60,670 research outputs found
Automatic offensive language detection from Twitter data using machine learning and feature selection of metadata
The popularity of social networks has only increased
in recent years. In theory, the use of social media was proposed
so we could share our views online, keep in contact with loved
ones or share good moments of life. However, the reality is
not so perfect, so you have people sharing hate speech-related
messages, or using it to bully specific individuals, for instance,
or even creating robots where their only goal is to target specific
situations or people. Identifying who wrote such text is not easy
and there are several possible ways of doing it, such as using
natural language processing or machine learning algorithms
that can investigate and perform predictions using the metadata associated with it. In this work, we present an initial
investigation of which are the best machine learning techniques
to detect offensive language in tweets. After an analysis of the
current trend in the literature about the recent text classification
techniques, we have selected Linear SVM and Naive Bayes
algorithms for our initial tests. For the preprocessing of data,
we have used different techniques for attribute selection that
will be justified in the literature section. After our experiments,
we have obtained 92% of accuracy and 95% of recall to detect
offensive language with Naive Bayes and 90% of accuracy and
92% of recall with Linear SVM. From our understanding, these
results overcome our related literature and are a good indicative
of the importance of the data description approach we have used
Asymmetrical bloch branes and the hierarchy problem
We investigate a two scalar fields split braneworld model which leads to a
possible approach to the hierarchy problem within the thick brane scenario. The
model exhibits a resulting asymmetric warp factor suitable for this purpose.
The solution is obtained by means of the orbit equation approach for a specific
value of one of the parameters. Besides, we analyze the model qualitative
behaviour for arbitrary parameters by inspecting the underlying dynamical
system defined by the equations which give rise to the braneworld model. We
finalize commenting on the metric fluctuation and stability issues.Comment: 8 pages, 7 figure
Information-Entropic for Travelling Solitons in Lorentz and CPT Breaking Systems
In this work we group three research topics apparently disconnected, namely
solitons, Lorentz symmetry breaking and entropy. Following a recent work [Phys.
Lett. B 713 (2012) 304], we show that it is possible to construct in the
context of travelling wave solutions a configurational entropy measure in
functional space, from the field configurations. Thus, we investigate the
existence and properties of travelling solitons in Lorentz and CPT breaking
scenarios for a class of models with two interacting scalar fields. Here, we
obtain a complete set of exact solutions for the model studied which display
both double and single-kink configurations. In fact, such models are very
important in applications that include Bloch branes, Skyrmions, Yang-Mills,
Q-balls, oscillons and various superstring-motivated theories. We find that the
so-called Configurational Entropy (CE) for travelling solitons, which we name
as travelling Configurational Entropy (TCE), shows that the best value of
parameter responsible to break the Lorentz symmetry is one where the energy
density is distributed equally around the origin. In this way, the
information-theoretical measure of travelling solitons in Lorentz symmetry
violation scenarios opens a new window to probe situations where the parameters
responsible for breaking the symmetries are random. In this case, the TCE
selects the best value
New Algorithms for Computing a Single Component of the Discrete Fourier Transform
This paper introduces the theory and hardware implementation of two new
algorithms for computing a single component of the discrete Fourier transform.
In terms of multiplicative complexity, both algorithms are more efficient, in
general, than the well known Goertzel Algorithm.Comment: 4 pages, 3 figures, 1 table. In: 10th International Symposium on
Communication Theory and Applications, Ambleside, U
D-Oscillons in the Standard Model-Extension
In this work we investigate the consequences of the Lorentz symmetry
violation on extremely long-living, time-dependent, and spatially localized
field configurations, named oscillons. This is accomplished in ()
dimensions for two interacting scalar field theories in the so-called Standard
Model-Extension context. We show that -dimensional scalar field lumps can
present a typical size , where is the associated
length scale of extra dimensions in Kaluza-Klein theories. Here, the size
is shown to strongly depend on the terms that control the Lorentz
violation of the theory. This implies either contraction or dilation of the
average radius , and a new rule for its composition, likewise.
Moreover, we show that the spatial dimensions for existence of oscillating
lumps have an upper limit, opening new possibilities to probe the existence of
a -dimensional oscillons at TeV energy scale. Moreover, in a cosmological
scenario with Lorentz symmetry breaking, we argue that in the early Universe
with an extremely high energy density and a strong Lorentz violation, the
typical size was highly dilated. With the expansion and subsequent
cooling of the Universe, we propose that it passed through a phase transition
towards a Lorentz symmetry, wherein tends to be compact.Comment: 8 pages, final version to appear in PR
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