CPH: Sentiment analysis of Figurative Language on Twitter #easypeasy #not
نویسندگان
چکیده
This paper describes the details of our system submitted to the SemEval 2015 shared task on sentiment analysis of figurative language on Twitter. We tackle the problem as regression task and combine several base systems using stacked generalization (Wolpert, 1992). An initial analysis revealed that the data is heavily biased, and a general sentiment analysis system (GSA) performs poorly on it. However, GSA proved helpful on the test data, which contains an estimated 25% nonfigurative tweets. Our best system, a stacking system with backoff to GSA, ranked 4th on the final test data (Cosine 0.661, MSE 3.404).1
منابع مشابه
SemEval-2015 Task 11: Sentiment Analysis of Figurative Language in Twitter
This report summarizes the objectives and evaluation of the SemEval 2015 task on the sentiment analysis of figurative language on Twitter (Task 11). This is the first sentiment analysis task wholly dedicated to analyzing figurative language on Twitter. Specifically, three broad classes of figurative language are considered: irony, sarcasm and metaphor. Gold standard sets of 8000 training tweets...
متن کاملDsUniPi: An SVM-based Approach for Sentiment Analysis of Figurative Language on Twitter
The DsUniPi team participated in the SemEval 2015 Task#11: Sentiment Analysis of Figurative Language in Twitter. The proposed approach employs syntactical and morphological features, which indicate sentiment polarity in both figurative and non-figurative tweets. These features were combined with others that indicate presence of figurative language in order to predict a fine-grained sentiment sc...
متن کاملUPF-taln: SemEval 2015 Tasks 10 and 11. Sentiment Analysis of Literal and Figurative Language in Twitter
In this paper, we describe the approach used by the UPF-taln team for tasks 10 and 11 of SemEval 2015 that respectively focused on “Sentiment Analysis in Twitter” and “Sentiment Analysis of Figurative Language in Twitter”. Our approach achieved satisfactory results in the figurative language analysis task, obtaining the second best result. In task 10, our approach obtained acceptable performanc...
متن کاملValenTo: Sentiment Analysis of Figurative Language Tweets with Irony and Sarcasm
This paper describes the system used by the ValenTo team in the Task 11, Sentiment Analysis of Figurative Language in Twitter, at SemEval 2015. Our system used a regression model and additional external resources to assign polarity values. A distinctive feature of our approach is that we used not only wordsentiment lexicons providing polarity annotations, but also novel resources for dealing wi...
متن کاملSentiment analysis methods in Sentiment analysis methods in Persian text: A survey
With the explosive growth of social media such as Twitter, reviews on e-commerce website, and comments on news websites, individuals and organizations are increasingly using opinions in these media for their decision making. Sentiment analysis is one of the techniques used to analyze userschr('39') opinions in recent years. Persian language has specific features and thereby requires unique meth...
متن کامل