Published on Sun Feb 26 2017

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

Mirko Lai, Delia Irazú Hernández Farías, Viviana Patti, Paolo Rosso

Stance detection is the task of identifying the speaker's opinion towards a particular target. This paper describes a novel approach for detecting stance in Twitter. We are interested in investigating political debates in social media.

0
0
0
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 Task6 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.

Fri May 01 2020
NLP
Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter
Will-They-Won't-They (WT-WT) contains 51,284 tweets in English. All the annotations are carried out by experts. The dataset constitutes a high-quality and reliable benchmark for future research.
0
0
0
Sun Sep 03 2017
NLP
A Semi-Supervised Approach to Detecting Stance in Tweets
Stance classification aims to identify, for a particular issue under discussion, whether the speaker or author of a conversational turn has Pro(Favor) or Con (Against) stance on the issue. Detecting stance in tweets is a new task proposed for SemEval-2016 Task6.
0
0
0
Mon Jan 07 2019
NLP
Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation Structure
Analysing how people react to rumours associated with news in social media is an important task to prevent the spreading of misinformation. In social media conversations, users show different stances and attitudes towards rumourous stories. Some users take a definite stance, supporting or denying the rumour at issue,
0
0
0
Fri Mar 23 2018
NLP
Stance Detection on Tweets: An SVM-based Approach
Stance detection is a subproblem of sentiment analysis. The stance output is usually given as Favor, Against, or Neither. The employed features are based on unigrams, bigrams, hashtags, external links, and lastly, named entities.
0
0
0
Wed Jun 21 2017
NLP
Stance Detection in Turkish Tweets
Stance detection is a classification problem in natural language processing. It is similar to the sentiment analysis problem but instead of the sentiment of the text author, the stance expressed for a particular target is investigated. This study is significant as it presents one of the initial stance detection data sets proposed so far.
0
0
0
Sat Sep 15 2018
Machine Learning
Inferring Political Alignments of Twitter Users: A case study on 2017 Turkish constitutional referendum
Increasing popularity of Twitter in politics is subject to commercial and academic interest. To fully exploit the merits of this platform, reaching the desired audience with desired political leanings is critical. This paper extends research on inferring political orientations of Twitter users to the case of 2017 Turkish constitutional referendum.
0
0
0