In this paper, we explore a target-dependent Twitter SA model that does not use external syntactic analyzers, by leveraging dis- tributed word representations ...

In particular, we split a tweet into a left context and a right context according to a given target, using distributed word representations and neural pooling ...

This paper shows that competitive results can be achieved without the use of syntax, by extracting a rich set of automatic features from a tweet, ...

Jun 19, 2011 · In our approach, rich feature representations are used to distinguish between sentiments expressed towards different targets. In order to ...

In this paper, we propose to improve target-dependent Twitter sentiment classification by 1) incorporating target-dependent features; and 2) taking related ...

This paper proposes to improve target-dependent Twitter sentiment classification by incorporating target- dependent features; and taking related tweets into ...

This code is used for the paper "Target-dependent Twitter Sentiment Classification with Rich Automatic Features" (IJCAI2015) To run the "targetdep+" model: ...

TweetSenti is a system for analyzing the sentiment of an entity in tweets. A sentence or tweet may contain multiple entities, and they do not always have ...

Missing: Rich Automatic

Jul 29, 2024 · Twitter-based sentiment analysis (TSA) is a method for automatically processing digital data to extract opinions.