We present a new challenging stance detection dataset, called Will-They-Won’t-They (WT--WT), which contains 51,284 tweets in English, making it by far the largest available dataset of the type. All the annotations are carried out by experts; therefore, the dataset constitutes a high-quality and reliable benchmark for future research in stance detection. Our experiments with a wide range of recent state-of-the-art stance detection systems show that the dataset poses a strong challenge to existing models in this domain.Keynes Fund, Cambridg
People express their opinions on blogs and other social media platforms. As per a recent estimate, i...
The majority of opinion mining tasks in natural language processing (NLP) have been focused on senti...
We present the IUCL system, based on supervised learning, for the shared task on stance detection. O...
Stance is defined as the expression of a speaker’s standpoint towards a given target or entity. To d...
Stance detection is one of the promising areas of computational linguistics, the task of which is to...
Stance detection (SD) entails classifying the sentiment of a text towards a given target, and is a r...
In this paper, we present a study for the identification of stancerelated features in text data from...
One may express favor (or disfavor) towards a target by using positive or negative language. Here fo...
In this paper, we present StEduCov, an annotated dataset for the analysis of stances toward online e...
Stance detection is a relatively new concept in data mining that aims to assign a stance label (favo...
Stance detection is one of the many NLP tasks that is gaining importance with the spreading of infor...
Stance detection is defined as understanding a person's view and opinion towards a given proposition...
The content posted by users on Social Networks represents an important source of information for a m...
In this paper we describe the participation of the WordUp! team in the VaxxStance shared task at Ibe...
Here for the first time we present a shared task on detecting stance from tweets: given a tweet and ...
People express their opinions on blogs and other social media platforms. As per a recent estimate, i...
The majority of opinion mining tasks in natural language processing (NLP) have been focused on senti...
We present the IUCL system, based on supervised learning, for the shared task on stance detection. O...
Stance is defined as the expression of a speaker’s standpoint towards a given target or entity. To d...
Stance detection is one of the promising areas of computational linguistics, the task of which is to...
Stance detection (SD) entails classifying the sentiment of a text towards a given target, and is a r...
In this paper, we present a study for the identification of stancerelated features in text data from...
One may express favor (or disfavor) towards a target by using positive or negative language. Here fo...
In this paper, we present StEduCov, an annotated dataset for the analysis of stances toward online e...
Stance detection is a relatively new concept in data mining that aims to assign a stance label (favo...
Stance detection is one of the many NLP tasks that is gaining importance with the spreading of infor...
Stance detection is defined as understanding a person's view and opinion towards a given proposition...
The content posted by users on Social Networks represents an important source of information for a m...
In this paper we describe the participation of the WordUp! team in the VaxxStance shared task at Ibe...
Here for the first time we present a shared task on detecting stance from tweets: given a tweet and ...
People express their opinions on blogs and other social media platforms. As per a recent estimate, i...
The majority of opinion mining tasks in natural language processing (NLP) have been focused on senti...
We present the IUCL system, based on supervised learning, for the shared task on stance detection. O...