Public opinion analysis for micro-blog post is a new trend, and wherein emotional tendency analysis on micro-blog topic is a hot spot in the sentiment analysis. According to the characteristics of contents and the various relations of Chinese micro-blog post, we construct the dictionaries of sentiment words, internet slang and emoticons respectively, and then implement the sentiment analysis al...

Microblogging is a popular social media where people express their opinions and sentiment on social topics. The Chinese microblogging service, called Weibo, has become a remarkable media in the Chinese society. People are eager to know others’ attitudes towards social events, thus sentiment analysis on those topical microblog messages is important. In this paper we introduce a lexicon-based sen...

We present a sentiment classification system that participated in the SemEval 2014 shared task on sentiment analysis in Twitter. Our system expands tokens in a tweet with semantically similar expressions using a large novel distributional thesaurus and calculates the semantic relatedness of the expanded tweets to word lists representing positive and negative sentiment. This approach helps to as...

This paper describes our system submitted for the Sentiment Analysis in Twitter task of SemEval-2016, and specifically for the Message Polarity Classification subtask. We used a system that combines Convolutional Neural Networks and Logistic Regression for sentiment prediction, where the former makes use of embedding features while the later utilizes various features like lexicons and dictionar...

In this paper, we propose GermanPolarityClues, a new publicly available lexical resource for sentiment analysis for the German language. While sentiment analysis and polarity classification has been extensively studied at different document levels (e.g. sentences and phrases), only a few approaches explored the effect of a polarity-based feature selection and subjectivity resources for the Germ...

Are today’s neologisms indicating that we are all a bunch of pessimists? New words are produced at the rapid rate of about 15 per day and distributed online. Some words last only a week contained to a small circle of friends while others find a permanent residence in the dictionary. But, as with the words that came before them, they are subject to the force of language evolution. We track a set...

Sentiment Analysis deals with the analysis of emotions, opinions and facts in the sentences which are expressed by the people. It allows us to track attitudes and feelings of the people by analyzing blogs, comments, reviews and tweets about all the aspects. The development of Internet has strong influence in all types of industries like tourism, healthcare and any business. The availability of ...

The Stock Sonar (TSS) is a stock sentiment analysis application based on a novel hybrid approach. While previous work focused on document level sentiment classification, or extracted only generic sentiment at the phrase level, TSS integrates sentiment dictionaries, phrase-level compositional patterns, and predicate-level semantic events. TSS generates precise in-text sentiment tagging as well a...

The paper presents our work in the multilingual opinion analysis task in NTCIR7 in Simplified Chinese. In detecting opinionated sentences, an EM algorithm was proposed to extract the sentiment words based on the sentimental dictionary, and then an iterative algorithm was used to estimate the score of the sentiment words and the sentences. In detecting relevant sentences, we solve this problem b...

Sentiment analysis is the automatic classification of the overall opinion conveyed by a text towards its subject matter. This paper discusses an experiment in the sentiment analysis of of a collection of movie reviews that have been automatically translated to Indonesian. Following [1], we employ three well known classification techniques: naive bayes, maximum entropy, and support vector machin...