Ranking-based Method for News Stance Detection

Qiang Zhang; Emine Yilmaz; Shangsong Liang

doi:10.1145/3184558.3186919

Ranking-based Method for News Stance Detection

Qiang Zhang, Emine Yilmaz, Shangsong Liang

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

33 Scopus citations

Abstract

A valuable step towards news veracity assessment is to understand stance from different information sources, and the process is known as the stance detection. Specifically, the stance detection is to detect four kinds of stances (

Original language	English (US)
Title of host publication	Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18
Publisher	Association for Computing Machinery (ACM)
ISBN (Print)	9781450356404
DOIs	https://doi.org/10.1145/3184558.3186919
State	Published - Apr 18 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research was supported by the China Scholarship Council (CSC) for award No. 201704910908.

Access to Document

10.1145/3184558.3186919

https://repository.kaust.edu.sa/bitstream/10754/627607/1/p41-zhang.pdf

Cite this

@inproceedings{b70d5ed59b5540e5a4be53aecfa62c13,

title = "Ranking-based Method for News Stance Detection",

abstract = "A valuable step towards news veracity assessment is to understand stance from different information sources, and the process is known as the stance detection. Specifically, the stance detection is to detect four kinds of stances (",

author = "Qiang Zhang and Emine Yilmaz and Shangsong Liang",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This research was supported by the China Scholarship Council (CSC) for award No. 201704910908.",

year = "2018",

month = apr,

day = "18",

doi = "10.1145/3184558.3186919",

language = "English (US)",

isbn = "9781450356404",

booktitle = "Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

}

TY - GEN

T1 - Ranking-based Method for News Stance Detection

AU - Zhang, Qiang

AU - Yilmaz, Emine

AU - Liang, Shangsong

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This research was supported by the China Scholarship Council (CSC) for award No. 201704910908.

PY - 2018/4/18

Y1 - 2018/4/18

N2 - A valuable step towards news veracity assessment is to understand stance from different information sources, and the process is known as the stance detection. Specifically, the stance detection is to detect four kinds of stances (

AB - A valuable step towards news veracity assessment is to understand stance from different information sources, and the process is known as the stance detection. Specifically, the stance detection is to detect four kinds of stances (

UR - http://hdl.handle.net/10754/627607

UR - https://dl.acm.org/citation.cfm?doid=3184558.3186919

U2 - 10.1145/3184558.3186919

DO - 10.1145/3184558.3186919

M3 - Conference contribution

SN - 9781450356404

BT - Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18

PB - Association for Computing Machinery (ACM)

ER -

Ranking-based Method for News Stance Detection

Abstract

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this