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This book serves as a convenient entry point for researchers,
practitioners, and students to understand the problems and
challenges, learn state-of-the-art solutions for their specific
needs, and quickly identify new research problems in their domains.
The contributors to this volume describe the recent advancements in
three related parts: (1) user engagements in the dissemination of
information disorder; (2) techniques on detecting and mitigating
disinformation; and (3) trending issues such as ethics, blockchain,
clickbaits, etc. This edited volume will appeal to students,
researchers, and professionals working on disinformation,
misinformation and fake news in social media from a unique lens.
This book serves as a convenient entry point for researchers,
practitioners, and students to understand the problems and
challenges, learn state-of-the-art solutions for their specific
needs, and quickly identify new research problems in their domains.
The contributors to this volume describe the recent advancements in
three related parts: (1) user engagements in the dissemination of
information disorder; (2) techniques on detecting and mitigating
disinformation; and (3) trending issues such as ethics, blockchain,
clickbaits, etc. This edited volume will appeal to students,
researchers, and professionals working on disinformation,
misinformation and fake news in social media from a unique lens.
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Combating Online Hostile Posts in Regional Languages during Emergency Situation - First International Workshop, CONSTRAINT 2021, Collocated with AAAI 2021, Virtual Event, February 8, 2021, Revised Selected Papers (Paperback, 1st ed. 2021)
Tanmoy Chakraborty, Kai Shu, H.Russell Bernard, Huan Liu, Md Shad Akhtar
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes selected and revised papers from the First
International Workshop on Combating On line Ho st ile Posts in
Regional Languages dur ing Emerge ncy Si tuation, CONSTRAINT 2021,
Collocated with AAAI 2021, held as virtual event, in February 2021.
The 14 full papers and 9 short papers presented were thoroughly
reviewed and selected from 62 qualified submissions. The papers
present interdisciplinary approaches on multilingual social media
analytics and non-conventional ways of combating online hostile
posts.
In the past decade, social media has become increasingly popular
for news consumption due to its easy access, fast dissemination,
and low cost. However, social media also enables the wide
propagation of "fake news," i.e., news with intentionally false
information. Fake news on social media can have significant
negative societal effects. Therefore, fake news detection on social
media has recently become an emerging research area that is
attracting tremendous attention. This book, from a data mining
perspective, introduces the basic concepts and characteristics of
fake news across disciplines, reviews representative fake news
detection methods in a principled way, and illustrates challenging
issues of fake news detection on social media. In particular, we
discussed the value of news content and social context, and
important extensions to handle early detection, weakly-supervised
detection, and explainable detection. The concepts, algorithms, and
methods described in this lecture can help harness the power of
social media to build effective and intelligent fake news detection
systems. This book is an accessible introduction to the study of
detecting fake news on social media. It is an essential reading for
students, researchers, and practitioners to understand, manage, and
excel in this area. This book is supported by additional materials,
including lecture slides, the complete set of figures, key
references, datasets, tools used in this book, and the source code
of representative algorithms. The readers are encouraged to visit
the book website for the latest information:
http://dmml.asu.edu/dfn/
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