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*CALL FOR PAPERSThe Joint International Workshop on Social Influence
Analysis and Mining Actionable Insights from Social Networks (SocInf+MAISoN
2018)In conjunction with the Federated AI Meeting (FAIM) / IJCAI-ECAI 2018
July 13-19, 2018Stockholm, SwedenWebsite:
<>Twitter: <>AIM AND
SCOPE The wide adoption of social networks over the past years has resulted
in an ocean of data which presents an interesting opportunity for
performing data mining and knowledge discovery in a real-world context. The
enormity and high variance of the information that propagates through large
user communities influences the public discourse in society and sets trends
and agendas in topics that range from marketing, education, business and
medicine to politics, technology and the entertainment industry. Mining the
contents of social networks provides an opportunity to discover social
structure characteristics, to analyze action patterns qualitatively and
quantitatively, and gives the ability to predict future events. In recent
years, decision makers have become savvy about how to translate social data
into actionable information in order to leverage them for a competitive
edge. Moreover,  social networks expose different aspects of the social
behavior of its users. In this respect, many users of social networks are
known as influencers. The influencers are users that usually publish their
opinions about different topics, products and services on the social
networks, and then affect intentionally or unintentionally the opinions,
emotions, or behaviors of other users on the social networks. Because of
the high impact of influencers on the opinions and behaviors of other
users, many organizations are interested in discovering influencers on
social networks to increase the promotion and sale of their products and
services. However, the discovery of influencers on social networks is a
very complex problem that requires developing models, techniques and
algorithms for an appropriate analysis.Traditional research in social
network mining mainly focuses on theories and methodologies for community
discovery, pattern detection and evolution, behavioural analysis and
anomaly (misbehaviour) detection. While interesting and definitely
worthwhile, the main distinguishing focus of this joint workshop will be
the use of social network data for building predictive models that can be
used to uncover hidden and unexpected aspects of user-generated content in
order to extract actionable insights from them and for analyzing different
aspects of social influence, such as influence maximization and discovering
influencers. Thus, the focus is on algorithms and methods for (social)
network analysis, data mining techniques to gain actionable real-world
insights, and models and approaches for understanding influence
dissemination and discovering influential users in social networks.In this
joint workshop, we invite researchers and practitioners, both from academia
and industry, from different disciplines such as computer science, data
mining, machine learning, network science, social network analysis and
other related areas to share their ideas and research achievements in order
to deliver technology and solutions for mining actionable insight from
social network data. TOPICS OF INTERESTWe solicit original, unpublished and
innovative research work on all aspects around, but not limited to, the
following themes: - Social networks and information/knowledge
dissemination- Topic and trend prediction- Prediction of information
diffusion patterns- Identification of causality and correlation between
event/topics/communities- Social network analysis and measures- Network
topology- Centrality measures- Community detection- Dynamic network models-
Diffusion models- Information diffusion modeling with social networks-
Information propagation and assimilation in social networks - Sentiment
diffusion in social networks- Competitive intelligence from social
networks- Social influence analysis on online social networks- Systems and
algorithms for discovering influential users - Recommending influential
users in online social networks - Social influence maximization - Modeling
social networks and behavior for discovering influential users -
Discovering influencers for advertising and viral marketing in social
networks - Decision support systems and influencer discovering - Predictive
modeling based on social networks such as- Box office prediction- Election
prediction- Flu prediction- Product adaptation models with social networks
such as- Sale price prediction- New product popularity prediction- Brand
popularity- Business downfall prediction- User modeling and social networks
including- Predict users daily activities including recurring events- User
churn prediction- Trust and reputation- Determining user similarities,
trustworthiness and reliabilityIMPORTANT DATES* Submission deadline: April
30, 2018* Notification date: June 3, 2018* Final version submission date :
June 17, 2018* Workshop: July 13-19, 2018 (exact date to be announced by
IJCAI organization)PROGRAM COMMITTEE CHAIRS - Marcelo G. Armentano
<>, ISISTAN Research
Institute (CONICET- UNICEN), Argentina- Ebrahim Bagheri
<>, Ryerson University,
Canada- Jérôme Kunegis <>,
University of Namur, Belgium- Frank Takes <>,
University of Amsterdam, The Netherlands- Jie Tang
<>, Tsinghua University, China-
Michalis Vazirgiannis
<>, École
Polytechnique, France- Virginia D. Yannibelli
<>, ISISTAN Research Institute
(CONICET- UNICEN), Argentina*

To be confirmed

*SUBMISSION AND SELECTION PROCESSSubmitted papers must be no longer than
seven pages (long papers, the last page may only contain references) or
three pages (position papers), including all figures, tables etc., and
should be formatted according to the style guide of IJCAI-ECAI 2018
Formatting Guidelines, LaTeX style or Word Template:
( <>).
Papers should be submitted in PDF format, with no information about authors
or affiliations (double blind review), through the EasyChair Conference
System (
<>).Each submitted
paper to SocInf+MAISoN 2018 will be refereed by at least three members of
the Workshop Program Committee, based on its originality, significance,
technical soundness, and clarity of expression. Submissions must be in
English, and can present mature research or experimental results as well as
promising work in progress. SPECIAL ISSUEThe authors of accepted papers
will be invited to submit a substantial extension of their manuscript (with
at least 30% additional content) to a special issue of the Elsevier
Information Processing and Management
journal.CONTACT [log in to unmask]
<[log in to unmask]>*Please feel free to circulate this CFP among
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