Tactics and Tallies: A Study of the 2016 U.S. Presidential Campaign Using Twitter 'Likes'

We propose a framework to measure, evaluate, and rank campaign effectiveness in the ongoing 2016 U.S. presidential election. Using Twitter data collected from Sept. 2015 to Jan. 2016, we first uncover the tweeting tactics of the candidates and second, using negative binomial regression and exploiting the variations in 'likes,' we evaluate the effectiveness of these tactics. Thirdly, we rank the candidates' campaign tactics by calculating the conditional expectation of their generated 'likes.' We show that while Ted Cruz and Marco Rubio put much weight on President Obama, this tactic is not being well received by their supporters. We demonstrate that Hillary Clinton's tactic of linking herself to President Obama resonates well with her supporters but the same is not true for Bernie Sanders. In addition, we show that Donald Trump is a major topic for all the other candidates and that the women issue is equally emphasized in Sanders' campaign as in Clinton's. Finally, we suggest two ways that politicians can use the feedback mechanism in social media to improve their campaign: (1) use feedback from social media to improve campaign tactics within social media; (2) prototype policies and test the public response from the social media.Comment: ICWSM 2017 - News and Public Opinion Worksho

Translating a Chinese Bestseller into English under the guidance of Skopos theory

China is getting more and more attention from the world due to its recent rapid development. However, for most people in the West, China is still something of a mystery. In order to enable English readers to know more about the modern society of China from an authentic perspective, the work 看见Kanjian (What Was Seen) has been chosen to be translated partially into English. It is the Chinese bestseller from 2013, a memoir written by the famous Chinese TV interviewer, Chai Jing, which has sold more than three million copies in China. The topics it deals with are real stories from the interviews she conducted, not just major events that have occurred in China, but also events from the lives of ordinary people. Many difficulties were encountered in the process of the translation, such as textual cohesion and coherence, sentence structure and vocabulary, as well as major cultural issues. How are these problems actually resolved? What translation strategies should be used to realise the translator’s translation objective? The Skopos theory will act as the main guide in this case study and the author will give a detailed analysis of translation examples using the Skopos theory.Apesar de a China estar a receber cada vez mais atenção do mundo devido ao seu rápido desenvolvimento recente, continua a representar um mistério para a maioria das pessoas no Ocidente. De modo a permitir que um público maior saiba mais sobre a sociedade moderna da China de uma perspetiva autêntica, o livro 看见Kanjian (O Que Foi Visto) foi escolhido para ser traduzido parcialmete para o inglês. Kanjian é um livro de memórias escrito pela conhecida repórter chinesa Chai Jing. Foi o livro mais vendido na China em 2013, com mais de três milhões de cópias vendidas. Os tópicos com os quais lida são histórias reais de entrevistas feitas pela repórter - não só grandes eventos que ocorreram na China, como também eventos das vidas de pessoas comuns. Foram encontradas várias dificuldades no processo de tradução: a coesão e a coerência textual, a estrutura das frases e o vocabulário e também questões culturais. Como se resolvem estes problemas? Que estratégias deve o tradutor utilizar para atingir o objetivo da tradução? A Teoria de Skopos funcionará como o principal guia neste estudo de caso e o autor fará uma análise detalhada dos exemplos de tradução usando esta teoria

Recovery rate, debt structure and valuation within U.S. bankruptcy law

The U.S. Bankruptcy Code is a frequently used channel to resolve corporate financial distress. In the code, liquidation (Chapter 7) and reorganization (Chapter 11) are two most crucial processes. My PhD thesis discusses several important issues around the U.S. Bankruptcy Code, including recovery rate determination in bankruptcy, debt valuation in bankruptcy under a two-class debt structure and determination of an optimal bankruptcy threshold. With the aim of linking corporate finance and asset pricing, new models of credit risk are developed in this thesis and fruitful empirical implications are generated. Specifically, the first main chapter is “Default and Recovery Rate under Chapter 11 with Multiple Debts”. This studies both theoretically and empirically the influence of debt structure on the outcome of debt renegotiation under Chapter 11. I investigate the trilateral negotiation in court-supervised formal bankruptcy. The model demonstrates how loans and bonds differ in terms of concentration level of debt owner and how this disparity impacts the action of the debtor company both before and after bankruptcy. The model developed in this chapter predicts that creditors’ ultimate recovery is higher for firms with more bank debt and less bargaining frictions and, despite the bank’s involvement improving total recovery, bondholders are still disadvantaged by the presence of senior bank creditors. Using a sample of 439 U.S. firms that filed for Chapter 11 during 1987-2014, I present evidence on the link between bank debt share and recovery rates that is supportive of the model’s prediction. The second main chapter is “Debt Structure and Valuation in U.S. Bankruptcy Code”. In this chapter I discuss the impact of bankruptcy procedure on security valuation by developing a credit risk model. As in the first chapter, the debt structure is in the form of two-class debt. A structural model of credit risk is built where default and liquidation are represented by two boundaries and a grace period is granted prior to liquidation. Within the setup, corporate debt is viewed as quasi Parisian corridor option and valuations are obtained via a partial differential equation formulation solved using a finite difference approach. The model can generate a credit spread for corporate debt which is more quantitatively consistent with the market credit spread. In this chapter I also show how the debt valuation is affected by several bankruptcy-related factors such as length of grace period. The last chapter, “Boundary Determination and Optimal Control Right Allocation in Financially Distressed Firms”, analyzes the determination of optimal default and liquidation boundaries in bankrupt entities. Compared with the previous chapter, this chapter reexamines the issue of debt valuation but allows the liquidation and renegotiation boundaries to be determined endogenously by valuing the maximization decision of involved parties. The model results show that different claim holders choose different default and liquidation boundaries to maximize the value of securities they hold, which leads to conflicts of interest between borrowers and lenders and also between different borrowers. The first-best outcome can be achieved if bondholders determine the liquidation boundary. Finally, the model shows that the optimal length of grace period, in the sense of firm value maximization, is roughly 6 months

Multiobjective Reliable Cloud Storage with Its Particle Swarm Optimization Algorithm

Information abounds in all fields of the real life, which is often recorded as digital data in computer systems and treated as a kind of increasingly important resource. Its increasing volume growth causes great difficulties in both storage and analysis. The massive data storage in cloud environments has significant impacts on the quality of service (QoS) of the systems, which is becoming an increasingly challenging problem. In this paper, we propose a multiobjective optimization model for the reliable data storage in clouds through considering both cost and reliability of the storage service simultaneously. In the proposed model, the total cost is analyzed to be composed of storage space occupation cost, data migration cost, and communication cost. According to the analysis of the storage process, the transmission reliability, equipment stability, and software reliability are taken into account in the storage reliability evaluation. To solve the proposed multiobjective model, a Constrained Multiobjective Particle Swarm Optimization (CMPSO) algorithm is designed. At last, experiments are designed to validate the proposed model and its solution PSO algorithm. In the experiments, the proposed model is tested in cooperation with 3 storage strategies. Experimental results show that the proposed model is positive and effective. The experimental results also demonstrate that the proposed model can perform much better in alliance with proper file splitting methods