In this paper, we introduce a novel approach to sentiment polarity classification of citations, which integrates data about the authors’ reputation. More specifically, our method extends the h-index with citation polarities and utilizes it in sentiment classification of citation sentences. Our computational results show that our method yields significant improvement in terms of classification p...

Recent advancements in machine translation foster an interest of its use in sentiment analysis. This thesis investigates prospects and limitations of using machine translation in cross-lingual sentiment analysis. To perform a sentiment analysis we need to learn linguistic features by either using tools such as part-of-speech taggers, parsers, or basic resources such as annotated corpora or sent...

Today microblogging has increasingly become a means of information diffusion via user's retweeting behavior. Since retweeting content, as context information of microblogging, is an understanding of microblogging, hence, user's retweeting sentiment tendency analysis has gradually become a hot research topic. Targeted at online microblogging, a dynamic social network, we investigate how to explo...

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. Ideally, an opinion mining tool would process a set of search results for a given item, generating a list of product attributes (quality, features, etc.) and aggregating opinions about each of them (poor, mixed, good). Then begin by ident...

In the recent decade, with the enormous growth of digital content in internet and databases, sentiment analysis has received more and more attention between information retrieval and natural language processing researchers. Sentiment analysis aims to use automated tools to detect subjective information from reviews. One of the main challenges in sentiment analysis is feature selection. Feature ...

Abstract Nowadays, it is important for buyers to know other customer opinions make informed decisions on buying a product or service. In addition, companies and organizations can exploit improve their products services. However, the Quintilian bytes of generated every day cannot be manually read summarized. Sentiment analysis opinion mining techniques offer solution automatically classify summa...

Automated identification of diverse sentiment types can be beneficial for many NLP systems such as review summarization and public media analysis. In some of these systems there is an option of assigning a sentiment value to a single sentence or a very short text. In this paper we propose a supervised sentiment classification framework which is based on data from Twitter, a popular microbloggin...

This paper describes our approach for SemEval-2017 Task 4 Sentiment Analysis in Twitter (SAT). Its five subtasks are divided into two categories: (1) sentiment classification, i.e., predicting topic-based tweet sentiment polarity, and (2) sentiment quantification, that is, estimating the sentiment distributions of a set of given tweets. We build a convolutional sentence classification system fo...

Sentiment Analysis is a Natural Language Processing-task that is relevant in a number of contexts, including the analysis of literature. We report on ongoing research towards enabling, for the first time, sentencelevel Sentiment Analysis in the domain of German novels. We create a labelled dataset from sentences extracted from German novels and, by adapting existing sentiment classifiers, reach...

This paper explains a study on the different sentiment analysis techniques with the process of annotation and tagging. It explains several research methods, newer techniques and concepts in sentiment analysis as well as classification. This also introduces the concept of Text-to-speech conversion expressively. This study is expected to improve the different methodologies in sentiment analysis a...