Workshops

WSDM 2017 features five workshops. All WSDM 2017 workshops will be held on Friday February 10, 2017.

Workshop on Scholarly Web Mining (SWM 2017)
  • Organizers: Robert Patton, Thomas Potok, Petr Knoth, Drahomira Herrmannova
  • https://ornlcda.github.io/SWM2017/
  • Researchers increasingly report their results through online publications, from research papers, data and software to experiments, observations and ideas. Immense amount of research-related data is available on the web on interlinked pages, in repositories, databases, social networking sites, etc. Consequently, researchers rely on online sources, often through search engines, to perform literature searches for their research — to search for papers, topics, people etc. to be able to produce new research. However, these publications can be used not only for traditional literature searches, but also as a source for discovering popular and emerging research topics, key publications and people or evaluating research excellence. To aid research, it is important to leverage the potential of data mining technologies to improve the process of how research is being done. This workshop aims to bring together people from different backgrounds who are interested in analysing and mining scholarly data available via web and social media sources using various approaches such as query log mining, graph analysis, text mining, etc., and/or who develop systems that enable such analysis and mining.
  • This is a half-day workshop.
Workshop for WSDM Cup 2017: Vandalism Detection and Triple Scoring
  • Organizers: Stefan Heindorf, Martin Potthast, Hannah Bast, Gregor Engels, Benno Stein
  • http://www.wsdm-cup-2017.org/
  • The WSDM Cup 2017 addressed key challenges of knowledge bases today: quality assurance and entity search. For quality assurance, we tackle the task of vandalism detection, based on a dataset of more than 82 million user-contributed revisions of the Wikidata knowledge base, all of which annotated with regard to whether or not they are vandalism. For entity search, we tackle the task of triple scoring, using a dataset that comprises relevance scores for triples from type-like relations including occupation and country of citizenship, based on about 10,000 human relevance judgments. For reproducibility sake, participants were asked to submit their software on TIRA, a cloud-based evaluation platform, and they were incentivized to share their approaches open source. In this workshop, we discuss the approaches and results.
  • This is a half-day workshop.
International Workshop on Mining Actionable Insights from Social Networks (MAISoN’17)
  • Organizers: Ebrahim Bagheri, Zeinab Noorian, Faezeh Ensan
  • http://ls3.rnet.ryerson.ca/MAISoN/2017/
  • 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.
  • This is a full-day workshop.
WSDM 2017 Workshop on Mining Online Health Reports
  • Organizers: Nigel Collier, Nut Limsopatham, Ingemar J. Cox, Vasileios Lampos, Aron Culotta and Mike Conway
  • https://sites.google.com/site/mohrs2017/home
  • Online health information is widely published by individuals in social media, chat rooms and discussion boards. At the same time search query logs and various forms of text messaging contain a vast amount of textual information that can be directly or indirectly linked to health conditions. This informal evidence about our individual health, attitudes and behaviours has the potential to be a valuable source for health applications ranging from real-time disease monitoring, to prioritising victim responses during disasters and detecting novel applications for drugs. However, in order to understand and integrate this data, researchers in academia and industry must grapple with theoretical, practical and ethical challenges that require immediate attention. The objective of the workshop is to bring  together a cross-disciplinary community of researchers to contribute to the debate around four main questions:  How can current sources of online health reports be characterised and what are the strengths and weaknesses of each? How are online health reports being processed using NLP/IR/ML technologies and/or integrated into traditional forms of health data such as biomedical databases and patient records?  How is online health data being used in real-world case studies and field evaluations? and What are the ethical/legal issues surrounding the exploitation of personal health reports?
  • This is a full-day workshop.
Cyber Deviance Detection (CyberDD 2017)
  • Organizers: Theodora Tsikrika, Pete Burnap, Babak Akhgar, Vasilis Katos, Stefanos Vrochidis, Matthew Williams
  • http://mklab.iti.gr/cyberdd2017/
  • Cyber Deviance refers to the deliberate misuse of technical infrastructure for subversive purposes and includes (but is not limited to): the spreading of extremist propaganda, antagonistic or hateful commentary; the distribution of malware; online fraud and identity theft; denial of service attacks; etc. Better understanding of such phenomena on the Web (including social media) allows for their early detection and underpins the development of effective models for predicting cyber security threats. The CyberDD 2017 workshop will focus on two research tracks: (i) Detecting and Mining Terrorist Online Content and (ii) Advances in Data Science for Cyber Security and Risk on the Web. The aim of the workshop is to bring together researchers and practitioners in Web search, data mining, security informatics, multimedia understanding, social media analysis, machine learning, digital forensics, and criminology with particular interest on cyber security, as well as industry representatives from search engines and social media platforms.
  • This is a full-day workshop.