New topic detection in microblogs and topic model evaluation using topical alignment

textThis thesis deals with topic model evaluation and new topic detection in microblogs. Microblogs are short and thus may not carry any contextual clues. Hence it becomes challenging to apply traditional natural language processing algorithms on such data. Graphical models have been traditionally used for topic discovery and text clustering on sets of text-based documents. Their unsupervised nature allows topic models to be trained easily on datasets meant for specific domains. However the advantage of not requiring annotated data comes with a drawback with respect to evaluation difficulties. The problem aggravates when the data comprises microblogs which are unstructured and noisy. We demonstrate the application of three types of such models to microblogs - the Latent Dirichlet Allocation, the Author-Topic and the Author-Recipient-Topic model. We extensively evaluate these models under different settings, and our results show that the Author-Recipient-Topic model extracts the most coherent topics. We also addressed the problem of topic modeling on short text by using clustering techniques. This technique helps in boosting the performance of our models. Topical alignment is used for large scale assessment of topical relevance by comparing topics to manually generated domain specific concepts. In this thesis we use this idea to evaluate topic models by measuring misalignments between topics. Our study on comparing topic models reveals interesting traits about Twitter messages, users and their interactions and establishes that joint modeling on author-recipient pairs and on the content of tweet leads to qualitatively better topic discovery. This thesis gives a new direction to the well known problem of topic discovery in microblogs. Trend prediction or topic discovery for microblogs is an extensive research area. We propose the idea of using topical alignment to detect new topics by comparing topics from the current week to those of the previous week. We measure correspondence between a set of topics from the current week and a set of topics from the previous week to quantify five types of misalignments: \textit{junk, fused, missing} and \textit{repeated}. Our analysis compares three types of topic models under different settings and demonstrates how our framework can detect new topics from topical misalignments. In particular so-called \textit{junk} topics are more likely to be new topics and the \textit{missing} topics are likely to have died or die out. To get more insights into the nature of microblogs we apply topical alignment to hashtags. Comparing topics to hashtags enables us to make interesting inferences about Twitter messages and their content. Our study revealed that although a very small proportion of Twitter messages explicitly contain hashtags, the proportion of tweets that discuss topics related to hashtags is much higher.Computer Science

Propagation of ultrastrong femtosecond laser pulses in PLASMON-X

The derivation is presented of the nonlinear equations that describe the propagation of ultrashort laser pulses in a plasma, in the Plasmon-X device. It is shown that the Plasmon-X scheme used for the electron acceleration uses a sufficiently broad beam ($L_\bot\sim 130\,\,\mu{\rm m}$) that justifies the use of the standard stationary 1-D approximation in the electron hydrodynamic equations, since the pulse width is sufficiently bigger than the pulse length ($\sim 7.5\,\,\mu{\rm m}$). Furthermore, with the laser power of $W\leq 250$ TW and the $130\,\,\mu{\rm m}$ spot size, the dimensionless laser vector potential is sufficiently small $|A_{\bot_0}|^2/{2} = ({W}/{c^2\epsilon_0})({\lambda^2}/{8 \pi^2 c})({4}/{\pi L_\bot^2})({e}/{m_0 c})^2 \sim 0.26$, the nonlinearity is sufficiently weak to allow the power expansion in the nonlinear Poissons's equation. Such approximation yields a nonlinear Schr\" odinger equation with a reactive nonlocal nonlinear term. The nonlocality contains a cosine function under the integral, indicating the oscillating wake. For a smaller spot size that is used for the Thomson scattering, $L_\bot = 10\,\, \mu$m, the length and the width of the pulse are comparable, and it is not possible to use the 1-D approximation in the hydrodynamic equations. With such small spot size, the laser intensity is very large, and most likely some sort of chanelling in the plasma would take place (the plasma gets locally depleted so much that the electromagnetic wave practically propagates in vacuum).Comment: Oral contribution O3.205 delivered at the 38th EPS Conference on Plasma Physics, Strasbourg, France, 26 June - 1 July, 201

Guide for third and fourth year students

Advice complied by Boston University School of Medicine students for incoming first year students and third or fourth year students preparing for clinical rotations

Self consistent thermal wave model description of the transverse dynamics for relativistic charged particle beams in magnetoactive plasmas

Thermal Wave Model is used to study the strong self-consistent Plasma Wake Field interaction (transverse effects) between a strongly magnetized plasma and a relativistic electron/positron beam travelling along the external magnetic field, in the long beam limit, in terms of a nonlocal NLS equation and the virial equation. In the linear regime, vortices predicted in terms of Laguerre-Gauss beams characterized by non-zero orbital angular momentum (vortex charge). In the nonlinear regime, criteria for collapse and stable oscillations is established and the thin plasma lens mechanism is investigated, for beam size much greater than the plasma wavelength. The beam squeezing and the self-pinching equilibrium is predicted, for beam size much smaller than the plasma wavelength, taking the aberrationless solution of the nonlocal Nonlinear Schroeding equation.Comment: Poster presentation P5.006 at the 38th EPS Conference on Plasma Physics, Strasbourg, France, 26 June - 1 July, 201