenna can change agents emotions at
longer distances. The stochastic resonance was also observed for the influence
of emotions on task execution efficiency.Comment: 28 pages, 19 figures, 3 table
Coevolution of Information Processing and Topology in Hierarchical Adaptive Random Boolean Networks
Random Boolean networks (RBNs) are frequently employed for modelling complex
systems driven by information processing, e.g. for gene regulatory networks
(GRNs). Here we propose a hierarchical adaptive RBN (HARBN) as a system
consisting of distinct adaptive RBNs - subnetworks - connected by a set of
permanent interlinks. Information measures and internal subnetworks topology of
HARBN coevolve and reach steady-states that are specific for a given network
structure. We investigate mean node information, mean edge information as well
as a mean node degree as functions of model parameters and demonstrate HARBN's
ability to describe complex hierarchical systems.Comment: 9 pages, 6 figure
An Agent-Based Model of Collective Emotions in Online Communities
We develop a agent-based framework to model the emergence of collective
emotions, which is applied to online communities. Agents individual emotions
are described by their valence and arousal. Using the concept of Brownian
agents, these variables change according to a stochastic dynamics, which also
considers the feedback from online communication. Agents generate emotional
information, which is stored and distributed in a field modeling the online
medium. This field affects the emotional states of agents in a non-linear
manner. We derive conditions for the emergence of collective emotions,
observable in a bimodal valence distribution. Dependent on a saturated or a
superlinear feedback between the information field and the agent's arousal, we
further identify scenarios where collective emotions only appear once or in a
repeated manner. The analytical results are illustrated by agent-based computer
simulations. Our framework provides testable hypotheses about the emergence of
collective emotions, which can be verified by data from online communities.Comment: European Physical Journal B (in press), version 2 with extended
introduction, clarification
Negative emotions boost users activity at BBC Forum
We present an empirical study of user activity in online BBC discussion
forums, measured by the number of posts written by individual debaters and the
average sentiment of these posts. Nearly 2.5 million posts from over 18
thousand users were investigated. Scale free distributions were observed for
activity in individual discussion threads as well as for overall activity. The
number of unique users in a thread normalized by the thread length decays with
thread length, suggesting that thread life is sustained by mutual discussions
rather than by independent comments. Automatic sentiment analysis shows that
most posts contain negative emotions and the most active users in individual
threads express predominantly negative sentiments. It follows that the average
emotion of longer threads is more negative and that threads can be sustained by
negative comments. An agent based computer simulation model has been used to
reproduce several essential characteristics of the analyzed system. The model
stresses the role of discussions between users, especially emotionally laden
quarrels between supporters of opposite opinions, and represents many observed
statistics of the forum.Comment: 29 pages, 6 figure
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
Lead Speciation in the Dusts Emitted from Non-Ferrous Metallurgy Processes
The paper presents results for the speciation analysis of lead in dusts derived from dedusting of technological gasses from metallurgical processes of non-ferrous metals with different elementary content, made in accordance with two equal sequential extractions. Analytical procedure A provided possibilities for determination of fraction of Pb2+, metallic lead and fraction containing mainly lead sulfides. The second procedure (procedure B) was sequential extraction in accordance with Tessier. The results obtained in accordance with procedure A indicate that, regardless of the dust origin, the dominant group of Pb compounds is composed of lead salts which are soluble under alkaline conditions or lead compounds that form plumbites in the reaction with NaOH
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