Detecting Stance in Tweets And Analyzing its Interaction with Sentiment
نویسندگان
چکیده
One may express favor (or disfavor) towards a target by using positive or negative language. Here for the first time we present a dataset of tweets annotated for whether the tweeter is in favor of or against pre-chosen targets, as well as for sentiment. These targets may or may not be referred to in the tweets, and they may or may not be the target of opinion in the tweets. We develop a simple stance detection system that outperforms all 19 teams that participated in a recent shared task competition on the same dataset (SemEval-2016 Task #6). Additionally, access to both stance and sentiment annotations allows us to conduct several experiments to tease out their interactions. We show that while sentiment features are useful for stance classification, they alone are not sufficient. We also show the impacts of various features on detecting stance and sentiment, respectively.
منابع مشابه
A Joint Sentiment-Target-Stance Model for Stance Classification in Tweets
Classifying the stance expressed in online microblogging social media is an emerging problem in opinion mining. We propose a probabilistic approach to stance classification in tweets, which models stance, target of stance, and sentiment of tweet, jointly. Instead of simply conjoining the sentiment or target variables as extra variables to the feature space, we use a novel formulation to incorpo...
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