Workshops & Tutorials

The ability to automatically process and interpret text fused with emoji will be essential as society embraces emoji as a standard form of online communication. However, processing emoji using traditional natural language processing techniques is a challenging task due to the pictorial nature of emoji and the fact that (the same) emoji may be used in different contexts and cultures to express different meanings. Emoji2019 aims to stimulate research on understanding social, cultural, communicative, and linguistic roles of emoji and developing novel approaches to analyze, interpret and understand them in social media. It provides a forum for researchers and practitioners from both academia and industry to discuss high-quality research, to exchange ideas, and to identify new opportunities for collaboration.

Machine learning and AI techniques are particularly effective in situations where deep and predictive insights need to be uncovered from such social media data sets that are large, diverse and fast changing. We aim to focus on how to apply data mining, recommendation, machine learning and AI models, algorithms and systems for analytic and predictive modeling on social media, big data, small data, web and sensor data. We invite researchers that are interested in going beyond standard analytics approaches and try to discover the intelligent information hidden in the large and fast-changing social media data.

The International Workshop of Deep Learning for Graphs and Structured Data Embedding aims to provide a forum for presenting the most recent advances in embedding and representation learning for structured data as well as deep learning for graphs to unearth rich knowledge. We expect novel research works that address various aspects and challenges around this topic, including learning representation for large-scale and dynamic networks, heterogeneous network embedding, scalable and efficient algorithms for other structured data embedding, deep learning methodologies for graph-structured data, novel platforms and applications supporting structured data embeddings, and beyond. We hope this dedicated workshop will foster further research discussions and development in this field.

Following up the success of the subsequent events at WWW2015, WWW2016, WWW2017 and WWW2018, the 5th AW4City 2019 aims to keep on attracting a significant international attention with regard to web applications for smart cities. This year, AW4City emphasizes on the contribution of web applications and Apps to urban mobility. In the era of cities and under the UN 2030 Agenda for sustainable growth, cities are making an important shift regarding thinking of compact cities and they develop sustainable mobility plans.

The primary objective of this full-day workshop is to bring together a latent community of researchers who treat disagreement (and subjectivity and ambiguity) as signal, rather than noise. Such researchers use theoretical and empirical methodology to characterize, utilize, mitigate and derive value from subjectivity, ambiguity and disagreement (see section Background for more in-depth analysis of related work). The workshop will include invited talks, short technical talks and a discussion of medium- and long-term challenges to fuel future work. A central goal for this second workshop edition is to begin to collect data and establish challenges for productively using data sets that exhibit disagreement using both existing methods as well as ideas put forward at the workshop.

The web provides a valuable space for individuals to interact with each other, and read, publish and share content. However, in recent times, it has also become a breeding ground for online misbehavior, including fraudulent engagement, user deception and scams, harassment, hate speech, cyberthreats, and cyberbullying. Thus, the aim of CybersSafety 2019 work is to improve cybersafety and build a better, safer, and more inclusive web and social media ecosystem for everyone. The workshop provides an interdisciplinary venue for researchers and practitioners to showcase pioneering research, demos, and tools that can improve the way in which cybersafety is done currently. Join us for a day filled with presentations, posters, panels, and demos!

Knowledge Graphs are graph structures that capture knowledge in the form of entities and the relationships between them, and optionally the provenance information. Along with Semantic Web standards such as RDF, OWL, and SPARQL, advances in Machine Learning, Deep Learning, Natural Language Processing, and Information Retrieval has led to automated construction of knowledge graphs such as DBpedia, YAGO, Wikidata, Google’s and LinkedIn’s Knowledge Graph, Microsoft’s Satori, and Product Knowledge Graph from Amazon and eBay. Knowledge Graphs are used in several applications such as search, question answering, data integration, recommendation systems etc., across several domains such as healthcare, geosciences, manufacturing, aviation, power, oil and gas. There are several challenges related to knowledge graphs from the perspective of both the technology and its applications. This workshop aims to foster discussions along these perspectives.

Human-in-the-loop is a model of interaction where a machine process and one or more humans have an iterative interaction. Computers are fast and accurate in processing vast amounts of data, people are creative and bring in their perspectives. Bringing humans and machines together creates a natural symbiosis for accurate interpretation of data. The goal of this workshop is to bring together researchers and practitioners in various areas of AI (i.e., Machine Learning, NLP, Computational Advertising, etc.) to explore new pathways of the human-in-the-loop paradigm to address some of the current concerns in AI, such as being able to explain and understand the results as well as avoiding bias in the underlying data that might lead to unfair or unethical conclusions.

The workshop aims to bring together researchers and practitioners from two research domains - mechanism design and machine learning - whose fields interact billions of times per day in practice but that are still, for the most part, keeping separate in the academic arena. The workshop will focus on motivating, promoting and disseminating interdisciplinary research combining these fields. Specifically, the workshop will tackle topics at the interaction of the two fields, including the increasing use of data and machine learning in designing mechanisms in broad contexts (e.g., mechanisms based on sampled past data) as well as the use of mechanism design techniques in machine learning (e.g., learning in a strategic setting).

The Third Workshop on Women in Web Data Science brings together female faculty, graduate students, research scientists, and industry researchers for an opportunity to connect, exchange ideas, and learn from each other in the field of Data Science. Underrepresented minorities, graduates, and undergraduates interested in pursuing data science, machine learning research are encouraged to participate. While most presenters should be women, everybody is invited to attend.

Hypermedia is increasingly used in Web service design, particularly in Linked Data and Web of Things systems where the use of static service contracts is not practical. This evolution raises new challenges: to discover, consume, and integrate hypermedia services at runtime, clients have to become increasingly autonomous in pursuit of their design goals. Such autonomous systems have been studied to a large extent in research on multi-agent systems (MAS). To consolidate the evolution of hypermedia services, it is now necessary to have comprehensive discussions on integrating hypermedia systems and MAS. We invite researchers and practitioners to design, build, evaluate, and share their vision on what the future of a hypermedia-driven Web for both people and autonomous agents will be.

LocWeb 2019 lies at the intersection of location-based services and Web architecture. It focuses on Web-scale services and systems facilitating location-aware information access as well as on Spatial Social Behavior Analytics on the Web as part of social computing. LocWeb addresses location as a cross-cutting issue in web research and technology that connects the online world to the physical spatial world. Subtopics include (i) geospatial semantics, systems, and standards; (ii) large-scale geospatial and geo-social ecosystems; (iii) mobility; (iv) location in the Web of Things; and (v) mining and searching geospatial data on the Web. The workshop encourages work describing Web-mediated or Web-scale approaches, and that thoroughly understand and embrace the geospatial dimension.

The Search-Oriented Conversational AI workshop brings together researchers and practitioners from NLP, AI/Deep Learning, and the search/IR communities to lay the ground for search-oriented conversational AI and establish future directions and collaborations. The focus of the third edition seeks to broaden participation between research and industry communities. The workshop features a strong program of invited talks from leaders in the field.

TempWeb focuses on investigating infrastructures, scalable methods, and innovative software for aggregating, querying, and analyzing heterogeneous data at Internet scale. Emphasis will be given to temporal data analysis along the time dimension for web data that has been collected over extended time periods. A major challenge in this regard is the sheer size of the data it exposes and the ability to make sense of it in a useful and meaningful manner for its users. On the Web, to a large extent, we have also reached this point. Web scale data analytics therefore needs to develop infrastructures and extended analytical tools to make sense of these.

The goal of this workshop is to bring together researchers exploring all aspects of Wikimedia websites such as Wikipedia, Wikidata, and Wikimedia Commons. With members of the Wikimedia Foundation’s Research team in the organizing committee and with the experience of successful workshops in 2015 (at ICWSM), 2016 (at WWW and ICWSM), 2017 (at WWW) and 2018 (at TheWebConf), we aim to continue facilitating a direct pathway for exchanging ideas between the organization that operates Wikimedia websites and the researchers interested in studying them.

From climate change to growing inequality, geopolitical upheaval and migrations, the challenges confronting our society are unprecedented, not only in their variety but also in their complexity. Data science and non-traditional data sources are becoming increasingly important to address these challenges and to unlock new opportunities in social innovation, philanthropy, international development and humanitarian aid. Data generated and collected by Web-based systems and communities can inform new models and support global agencies and policy makers to better identify needs, design interventions and evaluate impact. This workshop will showcase innovative contributions in the emerging field of data science for social good, and it will highlight the public interest value of new partnerships for the data age.

LA-WEB 2019 is the 10th of a series of refereed international conferences that aim to provide a venue to present, demonstrate and discuss the latest advancements in Web research that involves the Latin American Web community in its broadest sense. LA-WEB offers a great venue to show exciting new work that is mature (full papers) and work that is at an early stage and can benefit from discussion with colleagues (short papers). In this edition, LA-WEB will be co-located with The Web Conference 2019. We expect that this creates an opportunity for a synergetic atmosphere between the Latin American community and the global community of leading web researchers.

In an age where multiple apps, advertisements and an abundance of social media are vying to get the user’s attention, attention has become an extremely scarce resource. Never before has the need to understand attention economy been more acute. To raise the community's awareness on this issue, we present a unique, multi-disciplinary workshop that brings together experts offering diverse perspectives on attention. Starting with lessons from 4+ decades of work in Neuroscience / Cognitive Psychology on the science of attention, we will discuss advances in methods for studying attention on the web at scale and across devices, followed by applications of attention across domains ranging from information satisfaction for search/browse experiences on the web; measuring the effectiveness of advertising and web design; helping users with accessibility issues (e.g., ALS patients); to matters of current societal relevance such as designing improved measures and outcomes for digital wellbeing. We believe this workshop will spearhead new research initiatives towards better use of attention for digital wellbeing on the web and apps.
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Our society is struggling with an unprecedented amount of falsehood which harms wealth, democracy, and health. Debunking misinformation calls for interdisciplinary advancements in multiple social science areas, in addition to computer science. The last few years have witnessed a substantial growth in efforts at data-driven, AI-powered fact-checking. These efforts tackle various fronts, such as the detection of fabricated news, rumors, and spam, automation in fact-checking, flagging clickbait, and discovering fake accounts and malicious social media bots. This workshop aims at bringing together researchers, practitioners, and educators in the aforementioned areas to explore the ongoing challenges, solutions, ethics, and educational approaches in this context, with an emphasis on studies using computational and data-driven methodology.

The workshop on Linked Data on the Web and its Relationship to Distributed Ledgers (LDOW/LDDL) aims to stimulate discussion and further research into the challenges of publishing, consuming, and integrating structured data from the Web, covering established topics of the Linked Data on the Web (LDOW) community. As this year’s edition represents the coming together of the established Workshop on Linked Data On the Web (LDOW) with the Workshop on Linked Data and Distributed Ledgers (LDDL), we'll additionally address the question of how distributed ledgers could help towards solving some of these challenges, and how Linked Data technologies may help distributed ledgers to become more open and interoperable.

Can we build inclusive and representative machine-learning based-algorithms? Who is responsible for harm when algorithmic decision-making results in discriminatory outcomes? To whom should algorithms be transparent? What approaches to ethics might algorithms require? The FATES on the Web 2019 (Fairness, Accountability, Transparency, Ethics, and Society on the Web) is the first edition of a workshop to bring together researchers and enthusiasts concerned with the urgent challenges concerning algorithmic fairness and accountability, transparency, and ethics on data management and social interaction on the Web.

NLP and IR have been powering e-commerce applications since the early days of the fields. Today, NLP and IR already play a significant role in e-commerce tasks, including product search, recommender systems, product question answering, sentiment analysis, product description and review summarization, and customer review processing, amongst many other tasks. With the exploding popularity of chatbots and shopping assistants – both text- and voice-based – NLP, IR, question answering, and dialogue systems research is poised to transform e-commerce once again, but requires a forum where new and unfinished ideas could be discussed. The ECNLP workshop aims to provide a venue for the dissemination of late-breaking research results and ideas related to e-commerce and online shopping, bringing together researchers from both academia and industry.

There is a vast and rapidly increasing quantity of data published on the emerging Data Web. Knowledge graphs have emerged as scalable knowledge models for integrating data collected from heterogeneous and dynamic data sources. The workshop targets one of the emerging and fundamental problems in the Web, specifically the management and preservation of evolving knowledge graphs. This topic is of particular relevance to The Web Conference since it raises awareness of the many research challenges for preserving and managing knowledge graphs that evolve over time. Fostering active usage of such evolving knowledge graphs requires further research advances on topics such as storage, synchronisation, change representation and querying. Solutions to these problems correspond to main subjects of interests of the workshop.