Aims and Scope

Context. The wide adoption of social networks 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, 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 advantage. In particular, marketeers 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.

Goal. Traditional research in social network mining mainly focuses on theories and methodologies for community discovery, pattern detection and evolution, behavioral analysis and anomaly (misbehavior) detection. The main distinguishing focus of this 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. The objectives will be to transform insights into effective actions which could help organizations improve and refine their strategies. Thus, the focus is on social network analysis and mining techniques to gain actionable real-world insights.

Call for papers. In this workshop, we aim to to invite and gather researchers and practitioners from across the world and, in particular, from different disciplines, such as information retrieval, big data mining, machine learning, data science, 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.

We solicit original, unpublished and innovative research work on all aspects related to the theme of this workshop. The deadline for submissions of articles is January 10th, 2020.

Submission:

https://easychair.org/conferences/?conf=maison20