Researchers are beginning to explore how to generate summaries of extended argumentative conversations in social media, such as those found in reader comments in on-line news. To date, however, there has been little discussion of what these summaries should be like and a lack of humanauthored exemplars, quite likely because writing summaries of this kind of interchange is so difficult. In this paper we propose one type of reader comment summary – the conversation overview summary – that aims to capture the key argumentative content of a reader comment conversation. We describe a method we have developed to support humans in authoring conversation overview summaries and present a publicly available corpus – the first of its...
Comments left by readers on Web documents contain valu-able information that can be utilized in diff...
User comments in response to newspaper articles published online offer a unique resource for studyin...
User-contributed comments are one of the hallmarks of the Social Web, widely adopted across social m...
Automatic summarization of reader comments in on-line news is a challenging but clearly useful task...
Automatic Text Summarization is the challenging NLP task of summarizing some source input text - a s...
Abstractive summarization is a technique that allows for extracting condensed meanings from long tex...
Readers of a news article often read its comments contributed by other readers. By reading comments,...
User commenting is a valuable feature of many news outlets, enabling them a contact with readers and...
Comments are generally short pieces of text that one uses to share their opinions online. With the i...
In neural abstractive summarization field, conventional sequence-to-sequence based models often suff...
Large state-of-the-art corpora for training neural networks to create abstractive summaries are most...
This work proposes a trainable system for summarizing news and obtaining an approximate argumentati...
User comments in response to newspaper articles published online offer a unique resource for studyin...
Online communities host growing numbers of discussions amongst large groups of participants on all m...
With the diffusion of online newspapers and social media, users are becoming capable of retrieving d...
Comments left by readers on Web documents contain valu-able information that can be utilized in diff...
User comments in response to newspaper articles published online offer a unique resource for studyin...
User-contributed comments are one of the hallmarks of the Social Web, widely adopted across social m...
Automatic summarization of reader comments in on-line news is a challenging but clearly useful task...
Automatic Text Summarization is the challenging NLP task of summarizing some source input text - a s...
Abstractive summarization is a technique that allows for extracting condensed meanings from long tex...
Readers of a news article often read its comments contributed by other readers. By reading comments,...
User commenting is a valuable feature of many news outlets, enabling them a contact with readers and...
Comments are generally short pieces of text that one uses to share their opinions online. With the i...
In neural abstractive summarization field, conventional sequence-to-sequence based models often suff...
Large state-of-the-art corpora for training neural networks to create abstractive summaries are most...
This work proposes a trainable system for summarizing news and obtaining an approximate argumentati...
User comments in response to newspaper articles published online offer a unique resource for studyin...
Online communities host growing numbers of discussions amongst large groups of participants on all m...
With the diffusion of online newspapers and social media, users are becoming capable of retrieving d...
Comments left by readers on Web documents contain valu-able information that can be utilized in diff...
User comments in response to newspaper articles published online offer a unique resource for studyin...
User-contributed comments are one of the hallmarks of the Social Web, widely adopted across social m...