New markov chain based methods for single and cross-domain sentiment classification

Nowadays communication is switching from a centralized scenario, where communication media like newspapers, radio, TV programs produce information and people are just consumers, to a completely different decentralized scenario, where everyone is potentially an information producer through the use of social networks, blogs, forums that allow a real-time worldwide information exchange. These new instruments, as a result of their widespread diffusion, have started playing an important socio-economic role. They are the most used communication media and, as a consequence, they constitute the main source of information enterprises, political parties and other organizations can rely on. Analyzing data stored in servers all over the world is feasible by means of Text Mining techniques like Sentiment Analysis, which aims to extract opinions from huge amount of unstructured texts. This could lead to determine, for instance, the user satisfaction degree about products, services, politicians and so on. In this context, this dissertation presents new Document Sentiment Classification methods based on the mathematical theory of Markov Chains. All these approaches bank on a Markov Chain based model, which is language independent and whose killing features are simplicity and generality, which make it interesting with respect to previous sophisticated techniques. Every discussed technique has been tested in both Single-Domain and Cross-Domain Sentiment Classification areas, comparing performance with those of other two previous works. The performed analysis shows that some of the examined algorithms produce results comparable with the best methods in literature, with reference to both single-domain and cross-domain tasks, in $2$-classes (i.e. positive and negative) Document Sentiment Classification. However, there is still room for improvement, because this work also shows the way to walk in order to enhance performance, that is, a good novel feature selection process would be enough to outperform the state of the art. Furthermore, since some of the proposed approaches show promising results in $2$-classes Single-Domain Sentiment Classification, another future work will regard validating these results also in tasks with more than $2$ classes.

La comunicazione aziendale tra redazione e traduzione: Il caso di ipack srl.

This dissertation is the result of my participation in the Language Toolkit project, a recent collaboration between the Chamber of Commerce of Forlì and the School of Foreign Languages and Literatures, Interpreting and Translation at the University of Bologna, which aims to make students meet with the companies of our territory, in this case Ipack, based in Mercato Saraceno (FC). My dissertation is a specialized translation work from Italian into English of two documents that were entrusted to me: the declaration of compliance of Ipack’s products and a summary of the quality manual. They are two high technical texts and, therefore, the translation task required a preliminary phase of research on the topics and on the terminology of this specific domain. The dissertation consists of five chapters. The first chapter briefly introduces the company with which I collaborated for my dissertation project and provides an overview of business communication and a brief classification of Ipack’s communication tools. The second chapter covers the background topics, namely food packaging and quality management systems within companies. The third chapter concerns the analysis of the two texts, describing the intra-textual and extra-textual aspects, as well as the morphosyntaxical and lexical features. The fourth chapter is dedicated to the revision work on one of the two texts, the one about quality procedures. In the commentary following my review, I explain the methodology and the strategies that I used and I also provide some extended examples of the main changes applied to the original text, with respect to both content and linguistic features. Finally, the fifth chapter focuses on the translation of the texts followed by a commentary that explains the work methodology, resources and my translation choices, accompanied by practical examples.