Word Affect Intensities

Words often convey affect -- emotions, feelings, and attitudes. Lexicons of word-affect association have applications in automatic emotion analysis and natural language generation. However, existing lexicons indicate only coarse categories of affect association. Here, for the first time, we create an affect intensity lexicon with real-valued scores of association. We use a technique called best-worst scaling that improves annotation consistency and obtains reliable fine-grained scores. The lexicon includes terms common from both general English and terms specific to social media communications. It has close to 6,000 entries for four basic emotions. We will be adding entries for other affect dimensions shortly

Criticality in Third Order Lovelock Gravity and the Butterfly effect

We study third order Lovelock Gravity in $D=7$ at the critical point which three (A)dS vacua degenerate into one. We see there is not propagating graviton at the critical point. And also we compute the butterfly velocity for this theory at the critical point by considering the shock wave solutions near horizon, this is important to note that although there is no propagating graviton at the critical point, due to boundary gravitons the butterfly velocity is non-zero. Finally we observe that the butterfly velocity for third order Lovelock Gravity at the critical point in $D=7$ is less than the butterfly velocity for Einstein-Gauss-Bonnet Gravity at the critical point in $D=7$ which is less than the butterfly velocity in D = 7 for Einstein Gravity, $v_{B}^{E.H}>v_{B}^{E.G.B}>v_{B}^{3rd\,\,Lovelock}$. Maybe we can conclude that by adding higher order curvature corrections to Einstein Gravity the butterfly velocity decreases.Comment: 10 pages, No figure, Minor correction

Universality of the Acceleration Due to Gravity on the Surface of a Rapidly Rotating Neutron Star

On the surface of a rapidly rotating neutron star, the effective centrifugal force decreases the effective acceleration due to gravity (as measured in the rotating frame) at the equator while increasing the acceleration at the poles due to the centrifugal flattening of the star into an oblate spheroid. We compute the effective gravitational acceleration for relativistic rapidly rotating neutron stars and show that for a star with mass $M$, equatorial radius $R_e$, and angular velocity $\Omega$, the deviations of the effective acceleration due to gravity from the nonrotating case take on a universal form that depends only on the compactness ratio $M/R_e$, the dimensionless square of the angular velocity $\Omega^2R_e^3/GM$, and the latitude on the star's surface. This dependence is universal, in that it has very little dependence on the neutron star's equation of state. The effective gravity is expanded in the slow rotation limit to show the dependence on the effective centrifugal force, oblate shape of the star and the quadrupole moment of the gravitational field. In addition, an empirical fit and simple formula for the effective gravity is found. We find that the increase in the acceleration due to gravity at the poles is of the same order of magnitude as the decrease in the effective acceleration due to gravity at the equator for all realistic value of mass, radius and spin. For neutron stars that spin with frequencies near 600 Hz the difference between the effective gravity at the poles and the equator is about 20%.Comment: 13 pages, 3 figure

Recovery of binary sparse signals from compressed linear measurements via polynomial optimization

The recovery of signals with finite-valued components from few linear measurements is a problem with widespread applications and interesting mathematical characteristics. In the compressed sensing framework, tailored methods have been recently proposed to deal with the case of finite-valued sparse signals. In this work, we focus on binary sparse signals and we propose a novel formulation, based on polynomial optimization. This approach is analyzed and compared to the state-of-the-art binary compressed sensing methods

The Effect of Negators, Modals, and Degree Adverbs on Sentiment Composition

Negators, modals, and degree adverbs can significantly affect the sentiment of the words they modify. Often, their impact is modeled with simple heuristics; although, recent work has shown that such heuristics do not capture the true sentiment of multi-word phrases. We created a dataset of phrases that include various negators, modals, and degree adverbs, as well as their combinations. Both the phrases and their constituent content words were annotated with real-valued scores of sentiment association. Using phrasal terms in the created dataset, we analyze the impact of individual modifiers and the average effect of the groups of modifiers on overall sentiment. We find that the effect of modifiers varies substantially among the members of the same group. Furthermore, each individual modifier can affect sentiment words in different ways. Therefore, solutions based on statistical learning seem more promising than fixed hand-crafted rules on the task of automatic sentiment prediction.Comment: In Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA), San Diego, California, 201