ECNU: Extracting Effective Features from Multiple Sequential Sentences for Target-dependent Sentiment Analysis in Reviews
نویسندگان
چکیده
This paper describes our systems submitted to the target-dependent sentiment polarity classification subtask in aspect based sentiment analysis (ABSA) task (i.e., Task 12) in SemEval 2015. To settle this problem, we extracted several effective features from three sequential sentences, including sentiment lexicon, linguistic and domain specific features. Then we employed these features to construct classifiers using supervised classification algorithm. In laptop domain, our systems ranked 2nd out of 6 constrained submissions and 2nd out of 7 unconstrained submissions. In restaurant domain, the rankings are 5th out of 6 and 2nd out of 8 respectively.
منابع مشابه
ECNU at SemEval-2016 Task 5: Extracting Effective Features from Relevant Fragments in Sentence for Aspect-Based Sentiment Analysis in Reviews
This paper describes our systems submitted to the Sentence-level and Text-level AspectBased Sentiment Analysis (ABSA) task (i.e., Task 5) in SemEval-2016. The task involves two phases, namely, Aspect Detection phase and Sentiment Polarity Classification phase. We participated in the second phase of both subtasks in laptop and restaurant domains, which focuses on the sentiment analysis based on ...
متن کاملA Supervised Method for Constructing Sentiment Lexicon in Persian Language
Due to the increasing growth of digital content on the internet and social media, sentiment analysis problem is one of the emerging fields. This problem deals with information extraction and knowledge discovery from textual data using natural language processing has attracted the attention of many researchers. Construction of sentiment lexicon as a valuable language resource is a one of the imp...
متن کاملThe CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis
Hitherto, sentiment analysis has been mainly based on algorithms relying on the textual representation of online reviews and microblogging posts. Such algorithms are very good at retrieving texts, splitting them into parts, checking the spelling, and counting their words. But when it comes to interpreting sentences and extracting opinionated information, their capabilities are known to be very ...
متن کاملECNU: Expression- and Message-level Sentiment Orientation Classification in Twitter Using Multiple Effective Features
Microblogging websites (such as Twitter, Facebook) are rich sources of data for opinion mining and sentiment analysis. In this paper, we describe our approaches used for sentiment analysis in twitter (task 9) organized in SemEval 2014. This task tries to determine whether the sentiment orientations conveyed by the whole tweets or pieces of tweets are positive, negative or neutral. To solve this...
متن کاملA Rule-Based Approach For Effective Sentiment Analysis
The success of Web 2.0 applications has made online social media websites tremendous assets for supporting critical business intelligence applications. The knowledge gained from social media can potentially lead to the development of novel services that are better tailored to users’ needs and at the same time meet the objectives of businesses offering them. Online consumer reviews are one of th...
متن کامل