VerbNet based Citation Sentiment Class Assignment using Machine Learning

VerbNet Class Assignment as a WSD Task

Financial Sentiment Analysis Using Machine Learning Techniques

The rise of web content has presented a great opportunity to extract indicators of investor moods directly from news and social media. Gauging this sentiment or general prevailing attitude of investors may simplify the analysis of large, unstructured textual datasets and help anticipate price developments in the market. There are several challenges in developing a scalable and effective framewo...

Georeferencing Semi-Structured Place-Based Web Resources Using Machine Learning

In recent years, the shared content on the web has had significant growth. A great part of these information are publicly available in the form of semi-strunctured data. Moreover, a significant amount of these information are related to place. Such types of information refer to a location on the earth, however, they do not contain any explicit coordinates. In this research, we tried to georefer...

Sentiment Analysis in the Arabic Language Using Machine Learning

Sentiment Analysis in the Arabic Language Using Machine Learning Sentiment analysis has recently become one of the growing areas of research related to natural language processing and machine learning. Much opinion and sentiment about specific topics are available online, which allows several parties such as customers, companies and even governments, to explore these opinions. The first task is...

P ) Thumbs up ? Sentiment Classification using Machine Learning Techniques

We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three machine learning methods we employed (Naive Bayes, maximum entropy classification, and support vecto...