TY - GEN
T1 - The 5th International Workshop on Mining Actionable Insights from Social Networks (MAISoN 2020)
T2 - 29th ACM International Conference on Information and Knowledge Management, CIKM 2020
AU - Bagheri, Ebrahim
AU - Liu, Huan
AU - Shu, Kai
AU - Zarrinkalam, Fattane
N1 - Publisher Copyright: © 2020 Owner/Author.
PY - 2020/10/19
Y1 - 2020/10/19
N2 - For the fifth edition of the workshop on Mining Actionable Insights from Social Networks (MAISoN), we organized a special edition with focus on dis/misinformation mining from social media, co-located with CIKM 2020. This topic has attracted a lot of interest from the community since the Coronavirus (COVID-19) epidemic has given rise to an increase of misinformation on social media. The aim of this edition was to bring together researchers from different disciplines interested in mining dis/misinformation on social media. In particular, the distinguishing focus of this special edition was its emphasis on techniques that use social media data for building diagnostic, predictive and prescriptive analysis models related to misinformation. This means that there is rigorous attention for techniques that can be used to understand how and why dis/misinformation is created and spread, to uncover hidden and unexpected aspects of dis/misinformation content, and to recommend insightful countermeasures to restrict the circulation of dis/misinformation and alleviate their negative effects.
AB - For the fifth edition of the workshop on Mining Actionable Insights from Social Networks (MAISoN), we organized a special edition with focus on dis/misinformation mining from social media, co-located with CIKM 2020. This topic has attracted a lot of interest from the community since the Coronavirus (COVID-19) epidemic has given rise to an increase of misinformation on social media. The aim of this edition was to bring together researchers from different disciplines interested in mining dis/misinformation on social media. In particular, the distinguishing focus of this special edition was its emphasis on techniques that use social media data for building diagnostic, predictive and prescriptive analysis models related to misinformation. This means that there is rigorous attention for techniques that can be used to understand how and why dis/misinformation is created and spread, to uncover hidden and unexpected aspects of dis/misinformation content, and to recommend insightful countermeasures to restrict the circulation of dis/misinformation and alleviate their negative effects.
KW - disinformation
KW - domain insights
KW - misinformation
KW - predictive modelling
KW - prescriptive modeling
KW - social media
UR - http://www.scopus.com/inward/record.url?scp=85095862984&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85095862984&partnerID=8YFLogxK
U2 - 10.1145/3340531.3414078
DO - 10.1145/3340531.3414078
M3 - Conference contribution
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 3527
EP - 3528
BT - CIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
PB - Association for Computing Machinery
Y2 - 19 October 2020 through 23 October 2020
ER -