International Workshop on Mining Actionable Insights from Social Networks
MAISoN 2017: http://ls3.rnet.ryerson.ca/MAISoN/2017/
Co-located with Tenth ACM International Web Search and Data Mining (
WSDM) Conference in Cambridge, UK February 6-10, 2017.
http://www.wsdm-conference.org/2017/The
wide adoption of social network churns out an ocean of data which
presents an interesting opportunity for mining the data and discover new
knowledge to predict real-world outcomes. The enormity and high
variance of the information that propagates through large user
communities influence 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 attributes and contents of social network provides an opportunity
to discover social structure characteristics, analyze action patterns
qualitatively and quantitatively, and 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. In particular, marketers aggregate the
opinions of the collective population to dynamically calibrate,
anticipate and offer products and services that meet perpetually
shifting consumer demands in a hyper-competitive marketplace. The
traditional research in social network mainly focus on theories and
methodologies on community discovery, pattern detection and evolution,
behavioural analysis and anomaly and misbehaviour detection. The main
distinguishing focus of this workshop will be the use of social media
data for building predictive models that can be used to uncover hidden
and unexpected aspects of user-generated content in order to extract
actionable insight from them. The objectives will be to transform the
insight into effective actions which could help organizations improve
and refine their strategies.
In this workshop, we invite
researchers and practitioners from different disciplines such as
computer science, big data mining, machine learning, 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.
TopicsWe solicit original, unpublished and innovative research work on all aspects around, but not limited to, the following themes:
• Applications of Social Network Analysis
• 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
◦ Determining user similarities, trustworthiness and reliability
• Social networks and information/knowledge dissemination
◦ Topic and trend prediction
◦ Prediction of information diffusion patterns
◦ Identification of causality and correlation between event/topics/communities
• Information diffusion modeling with social networks
◦ Sentiment diffusion in social network
◦ Competitive intelligence from social networks
• Merging internal (proprietary) data with social data
• Search Behaviour Analytics with Social Networks
• Feature Engineering from Social Networks
• Social Networks and Recommender Systems
• Sentiment Analysis and Prediction on Social Networks
• Datasets and Evaluation methodologies for predictive modeling in social networks
Format and SubmissionWe
invite the submission of regular research papers (6-8 pages) as well as
position papers (2-4 pages). We recommend papers to be formatted
according to the standard double-column ACM Guidelines. All papers will
be peer reviewed by three reviewers.
All submissions must be submitted
in PDF format according to the guidelines through the Easychair
installation:
https://easychair.org/conferences/?conf=maison2017 Important Dates • Submission: November 10, 2016
• Decisions: December 5, 2016
Submissions will be due Midnight AoE time.
Organizers • Ebrahim Bagheri, Ryerson University <bagheri at ryerson dot ca >
• Zeinab Noorian, Ryerson University
• Faezeh Ensan, Ferdowsi University of Mashhad
_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to