Today’s massive news streams demand the automate analysis which is provided by various online news explorers. However, most of them do not provide sentiment analysis. The main problem of sentiment analysis of news is the differences between the writers and readers attitudes to the news text. News can be good or bad but have to be delivered in neutral words as pure facts. Although there are appl...

Most cross-lingual sentiment classification (CLSC) research so far has been performed at sentence or document level. Aspect-level CLSC, which is more appropriate for many applications, presents the additional difficulty that we consider subsentential opinionated units which have to be mapped across languages. In this paper, we extend the possible cross-lingual sentiment analysis settings to asp...

Whether or not U.S. women follow the recommended breast cancer screening guidelines is related to the perceived benefits and harms of the procedure. Twitter is a rich source of subjective information containing individuals’ sentiment towards public health interventions/technologies. Using a modified version of Hutto and Gilbert (2014) sentiment classifier, we described the temporal, geospatial,...

....................................................................................................................................... i Significance to defence and security ................................................................................................ i Résumé .......................................................................................................................

This note contains a short history of my work on the foundations of revealed preference, emphasizing the intellectual influence of Sydney Afriat. I also present a few “novel” applications of revealed preference analysis drawn from some areas of applied economics.

This study considers consumer online reviews for auto, home, and life insurance services to provide insights regarding understanding consumers’ attitude toward different insurance types. We apply the sentiment analysis technique to analyze the overall sentiment of each insurance type since 2012. Our findings show that since 2013 consumers had more negative attitudes toward insurance services. W...

We propose a statistical study of sentiment produced in an urban environment by collecting tweets submitted in a certain timeframe. Each tweet was processed using our own sentiment classifier and assigned either a positive or a negative label. By calculating the average mood, we were able to run a Mann-Withney’s U test to evaluate differences in the calculated mood per day of week. We found tha...

Existing sentiment classifiers usually work for only one specific language, and different classification models are used in different languages. In this paper we aim to build a universal sentiment classifier with a single classification model in multiple different languages. In order to achieve this goal, we propose to learn multilingual sentiment-aware word embeddings simultaneously based only...

English. Recent works on Sentiment Analysis over Twitter leverage the idea that the sentiment depends on a single incoming tweet. However, tweets are plunged into streams of posts, thus making available a wider context. The contribution of this information has been recently investigated for the English language by modeling the polarity detection as a sequential classification task over streams ...