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ARGUMENTATION IN SOCIAL MEDIA
Call for Papers for a Special Section of the ACM Transactions on
Internet Technology
http://toit.acm.org/CfP.html
Guest-edited by
Iryna Gurevych, UKP Lab, TU Darmstadt
Marco Lippi, DISI, University of Bologna
Paolo Torroni, DISI, University of Bologna
AIMS AND SCOPE
Argumentation is a rapidly expanding multidisciplinary research area at
the confluence of diverse fields such as philosophy, communication
studies, logic and artificial intelligence, computational linguistics,
social sciences, political sciences, and law. The contributions coming
from these heterogeneous disciplines and the large number of potential
applications that can be triggered by these studies have made
argumentation one of the hottest topics within the artificial
intelligence community with immediate relevance to the Web, distributed
computing, and mobile systems.
The Internet and the Web have inspired a variety of real-world
applications for argumentation, since social media, social networks, and
distributed platforms are some of the favorite sources and outlets for
opinions, advice, and comments of any sort for a large share of the
world population, and this type of content could very well lend itself
to argumentative analysis. However, current argumentative analysis
methodologies are costly and pose clear issues of scalability, since
they are mainly manual or only semi-automated, and they require a great
deal of expertise. Indeed, current text-based social media analytics
mainly focuses on approaches such as sentiment analysis, and does not
yet consider argument analysis. Sentiment analysis lets us analyze the
users' opinions about certain topics, but falls short of identifying the
reasons for the opinions expressed and the users' chains and patterns of
reasoning.
Recently we have observed tremendous interest and rapid expansion of
argumentation mining -- the process of automatically extracting
arguments from unstructured text -- as a means of filling this gap.
Developing enabling platforms for formal and informal argumentation in
distributed settings, mining dynamic natural language text, managing
consistency and accuracy in data representation, and information
presentation and visualization at large are very important and certainly
challenging domains for argumentation mining. Social networks and social
media in particular provide high-throughput, highly heterogeneous and
highly dynamic sources of data, which are likely to include significant
argumentative content. With argumentation mining, the potential behind
the combination of social media and argumentation studies has grown,
encompassing domains such as social issues and public policy, with
applications ranging from the analysis of the dynamics of social debates
on the Web to the detection of anomalous behavior; and from the study of
how influential arguments spread and become dominant within social
networks to the role of specific users within this kind of process.
The aim of this TOIT special section is to address the important
challenges that argumentation in the Web poses, involving the
perspective of distributed computing. These include, but are not limited
to, the development of algorithms and architectures for mining large
volumes of highly dynamic unstructured or semi-structured data
especially natural language text coming from social media; the
definition of appropriate models and structures that enable processing
and visualizing such data; the privacy, trust, legal, and ethical issues
related to the management and processing of user-generated argumentative
content; the development of enabling platforms for formal and informal
argumentation in distributed and agent-based environments; the
management of consistent and accurate data representations; the novel
use of resources such as ontologies and vocabulary systems; and the
presentation of large, complex, community-based argumentative content in
a usable way.
TOPICS
A list of topics to be covered by this special section includes, but is
not limited to a set of areas listed below.
Foundations
· Information models of user-generated arguments and debate in social media
· Argumentation-enabled collective intelligence and collaboration
· Security, privacy, trust, and ethical issues related to argumentative
analysis
Methods and technologies
· Mining and visualization of large volumes of highly dynamic data
· Argumentation and social informatics, social computing, and crowdsourcing
· Innovative semantic search methods, algorithms, and tools
· Middleware and APIs for online debating technologies
Applications
· Argumentation mining in social media
· Processing of user reviews for online entertainment, e-commerce, and
e-business applications
· Argumentation for e-learning
· Argumentation analysis for policy making
· Argumentation and online debates and mining for e-government
SUBMISSION INSTRUCTIONS
Manuscripts to this special section should be submitted via the
Manuscript Central website linked here:
http://toit.acm.org/submission.html Please select “Special Section:
Argumentation in Social Media” under Manuscript Type dropdown in the
Manuscript Central website. Submissions should be in the ACM
Transactions style, and limited to 20 pages. Authors should adhere to
the submission instructions and editorial policies described at
http://toit.acm.org/submission.html
IMPORTANT DATES
Submissions: 15 January 2016
First decisions: 16 May 2016
Revisions: 20 July 2016
Final decisions: 15 September 2016
Final submissions: 14 October 2016
Publication: January 2017
CONTACT INFORMATION
Please direct all your inquiries to [email protected]
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