TY - GEN
T1 - How to Assess and Rank User-Generated Content on Web
AU - Momeni, Elaheh
AU - Cardie, Claire
AU - Diakopoulos, Nicholas
N1 - Publisher Copyright:
© 2018 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC BY 4.0 License.
PY - 2018/4/23
Y1 - 2018/4/23
N2 - User-generated content (UGC) on the Web, especially on social media platforms, facilitates the association of additional information with digital resources and online social topics and it can provide valuable supplementary content. However, UGC varies in quality and, consequently, raises the challenge of how to maximize its utility for a variety of end-users, in particular in the age of misinformation. This study aims to provide researchers and Web data curators with answers to the following questions: (1) What are the existing approaches and methods for assessing and ranking UGC (2) What features and metrics have been used successfully to assess and predict UGC value across a range of application domains This survey is composed of a systematic review of approaches for assessing and ranking UGC: results obtained by identifying and comparing methodologies within the context of short text-based UGC on the Web. This survey categorizes existing assessment and ranking approaches into four framework types and discusses the main contributions and considerations of each type. Furthermore, it suggests a need for further experimentation and encourages the development of new approaches for the assessment and ranking.
AB - User-generated content (UGC) on the Web, especially on social media platforms, facilitates the association of additional information with digital resources and online social topics and it can provide valuable supplementary content. However, UGC varies in quality and, consequently, raises the challenge of how to maximize its utility for a variety of end-users, in particular in the age of misinformation. This study aims to provide researchers and Web data curators with answers to the following questions: (1) What are the existing approaches and methods for assessing and ranking UGC (2) What features and metrics have been used successfully to assess and predict UGC value across a range of application domains This survey is composed of a systematic review of approaches for assessing and ranking UGC: results obtained by identifying and comparing methodologies within the context of short text-based UGC on the Web. This survey categorizes existing assessment and ranking approaches into four framework types and discusses the main contributions and considerations of each type. Furthermore, it suggests a need for further experimentation and encourages the development of new approaches for the assessment and ranking.
KW - adaptive and interactive
KW - assessment and ranking
KW - crowd-based
KW - social media
KW - user-generated content
UR - http://www.scopus.com/inward/record.url?scp=85077304346&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077304346&partnerID=8YFLogxK
U2 - 10.1145/3184558.3186239
DO - 10.1145/3184558.3186239
M3 - Conference contribution
AN - SCOPUS:85077304346
T3 - The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
SP - 489
EP - 493
BT - The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
PB - Association for Computing Machinery, Inc
T2 - 27th International World Wide Web, WWW 2018
Y2 - 23 April 2018 through 27 April 2018
ER -