WORKSHOP REPORTDiversiWeb 2011
Elena Simperl
KIT
Karlsruhe, Germany
elena.simperl@kit.edu

Devika P. Madalli
Indian Statistical InstituteBangalore, India
devika@drtc.isibang.ac.in

Denny Vrandečić
KIT
Karlsruhe, Germany
denny.vrandecic@kit.edu

Enrique Alfonseca
GoogleZurich, Switzerland
ealfonseca@google.com

Abstract
DiversiWeb 2011, the First International Workshop on Knowledge Diversity on the Web,
co-located with WWW2011 in Hyderabad, India, provided an interdisciplinary forum forresearchers and practitioners to present and discuss their ideas related to the challenges
posed by diversity on the Web. We addressed a wide array of interdisciplinary questions,which need to be tackled in order to preserve the fragile balance between a world that iscontinually converging and growing together, the rich diversity of the global society, and thedangers of fragmentation and splintering.

1Introduction

Almost 20 years after its introduction, the Web provides a platform for the publication, useand exchange of information, at planetary scale, on virtually every topic, and representing
an amazing diversity of opinions, viewpoints, mindsets and backgrounds. The success of theWeb can be attributed to several factors, most notably to its principled scalable design, butalso to a number of subsequent ICT developments such as smart user-generated content,
mobile devices, and most recently cloud computing.
The first two of these have dramatically lowered the last barriers of entry when it comes toproducing and consuming information online, leading to an unprecedented growth and masscollaboration. They are responsible for hundreds of millions of users all over the globe creating high-quality encyclopedias, publishing Terabytes of multimedia content, contributing
to world-class software, and lively taking part in defining the agenda of many aspects of oursociety by raising their voices, and publicly expressing and sharing their ideas, viewpoints,and resources.
The other side of the coin in this unique success story is, nevertheless, the great challenges
associated with managing the sheer amounts of information continuously being publishedonline, whilst allowing for purposeful use, and leveraging the diversity inherently unfolding
through global-scale collaboration. In this context, diversity includes different opinions,sentiments, preferences, or worldviews that are reflected in the way information is expressedon the Web. These challenges are still to be solved at many levels, from the infrastructure
to store and access the information, through the methods and techniques to make sense outof it, to the paradigms underlying the processes of Web-based information provision andconsumption.
As an example, when searching for blog posts, state-of-the-art technology – be that
popularity-based algorithms, recommendation engines or collaborative filters – tends to return either the most popular posts, or those which correspond with a personal profile andtherefore with the known opinions and tastes of the reader. Alternative points of view, andnew unexpected content, are not taken into account as they are not highly ranked, and posts
expressing different opinions are sometimes even discarded.
This behavior has particularly negative consequences when dealing with information thatis expected and intended to be subject to diverse opinion – as is the case with news reports,
ratings of products or media content, customer reviews, or any other type of subjective
assessment. The same negative effects apply in a community-driven environment that isdesigned for collaboration – the most obvious example here being Wikipedia and the blogosphere. The information diversity exposed in such an environment, impressive both withrespect to scale and the richness of opinions and viewpoints expressed, cannot be handled
without adequate computer support in an economically feasible manner. In the long run,
maintaining the current state-of-affairs will change the ways and the extent to which people
are informed (or not) on a particular topic, tremendously influencing how they look into that
topic, what they find about it and what they think about it.
On top of all this, it is meanwhile acknowledged that the current state of affairs hampers
true collaboration. For example, Wikipedia is a tremendous success, but it is also a largely
meritocratic system with a decreasing number of active contributors, whereas the blogosphere has to deal with the limited attention of the blog authors. What is needed are novel
concepts, methods and tools that allow humans and machines to leverage the huge amounts
of information created by a community, based on interaction models that support expressing, communicating and reasoning about divergent models simultaneously. This would not
only enhance true collaboration, but would also significantly improve various aspects of theinformation management life cycle, thus addressing information overload in sectors which
rely on opinions-driven information sources and mass participation – news, ratings, reviews,
and social and information sharing portals of any kind.

2Goals of the workshop

The overall aim of this workshop was to provide an interdisciplinary forum for researchers andpractitioners to present and discuss their ideas related to the challenges posed by diversity on
the Web. We addressed a wide array of interdisciplinary questions, which need to be tackled
in order to preserve the fragile balance between a world that is continually converging andgrowing together, the rich diversity of the global society, and the dangers of fragmentation andsplintering. This includes but is not limited to questions such as ’How to model diversity?’,’How to discover bias and opinion in blog posts, tweets, forum items, wiki edits, etc.?’, ’How
to rank, aggregate, summarize, and exploit information in a diversity-aware manner?’, ’Whatare the applications of diversity-rich information sources?’, ’How can we use diversity as anasset instead of regarding it as a barrier?’.

3Topics

The list of topics mentioned in the call for papers was:
• Analyze the capabilities of current information management models, algorithms andtechnologies to leverage knowledge diversity,• Extend existing models, methods, techniques and tools to accommodate the requirements arising from paying a proper account to diversity-expressed information sources
and communication and collaboration environments characterized by a rich variety ofopinions and viewpoints.
• Discuss the foundations of knowledge diversity on the Web and propose alternative
paradigms,• Propose novel evaluation strategies, methods and techniques to assess the impact ofdiversity-minded information management.
Topics of the workshop include, but are not limited to:• Risks and advantages of diversity and diversification on the Web• Facets of knowledge diversity and conceptual and formal models for representing andunderstanding diversity• Discovery and mining of corpora for diversity-related information• Use of Natural Language Processing techniques for diversity mining• Classifying Web 2.0 content items such as blog posts, videos, tweets, and wiki-edits bytheir biases• Usage and benefits of diversity in the corporate context, e.g. in order to understandfeedback and communication with the customer• Enabling or improving communication and collaboration over barriers induced by diversity• Extensions to Web applications taking diversity into account• Exposing and explaining diversity to end users• User experiences avoiding the radicalization of groups by exposing them to alternatives• User interfaces allowing the explicit annotation of content with diversity markers• Studies on the acceptance by end-users of diversified applications.

4Papers

We selected the following six papers from the submissions, based on the recommendationsof the DiversiWeb programme committee.11

http://render-project.eu/diversiweb-2011/• Towards a Knowledge Diversity Model by Rakebul Hasan, Katharina Siorpaes,
Reto Krummenacher, and Fabian Flöck. Abstract: The Web is an unprecedented enabler for publishing, using and exchanging information at global scale. Virtually any
topic is covered by an amazing diversity of opinions, viewpoints, mind sets and backgrounds. The research project RENDER works on methods and techniques to leverage
diversity as a crucial source of innovation and creativity, and designs novel algorithms
that exploits diversity for ranking, aggregating and presenting Web content. Essential
in this respect is a knowledge model that makes accessible – cognitively to human users
as well as computationally to the machine – the diversity in content. In this paper, we
present a glossary of relevant terms that serves as baseline to the specification of theKnowledge Diversity Model.
• Expressing Opinion Diversity by Andreea Bizău, Delia Rusu, and Dunja Mladenić.
Abstract: The focus of this paper is describing a natural language processing methodology for identifying opinion diversity expressed within text. We achieve this by building
a domain-driven opinion vocabulary, in order to be able to identify domain specificwords and expressions. As a use case scenario, we consider Twitter comments related
to movies, and try to capture opinion diversity by employing an opinion vocabulary,which we generate based on a corpus of IMDb movie reviews.
• Scalable Detection of Sentiment-Based Contradictions by Mikalai Tsytsarau,Themis Palpanas, and Kerstin Denecke. Abstract: The analysis of user opinions expressed on the Web is becoming increasingly relevant to a variety of applications. It
allows us to track the evolution of opinions or discussions in the blogosphere, or perform product surveys. The aggregation of sentiments and analysis of contradictions isanother important application, which becomes effective since we are able to capture
the diversity in sentiments on different topics with more precision and on a large scale.
Though, there is still a need for a scalable way of sentiment aggregation with respect
to the time dimension, which preserves enough information to capture contradictions.
In this paper, we are focusing on the problem of finding sentiment-based contradictions
at a large scale. First, we define two types of contradictions, depending on the distributions of opposite sentiments over time. Second, we introduce a novel measure ofcontradiction based on the mean value and the variance of sentiments among different
texts. Third, we propose a scalable method for identifying both types of contradictions
at different time scales. We evaluate the performance of our method using synthetic
and real-world datasets, as well as a user-study. The experiments demonstrate theeffectiveness of the proposed method in capturing contradictions in a scalable manner.
• Faceted Approach To Diverse Query Processing by Alessandro Agostini, Devika
P. Madalli, and A. R. D. Prasad. Abstract: This paper presents a formal framework forimplementing a query refinement method. The method uses general principles of facet
analysis. Two key notions are advanced and discussed: diversity and focus. Diversity
refers to the information needs of a querying user; it is captured by the notion of facet.
A focus refers to how diversity is captured from the documents as organized by theuser; it provides a kind of context to the user query. The method is situated within theformal framework of the smallest propositionally closed description logic ALC, thereby
betting that ALC provides us with a suitable SAT solver to implement a facet engine,which is the main component of our method.
• Approximate subgraph matching for detection of topic variations by MitjaTrampuš, and Dunja Mladenić. Abstract: The paper presents an approach to detectionof topic variations based on approximate graph matching. Text items are represented
as semantic graphs and approximately matched based on a taxonomy of node and edgelabels. Best-matching subgraphs are used as a template against which to align andcompare the articles. The proposed approach is applied on news stories using WordNetas the predefined taxonomy. Illustrative experiments on real-world data show that theapproach is promising.
• Mining Diverse Views from Related Articles by Ravali Pochampally, and Kamalakar Karlapalem. Abstract: The world wide web allows for diverse articles to beavailable on a news event, product or any topic. It is not impossible to find a few hundred articles that discuss a specific topic thus making it difficult for a user to quickly
process the information. Summarization condenses huge volume of information related
to a topic but does not provide a delineation of the issues pertaining to it. We want
to extract the diverse issues pertaining to a topic by mining views from a collection ofarticles related to it. A view is a set of sentences, related in content, that address anissue relevant to a topic. We present a framework for extraction and ranking of views
and have conducted experiments to evaluate the framework.

5Video and paper proceedings

The proceedings of the workshop are available from the workshop website.2 Video recordingsof all talks as well as the slides of the talks are expected to be available by mid 2011 thanks
to courtesy of VideoLectures.net.3

6Acknowledgments

The workshop was partially funded by EU IST FP7 projects RENDER4 and Living Knowledge.5 We thank the program committee for the indispensable help in the selection process
for the workshop program, and VideoLectures.net for recording the workshop.

2

http://render-project.eu/diversiweb2011/
http://videolectures.net
4
http://render-project.eu
5
http://livingknowledge-project.eu/
3