Stance detection, the task of identifying the speaker’s opinion towards a particular target, has attracted the attention of researchers. This paper describes a novel approach for detecting stance in Twitter. We define a set of features in order to consider the context surrounding a target of interest with the final aim of training a model for predicting the stance towards the mentioned targets. In particular, we are interested in investigating political debates in social media. For this reason we evaluated our approach focusing on two targets of the SemEval-2016 Task 6 on Detecting stance in tweets, which are related to the political campaign for the 2016 U.S. presidential elections: Hillary Clinton vs. Donald Trump. For the sake of comparison with the state of the art, we evaluated our model against the dataset released in the SemEval-2016 Task 6 shared task competition. Our results outperform the best ones obtained by participating teams, and show that information about enemies and friends of politicians help in detecting stance towards them.

Friends and Enemies of Clinton and Trump: Using Context for Detecting Stance in Political Tweets

Lai Mirko;Hernández Farías Delia Irazu;Patti Viviana;
2017-01-01

Abstract

Stance detection, the task of identifying the speaker’s opinion towards a particular target, has attracted the attention of researchers. This paper describes a novel approach for detecting stance in Twitter. We define a set of features in order to consider the context surrounding a target of interest with the final aim of training a model for predicting the stance towards the mentioned targets. In particular, we are interested in investigating political debates in social media. For this reason we evaluated our approach focusing on two targets of the SemEval-2016 Task 6 on Detecting stance in tweets, which are related to the political campaign for the 2016 U.S. presidential elections: Hillary Clinton vs. Donald Trump. For the sake of comparison with the state of the art, we evaluated our model against the dataset released in the SemEval-2016 Task 6 shared task competition. Our results outperform the best ones obtained by participating teams, and show that information about enemies and friends of politicians help in detecting stance towards them.
MICAI 2016
Cancún, Mexico
23-29 October
Lecture Notes in Computer Science
Springer
10061
155
168
978-3-319-62433-4
978-3-319-62434-1
https://link.springer.com/chapter/10.1007/978-3-319-62434-1_13
https://www.researchgate.net/publication/318856078_Friends_and_Enemies_of_Clinton_and_Trump_Using_Context_for_Detecting_Stance_in_Political_Tweets
https://www.google.it/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwiOkJmky8_XAhWPyKQKHfFXBO0QFggmMAA&url=https%3A%2F%2Farxiv.org%2Fabs%2F1702.08021&usg=AOvVaw3MWNUctIjR_kRZqso3H1Tb
Lai, Mirko; HERNANDEZ FARIAS, DELIA IRAZU; Patti, Viviana; Rosso, Paolo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1652427
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