OpenRaiser/Intern-Atlas huggingface dataset:
When relevance is not enough: promoting diversity and freshnessin personalized question recommendation
Authors: Idan Szpektor, Yoelle Maarek, Dan Pelleg
Venue: WWW
Year: 2013

What makes a good question recommendation system for community question-answering sites? First, to maintain the health of the ecosystem, it needs to be designed around answerers, rather than exclusively for askers. Next, it needs to scale to many questions and users, and be fast enough to route a newly-posted question to potential answerers within the few minutes before the asker's patience runs out. It also needs to show each answerer questions that are relevant to his or her interests. We have designed and built such a system for Yahoo! Answers, but realized, when testing it with live users, that it was not enough.
Towards integration of web data into a coherent educational data graph
Authors: Davide Taibi, Besnik Fetahu, Stefan Dietze
Venue: WWW
Year: 2013

Personalisation, adaptation and recommendation are central aims of Technology Enhanced Learning (TEL) environments. In this context, information retrieval and clustering techniques are more and more often applied to filter and deliver learning resources according to user preferences and requirements. However, the suitability and scope of possible recommendations is fundamentally dependent on the available data, such as metadata about learning resources as well as users. However, quantity and quality of both is still limited. On the other hand, throughout the last years, the Linked Data (LD) movement has succeeded to provide a vast body of well-interlinked and publicly accessible Web data. This in particular includes Linked Data of explicit or implicit educational nature. In this paper, we propose a large-scale educational dataset which has been generated by exploiting Linked Data methods together with clustering and interlinking techniques to extract import and interlink a wide range of educationally relevant data. We also introduce a set of reusable techniques which were developed to realise scalable integration and alignment of Web data in educational settings.
Groundhog day: near-duplicate detection on Twitter
Authors: Ke Tao, Fabian Abel, Claudia Hauff, Geert-Jan Houben, Ujwal Gadiraju
Venue: WWW
Year: 2013

With more than 340~million messages that are posted on Twitter every day, the amount of duplicate content as well as the demand for appropriate duplicate detection mechanisms is increasing tremendously. Yet there exists little research that aims at detecting near-duplicate content on microblogging platforms. We investigate the problem of near-duplicate detection on Twitter and introduce a framework that analyzes the tweets by comparing (i) syntactical characteristics, (ii) semantic similarity, and (iii) contextual information. Our framework provides different duplicate detection strategies that, among others, make use of external Web resources which are referenced from microposts. Machine learning is exploited in order to learn patterns that help identifying duplicate content. We put our duplicate detection framework into practice by integrating it into Twinder, a search engine for Twitter streams. An in-depth analysis shows that it allows Twinder to diversify search results and improve the quality of Twitter search. We conduct extensive experiments in which we (1) evaluate the quality of different strategies for detecting duplicates, (2) analyze the impact of various features on duplicate detection, (3) investigate the quality of strategies that classify to what exact level two microposts can be considered as duplicates and (4) optimize the process of identifying duplicate content on Twitter. Our results prove that semantic features which are extracted by our framework can boost the performance of detecting duplicates.
Does social contact matter?: modelling the hidden web of trust underlying twitter
Authors: Mozhgan Tavakolifard, Kevin C. Almeroth, Jon Atle Gulla
Venue: WWW
Year: 2013

Social recommender systems aim to alleviate the information overload problem on social network sites. The social network structure is often an important input to these recommender systems. Typically, this structure cannot be inferred directly from declared relationships among users. The goal of our work is to extract an underlying hidden and sparse network which more strongly represents the actual interactions among users. We study how to leverage Twitter activities like micro-blogging and the network structure to find a simple, efficient, but accurate method to infer and expand this hidden network. We measure and compare the performance of several different modeling strategies using a crawled data set from Twitter. Our results reveal that the structural similarity in the network generated by users' retweeting behavior outweighs the other discussed methods.
Framework for evaluation of text captchas
Authors: Achint Thomas, Kunal Punera, Lyndon Kennedy, Belle L. Tseng, Yi Chang
Venue: WWW
Year: 2013

Interactive websites use text-based Captchas to prevent unauthorized automated interactions. These Captchas must be easy for humans to decipher while being difficult to crack by automated means. In this work we present a framework for the systematic study of Captchas along these two competing objectives. We begin by abstracting a set of distortions that characterize current and past commercial text-based Captchas. By means of user studies, we quantify the way human Captcha solving performance varies with changes in these distortion parameters. To quantify the effect of these distortions on the accuracy of automated solvers (bots), we propose a learning-based algorithm that performs automated Captcha segmentation driven by character recognition. Results show that our proposed algorithm is generic enough to solve text-based Captchas with widely varying distortions without requiring the use of hand-coded image processing or heuristic rules.
Uncovering locally characterizing regions within geotagged data
Authors: Bart Thomee, Adam Rae
Venue: WWW
Year: 2013

We propose a novel algorithm for uncovering the colloquial boundaries of locally characterizing regions present in collections of labeled geospatial data. We address the problem by first modeling the data using scale-space theory, allowing us to represent it simultaneously across different scales as a family of increasingly smoothed density distributions. We then derive region boundaries by applying localized label weighting and image processing techniques to the scale-space representation of each label. Important insights into the data can be acquired by visualizing the shape and size of the resulting boundaries for each label at multiple scales. We demonstrate our technique operating at scale by discovering the boundaries of the most geospatially salient tags associated with a large collection of georeferenced photos from Flickr and compare our characterizing regions that emerge from the data with those produced by a recent technique from the research literature.
The HTP model: understanding the development of social machines
Authors: Ramine Tinati, Leslie Carr, Susan Halford, Catherine Pope
Venue: WWW
Year: 2013

The Web represents a collection of socio-technical activities inter-operating using a set of common protocols and standards. Online banking, web TV, internet shopping, e-government and social networking are all different kinds of human interaction that have recently leveraged the capabilities of the Web architecture. Activities that have human and computer components are referred to as social machines. This paper introduces HTP, a socio-technical model to understand, describe and analyze the formation and development of social machines and other web activities. HTP comprises three components: heterogeneous networks of actors involved in a social machine; the iterative process of translation of the actors' activities into a temporarily stable and sustainable social machine; and the different phases of this machine's adaptation from one stable state to another as the surrounding networks restructure and global agendas ebb and flow. The HTP components are drawn from an interdisciplinary range of theoretical positions and concepts. HTP provides an analytical framework to explain why different Web activities remain stable and functional, whilst others fail. We illustrate the use of HTP by examining the formation of a classic social machine (Wikipedia), and the stabilization points corresponding to its different phases of development.
An approach for using Wikipedia to measure the flow of trends across countries
Authors: Ramine Tinati, Thanassis Tiropanis, Leslie Carr
Venue: WWW
Year: 2013

Wikipedia has grown to become the most successful online encyclopedia on the Web, containing over 24 million articles, offered in over 240 languages. In just over 10 years Wikipedia has transformed from being just an encyclopedia of knowledge, to a wealth of facts and information, from articles discussing trivia, political issues, geographies and demographics, to popular culture, news articles, and social events. In this paper we explore the use of Wikipedia for identifying the flow of information and trends across the world. We start with the hypothesis that, given that Wikipedia is a resource that is globally available in different languages across countries, access to its articles could be a reflection human activity. To explore this hypothesis we try to establish metrics on the use of Wikipedia in order to identify potential trends and to establish whether or how those trends flow from one county to another. We subsequently compare the outcome of this analysis to that of more established methods that are based on online social media or traditional media. We explore this hypothesis by applying our approach to a subset of Wikipedia articles and also a specific worldwide social phenomenon that occurred during 2012; we investigate whether access to relevant Wikipedia articles correlates to the viral success of the South Korean pop song, "Gangnam Style" and the associated artist "PSY" as evidenced by traditional and online social media. Our analysis demonstrates that Wikipedia can indeed provide a useful measure for detecting social trends and events, and in the case that we studied; it could have been possible to identify the specific trend quicker in comparison to other established trend identification services such as Google Trends.
Large-scale social recommender systems: challenges and opportunities
Authors: Mitul Tiwari
Venue: WWW
Year: 2013

Online social networks have become very important for networking, communication, sharing, and content discovery. Recommender systems play a significant role on any online social network for engaging members, recruiting new members, and recommending other members to connect with. This talk presents challenges in recommender systems, graph analysis, social stream relevance and virality on a large-scale social networks such as LinkedIn, the largest professional network with more than 200M members.
Information sharing on Twitter during the 2011 catastrophic earthquake
Authors: Fujio Toriumi, Takeshi Sakaki, Kousuke Shinoda, Kazuhiro Kazama, Satoshi Kurihara, Itsuki Noda
Venue: WWW
Year: 2013

Such large disasters as earthquakes and hurricanes are very unpredictable. During a disaster, we must collect information to save lives. However, in time disaster, it is difficult to collect information which is useful for ourselves from such traditional mass media as TV and newspapers that contain information for the general public. Social media attract attention for sharing information, especially Twitter, which is a hugely popular social medium that is now being used during disasters. In this paper, we focus on the information sharing behaviors on Twitter during disasters. We collected data before and during the Great East Japan Earthquake and arrived at the following conclusions:
Structured summarization for news events
Authors: Giang Binh Tran
Venue: WWW
Year: 2013

Helping users to understand the news is an acute problem nowadays as the users are struggling to keep up with tremendous amount of information published every day in the Internet. In this research, we focus on modelling the content of news events by their semantic relations with other events, and generating structured summarization.
A glance at an overlooked part of the world wide web
Authors: Ionut Trestian, Chunjing Xiao, Aleksandar Kuzmanovic
Venue: WWW
Year: 2013

Although according to surveys related to internet user activity it is considered one of the most popular aspects, few studies are actually concerned with internet pornography. This paper is aimed at rectifying that overlook. In particular, we study user activity related to internet pornography by looking at two main behaviors: (i) watching pornography, and (ii) providing feedback on pornography items in the form of ratings and comments.
ASQ: interactive web presentations for hybrid MOOCs
Authors: Vasileios Triglianos, Cesare Pautasso
Venue: WWW
Year: 2013

ASQ is a Web application for creating and delivering interactive HTML5 presentations. It is designed to support teachers that need to gather real-time feedback from the students while delivering their lectures. Presentation slides are delivered to viewers that can answer the questions embedded in the slides. The objective is to maximize the efficiency of bi-directional communication between the lecturer and a large audience. More specifically, in the context of a hybrid MOOC classroom, a teacher can use ASQ to get feedback in real time about the level of comprehension of the presented material while reducing the time for gathering survey data, monitoring attendance and assessing solutions.
New features for query dependent sponsored search click prediction
Authors: Ilya Trofimov
Venue: WWW
Year: 2013

Click prediction for sponsored search is an important problem for commercial search engines. Good click prediction algorithm greatly affects on the revenue of the search engine, user experience and brings more clicks to landing pages of advertisers. This paper presents new query-dependent features for the click prediction algorithm based on treating query and advertisement as bags of words. New features can improve prediction accuracy both for ads having many and few views.
MediaFinder: collect, enrich and visualize media memes shared by the crowd
Authors: Raphaël Troncy, Vuk Milicic, Giuseppe Rizzo, José Luis Redondo García
Venue: WWW
Year: 2013

Social networks play an increasingly important role for sharing media items related to human's activities, feelings, emotions and conversations opening a window to the world in real-time. However, these images and videos are spread over multiple social networks. In this paper, we first describe a so-called media server that collect recent images and videos which can be potentially attached to an event. These media items can then be used for the automatic generation of visual summaries. However, making sense out of the resulting media galleries is an extremely challenging task. We present a framework that leverages on: (i) visual features from media items for near-deduplication and (ii) textual features from status updates to enrich, cluster and generate storyboards. A prototype is publicly available at http://mediafinder.eurecom.fr.
Scaling graph computations at facebook
Authors: Johan Ugander
Venue: WWW
Year: 2013

With over a billion nodes and hundreds of billions of edges, scalability is at the forefront of concerns when dealing with the Facebook social graph. This talk will focus on two recent advances in graph computations at Facebook. The first focus concerns the development of a novel graph sharding algorithm - Balanced Label Propagation - for load-balancing distributed graph computations. Using Balanced Label Propagation, we were able to reduce by 50% the query time of Facebook's 'People You May Know' service, the realtime distributed system responsible for the feature extraction and ranking of the friends-of-friends of all active Facebook users. The second focus concerns the 2011 computation of the average distance distribution between all active Facebook users. This computation, which produced an average distance of 4.74, was made possible by two recent computational advances: Hyper-ANF, a modern probabilistic algorithm for computing distance distributions, and Layered Label Propagation, a modern compression scheme suited for social graphs. The details of how this computation was coordinated will be described. The talk describes joint work with Lars Backstrom, Paolo Boldi, Marco Rosa, and Sebastiano Vigna.
The ACE theorem for querying the web of data
Authors: Jürgen Umbrich, Claudio Gutierrez, Aidan Hogan, Marcel Karnstedt, Josiane Xavier Parreira
Venue: WWW
Year: 2013

Inspired by the CAP theorem, we identify three desirable properties when querying the Web of Data: Alignment (results up-to-date with sources), Coverage (results covering available remote sources), and Efficiency (bounded resources). In this short paper, we show that no system querying the Web can meet all three ACE properties, but instead must make practical trade-offs that we outline.
Nerding out on twitter: fun, patriotism and #curiosity
Authors: Victoria S. Uren, Aba-Sah Dadzie
Venue: WWW
Year: 2013

This paper presents an analysis of tweets collected over six days before, during and after the landing of the Mars Science Laboratory, known as Curiosity, in the Gale Crater on the 6th of August 2012. A sociological application of web science is demonstrated by use of parallel coordinate visualization as part of a mixed methods study. The results show strong, predominantly positive, international interest in the event. Scientific details dominated the stream, but, following the successful landing, other themes emerged such as fun, and national pride.
A case-based analysis of the effect of offline media on online conversion actions
Authors: Damir Vandic, Didier Nibbering, Flavius Frasincar
Venue: WWW
Year: 2013

In this paper, we investigate how offline advertising, by means of TV and radio, influences online search engine advertisement. Our research is based on the search engine-driven conversion actions of a 2012 marketing campaign of the potato chips manufacturer Lays. In our analysis we use several models, including linear regression (linear model) and Support Vector Regression (non-linear model). Our results confirm that offline commercials have a positive effect on the number of conversion actions from online marketing campaigns. This effect is especially visible in the first 50 minutes after the advertisement broadcasting.
Examining lists on Twitter to uncover relationships between following, membership and subscription
Authors: Srikar Velichety, Sudha Ram
Venue: WWW
Year: 2013

We report on an exploratory analysis of pairwise relationships between three different forms of information consumption on Twitter viz., following, listing and subscribing. We develop a systematic framework to examine the relationships between these three forms. Using our framework, we conducted an empirical analysis of a dataset from Twitter. Our results show that people not only consume information by explicitly following others, but also by listing and subscribing to lists and that the people they list or subscribe to are not the same as the ones they follow. Our work has implications for understanding information propagation and diffusion via Twitter and for generating recommendations for adding users to lists, subscribing and merging or splitting them.
Discovery of technical expertise from open source code repositories
Authors: Rahul Venkataramani, Atul Gupta, Allahbaksh M. Asadullah, Basavaraju Muddu, Vasudev D. Bhat
Venue: WWW
Year: 2013

Online Question and Answer websites for developers have emerged as the main forums for interaction during the software development process. The veracity of an answer in such websites is typically verified by the number of 'upvotes' that the answer garners from peer programmers using the same forum. Although this mechanism has proved to be extremely successful in rating the usefulness of the answers, it does not lend itself very elegantly to model the expertise of a user in a particular domain. In this paper, we propose a model to rank the expertise of the developers in a target domain by mining their activity in different opensource projects. To demonstrate the validity of the model, we built a recommendation system for StackOverflow which uses the data mined from GitHub.
Graph-based malware distributors detection
Authors: Andrei Venzhega, Polina Zhinalieva, Nikolay Suboch
Venue: WWW
Year: 2013

Search engines are currently facing a problem of websites that distribute malware. In this paper we present a novel efficient algorithm that learns to detect such kind of spam. We have used a bipartite graph with two types of nodes, each representing a layer in the graph: web-sites and file hostings (FH), connected with edges representing the fact that a file can be downloaded from the hosting via a link on the web-site. The performance of this spam detection method was verified using two set of ground truth labels: manual assessments of antivirus analysts and automatically generated assessments obtained from antivirus companies. We demonstrate that the proposed method is able to detect new types of malware even before the best known antivirus solutions are able to detect them.
Distributed affordance: an open-world assumption for hypermedia
Authors: Ruben Verborgh, Michael Hausenblas, Thomas Steiner, Erik Mannens, Rik Van de Walle
Venue: WWW
Year: 2013

Hypermedia links and controls drive the Web by transforming information into affordances through which users can choose actions. However, publishers of information cannot predict all actions their users might want to perform and therefore, hypermedia can only serve as the engine of application state to the extent the user's intentions align with those envisioned by the publisher. In this paper, we introduce distributed affordance, a concept and architecture that extends application state to the entire Web. It combines information inside the representation with knowledge of action providers to generate affordance from the user's perspective. Unlike similar approaches such as Web Intents, distributed affordance scales both in the number of actions and the number of action providers, because it is resource-oriented instead of action-oriented. A proof-of-concept shows that distributed affordance is a feasible strategy on today's Web.
Serefind: a social networking website for classifieds
Authors: Pramod Verma
Venue: WWW
Year: 2013

This paper presents the design and implementation of a social networking website for classifieds, called Serefind. We designed search interfaces with focus on security, privacy, usability, design, ranking, and communications. We deployed this site at the Johns Hopkins University, and the results show it can be used as a self-sustaining classifieds site for public or private communities.
Google+Ripples: a native visualization of information flow
Authors: Fernanda B. Viégas, Martin Wattenberg, Jack Hebert, Geoffrey Borggaard, Alison Cichowlas, Jonathan Feinberg, Jon Orwant, Christopher Richard Wren
Venue: WWW
Year: 2013

G+ Ripples is a visualization of information flow that shows users how public posts are shared on Google+. Unlike other social network visualizations, Ripples exists as a "native" visualization: it is directly accessible from public posts on Google+. This unique position leads to both new constraints and new possibilities for design. We describe the visualization technique, which is a new mix of node-and-link and circular treemap metaphors. We then describe user reactions as well as some of the patterns of sharing that are made evident by the Ripples visualization.