Aims and Scope

Context. The wide adoption of social media 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. This influence can however act as a double-edged sword, since it can also introduce threats to the community, if it is rooted in dissemination of disinformation, i.e. purposefully manipulated news and information, or misinformation, i.e. false and incorrect information, on social media. In recent years, the potential threats of dis/misinformation has been the subject of huge controversy in different domains like public healthcare systems, socio-economics, business and politics. For instance, the circulation of scientifically invalid information and news can negatively affect the way the public responds to the outbreak of a pandemic disease, like COVID-19. Threats can also be posed to the legitimacy of an election system by enabling opponent campaigns to shape the public opinion based on conspiracy theories stemming from false information. Mining the contents of social media to recognize the instances of misinformation and disinformation is a very first step towards immunizing the public society against the negative impacts they could introduce.

Goal. Traditional research on dis/misinformation mining from social media mainly focuses on descriptive methods such as fake news detection and propagation analysis, malicious bot detection, fact-checking social media content, and detecting the source of claims and rumors. The main distinguishing focus of this special issue will be the use of social media data for building diagnostic, predictive and prescriptive analysis models that can be used to understand how and why dis/misinformation is created and spread, to uncover hidden and unexpected aspects of dis/misinformation content, and to recommend insightful countermeasures to restrict the circulation of dis/misinformation and alleviate their negative effects. The ultimate goal is to immunize the social media against dis/misinformation and improving the trustworthiness of the social content and the socio-economic and business systems working based on the insights mined from social media. The main focus of the special issue is on proposing models and methods for tackling dis/misinformation in real-world scenarios.

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 dis/misinformation from social media.

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 July 24, 2020 August 1, 2020.

Submission:

https://easychair.org/conferences/?conf=maison2020