What Theories of Political Participation Can Teach Us about the Blogosphere, and Vice Versa.

Few venues span the spectrum of political ideas better than the blogosphere, the sprawling online network of "web-logs"' and their authors. Roughly 1.3 million Americans blog at least occasionally about politics, with aggregate daily readership exceeding that of major newspapers, and daily aggregate word counts in the tens of millions. This incredibly diverse medium captures the daily thoughts of people from all walks of life, from Senators to army wives to community activists to business owners to conspiracy theorists, all lending their voices to a public forum that was almost unimaginable a generation ago. Previous research has focused primarily on how blogging is different, especially how blogging is different from traditional journalism. In contrast, I show how political blogging is strikingly similar--to political activism. The same social forces that lead people to vote, protest, or write letters to public officials can also lead them to blog about politics. Thus, bloggers are not journalists. They are activists, which means that classic theories of political participation can inform the study of blogging. This project explores these similarities, detailing the forces that drive participation in the political blogosphere, and revealing where the blogosphere represents--and distorts--the voice of the electorate. This research provides clues into behaviors that are hard to observe in other contexts, but matter deeply for society and for democracy. Conversely, data from the blogosphere can open new avenues of research into political participation. Unlike most forms of communication, blogging leaves a permanent data trail. Archives of thousands of political blogs exist online, complete with text, dates, links, and comments. This project taps this wealth of social data using a combination of techniques from social and computer science: survey research, content analysis, web crawling, and automated text classification. Using this interdisciplinary mix of tools, I survey hundreds of bloggers and analyze nearly eight million blog posts. In the process, I build methodological bridges between social and computer science, making software and data available for future research.PHDPublic Policy & Political ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102371/1/agong_1.pd

Networks and Language in the 2010 Election

The midterm (2010) election in the U.S. presented a unique opportunity to study the online social media strategy of various political groups. Although candidates had previously leveraged social media, the prevalence of use during this election allows us to study a significant percentage of candidates and a novel glimpse into their networks and messaging. In combination, the networks and associated content reflect positioning of candidates both structurally and in framing in relation to other politicians. In our work, we study the use of Twitter by House, Senate and gubernatorial candidates during the midterm elections in the U.S. Our data includes almost 700 candidates and over 460k tweets that they produced in the 3.5 years leading to the elections. We utilize graph and text mining techniques to analyze differences between Democrats, Republicans and Tea Party candidates, and suggest a novel use of language modeling for estimating content cohesiveness. Our findings show significant differences in the usage patterns of social media, and suggest conservative candidates used this medium more effectively, conveying a coherent message and maintaining a dense graph of connections. Despite the lack of party leadership, we find Tea Party members display both structural and language‐based cohesiveness. Finally, we investigate the relation between network structure, content and election results by creating a proof‐of‐concept model that extends incumbency models to predict candidate victory

Combined constraints on modified Chaplygin gas model from cosmological observed data: Markov Chain Monte Carlo approach

We use the Markov Chain Monte Carlo method to investigate a global constraints on the modified Chaplygin gas (MCG) model as the unification of dark matter and dark energy from the latest observational data: the Union2 dataset of type supernovae Ia (SNIa), the observational Hubble data (OHD), the cluster X-ray gas mass fraction, the baryon acoustic oscillation (BAO), and the cosmic microwave background (CMB) data. In a flat universe, the constraint results for MCG model are, $\Omega_{b}h^{2}=0.02263^{+0.00184}_{-0.00162}$ ($1\sigma$) $^{+0.00213}_{-0.00195}$ $(2\sigma)$, $B_{s}=0.7788^{+0.0736}_{-0.0723}$ ($1\sigma$) $^{+0.0918}_{-0.0904}$ $(2\sigma)$, $\alpha=0.1079^{+0.3397}_{-0.2539}$ ($1\sigma$) $^{+0.4678}_{-0.2911}$ $(2\sigma)$, $B=0.00189^{+0.00583}_{-0.00756}$ ($1\sigma$) $^{+0.00660}_{-0.00915}$ $(2\sigma)$, and $H_{0}=70.711^{+4.188}_{-3.142}$ ($1\sigma$) $^{+5.281}_{-4.149}$ $(2\sigma)$.Comment: 12 pages, 1figur

Constraints on accelerating universe using ESSENCE and Gold supernovae data combined with other cosmological probes

We use recently observed data: the 192 ESSENCE type Ia supernovae (SNe Ia), the 182 Gold SNe Ia, the 3-year WMAP, the SDSS baryon acoustic peak, the X-ray gas mass fraction in clusters and the observational $H(z)$ data to constrain models of the accelerating universe. Combining the 192 ESSENCE data with the observational $H(z)$ data to constrain a parameterized deceleration parameter, we obtain the best fit values of transition redshift and current deceleration parameter $z_{T}=0.632^{+0.256}_{-0.127}$, $q_{0}=-0.788^{+0.182}_{-0.182}$. Furthermore, using $\Lambda$CDM model and two model-independent equation of state of dark energy, we find that the combined constraint from the 192 ESSENCE data and other four cosmological observations gives smaller values of $\Omega_{0m}$ and $q_{0}$, but a larger value of $z_{T}$ than the combined constraint from the 182 Gold data with other four observations. Finally, according to the Akaike information criterion it is shown that the recently observed data equally supports three dark energy models: $\Lambda$CDM, $w_{de}(z)=w_{0}$ and $w_{de}(z)=w_{0}+w_{1}\ln(1+z)$.Comment: 18 pages, 8 figure

Surface Structure of Liquid Metals and the Effect of Capillary Waves: X-ray Studies on Liquid Indium

We report x-ray reflectivity (XR) and small angle off-specular diffuse scattering (DS) measurements from the surface of liquid Indium close to its melting point of $156^\circ$C. From the XR measurements we extract the surface structure factor convolved with fluctuations in the height of the liquid surface. We present a model to describe DS that takes into account the surface structure factor, thermally excited capillary waves and the experimental resolution. The experimentally determined DS follows this model with no adjustable parameters, allowing the surface structure factor to be deconvolved from the thermally excited height fluctuations. The resulting local electron density profile displays exponentially decaying surface induced layering similar to that previously reported for Ga and Hg. We compare the details of the local electron density profiles of liquid In, which is a nearly free electron metal, and liquid Ga, which is considerably more covalent and shows directional bonding in the melt. The oscillatory density profiles have comparable amplitudes in both metals, but surface layering decays over a length scale of $3.5\pm 0.6$ \AA for In and $5.5\pm 0.4$ \AA for Ga. Upon controlled exposure to oxygen, no oxide monolayer is formed on the liquid In surface, unlike the passivating film formed on liquid Gallium.Comment: 9 pages, 5 figures; submitted to Phys. Rev.

Does accelerating universe indicates Brans-Dicke theory

The evolution of universe in Brans-Dicke (BD) theory is discussed in this paper. Considering a parameterized scenario for BD scalar field $\phi=\phi_{0}a^{\alpha}$ which plays the role of gravitational "constant" $G$, we apply the Markov Chain Monte Carlo method to investigate a global constraints on BD theory with a self-interacting potential according to the current observational data: Union2 dataset of type supernovae Ia (SNIa), high-redshift Gamma-Ray Bursts (GRBs) data, observational Hubble data (OHD), the cluster X-ray gas mass fraction, the baryon acoustic oscillation (BAO), and the cosmic microwave background (CMB) data. It is shown that an expanded universe from deceleration to acceleration is given in this theory, and the constraint results of dimensionless matter density $\Omega_{0m}$ and parameter $\alpha$ are, $\Omega_{0m}=0.286^{+0.037+0.050}_{-0.039-0.047}$ and $\alpha=0.0046^{+0.0149+0.0171}_{-0.0171-0.0206}$ which is consistent with the result of current experiment exploration, $\mid\alpha\mid \leq 0.132124$. In addition, we use the geometrical diagnostic method, jerk parameter $j$, to distinguish the BD theory and cosmological constant model in Einstein's theory of general relativity.Comment: 16 pages, 3 figure

Constraints on the generalized tachyon field models from latest observational data

We consider constraints on generalized tachyon field (GTF) models from latest observational data (including 182 gold SNIa data, the shift parameter, and the acoustic scale). We obtain at 68.3% confidence level $\Omega_{\rm m}=0.37\pm0.01$, $k_0=0.09^{+0.04}_{-0.03}$, $\alpha=1.8^{+7.4}_{-0.7}$ (the best-fit values of the parameters) and $z_{q=0}\sim 0.47-0.51$ (the transitional redshift) for GTF as dark energy component only; $k_0=0.21^{+0.20}_{-0.18}$, $\alpha=0.57\pm0.01$ and $z_{q=0}\sim 0.49-0.68$ for GTF as unification of dark energy and dark matter. In both cases, GTF evolves like dark matter in the early universe. By applying model-comparison statistics and test with independent $H(z)$ data, we find GTF dark energy scenario is favored over the $\Lambda$CDM model, and the $\Lambda$CDM model is favored over GTF unified dark matter by the combined data. For GTF as dark energy component, the fluctuations of matter density is consistent with the growth of linear density perturbations. For GTF unified dark matter, the growth of GTF density fluctuations grow more slowly for $a\to1$, meaning GTF do not behave as classical $\Lambda$CDM scenarios.Comment: 21pages, 14 figure

Time separation as a hidden variable to the Copenhagen school of quantum mechanics

The Bohr radius is a space-like separation between the proton and electron in the hydrogen atom. According to the Copenhagen school of quantum mechanics, the proton is sitting in the absolute Lorentz frame. If this hydrogen atom is observed from a different Lorentz frame, there is a time-like separation linearly mixed with the Bohr radius. Indeed, the time-separation is one of the essential variables in high-energy hadronic physics where the hadron is a bound state of the quarks, while thoroughly hidden in the present form of quantum mechanics. It will be concluded that this variable is hidden in Feynman's rest of the universe. It is noted first that Feynman's Lorentz-invariant differential equation for the bound-state quarks has a set of solutions which describe all essential features of hadronic physics. These solutions explicitly depend on the time separation between the quarks. This set also forms the mathematical basis for two-mode squeezed states in quantum optics, where both photons are observable, but one of them can be treated a variable hidden in the rest of the universe. The physics of this two-mode state can then be translated into the time-separation variable in the quark model. As in the case of the un-observed photon, the hidden time-separation variable manifests itself as an increase in entropy and uncertainty.Comment: LaTex 10 pages with 5 figure. Invited paper presented at the Conference on Advances in Quantum Theory (Vaxjo, Sweden, June 2010), to be published in one of the AIP Conference Proceedings serie

A multi-targeted approach to suppress tumor-promoting inflammation

Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-κB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes