OpenRaiser/Intern-Atlas huggingface dataset:
Online social networks: beyond popularity
Authors: Ricardo Baeza-Yates, Diego Sáez-Trumper
Venue: WWW
Year: 2013

One of the main differences between traditional Web analysis and online Social Networks (OSNs) studies, is that in the first case the information is organized around content, while in the second case it is organized around people. While search engines have done a good job finding relevant content across billions of pages, nowadays we do not have an equivalent tool to find relevant people in OSNs. Even though an impressive amount of research has been done in this direction, there are still a lot of gaps to cover. Although the first intuition could be (and was!) search for popular people, previous research have shown that users' in-degree (e.g. number of friends or followers) is important but not enough to represent the importance and reputation of a person. Another approach is to study the content of the messages exchanged between users, trying to identify topical experts. However the computational cost of such approach - including language diversity - is a big limitation. In our work we take a content-agnostic approach, focusing in frequency, type, and time properties of user actions rather than content, mixing their static characteristics (social graph) and their activities (dynamic graphs). Our goal is to understand the role of popular users in OSNs, and also find "hidden important users": do popular users create new trends and cascades? Do they add value to the network? And, if they don't, who does it? Our research provides preliminary answers for these questions.
G-path: flexible path pattern query on large graphs
Authors: Yiyuan Bai, Chaokun Wang, Yuanchi Ning, Hanzhao Wu, Hao Wang
Venue: WWW
Year: 2013

With the socialization trend of web sites and applications, the techniques of effective management of graph-structured data have become one of the most important modern web technologies. In this paper, we present a system of path query on large graphs, known as G-Path. Based on Hadoop distributed framework and bulk synchronized parallel model, the system can process generic queries without preprocessing or building indices. To demonstrate the system, we developed a web-based application which allows searching entities and relationships on a large social network, e.g., DBLP publication network or Twitter dataset. With the flexibility of G-Path, the application is able to handle different kinds of queries. For example, a user may want to search for a publication graph of an author while another user may want to search for all publications of the author's co-authors. All these queries can be done by an interactive user interface and the results will be shown in a visual graph.
Client-server web applications widgets
Authors: Vincent Balat
Venue: WWW
Year: 2013

The evolution of the Web from a content platform into an application platform has raised many new issues for developers. One of the most significant is that we are now developing distributed applications, in the specific context of the underlying Web technologies. In particular, one should be able to compute some parts of the page either on server or client sides, depending on the needs of developers, and preferably in the same language, with the same functions. This paper deals with the particular problem of user interface generation in this client-server setting. Many widget libraries for browsers are fully written in JavaScript and do not allow to generate the interface on server side, making more difficult the indexing of pages by search engines. We propose a solution that makes possible to generate widgets either on client side or on server side in a very flexible way. It is implemented in the Ocsigen framework.
Towards highly scalable pregel-based graph processing platform with x10
Authors: Nguyen Thien Bao, Toyotaro Suzumura
Venue: WWW
Year: 2013

Many practical computing problems concern large graph. Standard problems include web graph analysis and social networks analysis like Facebook, Twitter. The scale of these graph poses challenge to their efficient processing. To efficiently process large-scale graph, we create X-Pregel, a graph processing system based on Google's Computing Pregel model [1], by using the state-of-the-art PGAS programming language X10. We do not purely implement Google Pregel by using X10 language, but we also introduce two new features that do not exists in the original model to optimize the performance: (1) an optimization to reduce the number of messages which is exchanged among workers, (2) a dynamic re-partitioning scheme that effectively reassign vertices to different workers during the computation. Our performance evaluation demonstrates that our optimization method of sending messages achieves up to 200% speed up on Pagerank by reducing the network I/O to 10 times in comparison with the default method of sending messages when processing SCALE20 Kronecker graph [2](vertices = 1,048,576, edges = 33,554,432). It also demonstrates that our system processes large graph faster than prior implementation of Pregel such as GPS [3](stands for graph processing system) and Giraph [4].
Popularity prediction in microblogging network: a case study on sina weibo
Authors: Peng Bao, Huawei Shen, Junming Huang, Xueqi Cheng
Venue: WWW
Year: 2013

Predicting the popularity of content is important for both the host and users of social media sites. The challenge of this problem comes from the inequality of the popularity of content. Existing methods for popularity prediction are mainly based on the quality of content, the interface of social media site to highlight contents, and the collective behavior of users. However, little attention is paid to the structural characteristics of the networks spanned by early adopters, i.e., the users who view or forward the content in the early stage of content dissemination. In this paper, taking the Sina Weibo as a case, we empirically study whether structural characteristics can provide clues for the popularity of short messages. We find that the popularity of content is well reflected by the structural diversity of the early adopters. Experimental results demonstrate that the prediction accuracy is significantly improved by incorporating the factor of structural diversity into existing methods.
Dynamic evaluation of online display advertising with randomized experiments: an aggregated approach
Authors: Joel Barajas, Ram Akella, Marius Holtan, Jaimie Kwon, Aaron Flores, Victor Andrei
Venue: WWW
Year: 2013

We perform a randomized experiment to estimate the effects of a display advertising campaign on online user conversions. We present a time series approach using Dynamic Linear Models to decompose the daily aggregated conversions into seasonal and trend components. We attribute the difference between control and study trends to the campaign. We test the method using two real campaigns run for 28 and 21 days respectively from the Advertising.com ad network.
A large-scale, longitudinal study of user profiles in world of warcraft
Authors: Jonathan Bell, Swapneel Sheth, Gail E. Kaiser
Venue: WWW
Year: 2013

We present a survey of usage of the popular Massively Multiplayer Online Role Playing Game, World of Warcraft. Players within this game often self-organize into communities with similar interests and/or styles of play. By mining publicly available data, we collected a dataset consisting of the complete player history for approximately six million characters, with partial data for another six million characters. The paper provides a thorough description of the distributed approach used to collect this massive community data set, and then focuses on an analysis of player achievement data in particular, exposing trends in play from this highly successful game. From this data, we present several findings regarding player profiles. We correlate achievements with motivations based upon a previously-defined motivation model, and then classify players based on the categories of achievements that they pursued. Experiments show players who fall within each of these buckets can play differently, and that as players progress through game content, their play style evolves as well.
Cascading tree sheets and recombinant HTML: better encapsulation and retargeting of web content
Authors: Edward Benson, David R. Karger
Venue: WWW
Year: 2013

Cascading Style Sheets (CSS) took a valuable step towards separating web content from presentation. But HTML pages still contain large amounts of "design scaffolding" needed to hierarchically layer content for proper presentation. This paper presents Cascading Tree Sheets (CTS), a CSS-like language for separating this presentational HTML from real content. With CTS, authors can use standard CSS selectors to describe how to graft presentational scaffolding onto their pure-content HTML. This improved separation of content from presentation enables even naive authors to incorporate rich layouts (including interactive Javascript) into their own pages simply by linking to a tree sheet and adding some class names to their HTML.
Inside YAGO2s: a transparent information extraction architecture
Authors: Joanna Biega, Erdal Kuzey, Fabian M. Suchanek
Venue: WWW
Year: 2013

YAGO [9, 6] is one of the largest public ontologies constructed by information extraction. In a recent refactoring called YAGO2s, the system has been given a modular and completely transparent architecture. In this demo, users can see how more than 30 individual modules of YAGO work in parallel to extract facts, to check facts for their correctness, to deduce facts, and to merge facts from different sources. A GUI allows users to play with different input files, to trace the provenance of individual facts to their sources, to change deduction rules, and to run individual extractors. Users can see step by step how the extractors work together to combine the individual facts to the coherent whole of the YAGO ontology.
Towards leveraging closed captions for news retrieval
Authors: Roi Blanco, Gianmarco De Francisci Morales, Fabrizio Silvestri
Venue: WWW
Year: 2013

IntoNow from Yahoo! is a second screen application that enhances the way of watching TV programs. The application uses audio from the TV set to recognize the program being watched, and provides several services for different use cases. For instance, while watching a football game on TV it can show statistics about the teams playing, or show the title of the song performed by a contestant in a talent show. The additional content provided by IntoNow is a mix of editorially curated and automatically selected one. From a research perspective, one of the most interesting and challenging use cases addressed by IntoNow is related to news programs (newscasts). When a user is watching a newscast, IntoNow detects it and starts showing online news articles from the Web. This work presents a preliminary study of this problem, i.e., to find an online news article that matches the piece of news discussed in the newscast currently airing on TV, and display it in real-time.
Large-scale social-media analytics on stratosphere
Authors: Christoph Boden, Marcel Karnstedt, Miriam Fernández, Volker Markl
Venue: WWW
Year: 2013

The importance of social-media platforms and online communities - in business as well as public context - is more and more acknowledged and appreciated by industry and researchers alike. Consequently, a wide range of analytics has been proposed to understand, steer, and exploit the mechanics and laws driving their functionality and creating the resulting benefits. However, analysts usually face significant problems in scaling existing and novel approaches to match the data volume and size of modern online communities. In this work, we propose and demonstrate the usage of the massively parallel data processing system Stratosphere, based on second order functions as an extended notion of the MapReduce paradigm, to provide a new level of scalability to such social-media analytics. Based on the popular example of role analysis, we present and illustrate how this massively parallel approach can be leveraged to scale out complex data-mining tasks, while providing a programming approach that eases the formulation of complete analytical workflows.
The economics of data: quality, value & exchange in web observatories
Authors: Paul Booth, Paul Gaskell, Chris Hughes
Venue: WWW
Year: 2013

The aim of this paper is to present a requirement for assessing the quality of data and the development of efficient methods of valuing and exchanging data among Web Observatories. Using economic and business theory a range of concepts are explored which include a brief review of existing business structures related to the exchange of goods, data or otherwise. The paper calls for a wider discussion by the Web Observatory community to begin to define relevant criteria by which data can be assessed and improved over time. The economic incentives are addressed as part of a price by proxy framework we introduce, which is supported by the need to strive for clear pricing signals and the reduction of information asymmetries. What is presented here is a way of establishing and improving data quality with a view to valuing data exchanges that does not require the presence of money in the transaction, yet it remains tied to revenue generation models as they exist online.
Strategyproof mechanisms for competitive influence in networks
Authors: Allan Borodin, Mark Braverman, Brendan Lucier, Joel Oren
Venue: WWW
Year: 2013

Motivated by applications to word-of-mouth advertising, we consider a game-theoretic scenario in which competing advertisers want to target initial adopters in a social network. Each advertiser wishes to maximize the resulting cascade of influence, modeled by a general network diffusion process. However, competition between products may adversely impact the rate of adoption for any given firm. The resulting framework gives rise to complex preferences that depend on the specifics of the stochastic diffusion model and the network topology.
Reactive crowdsourcing
Authors: Alessandro Bozzon, Marco Brambilla, Stefano Ceri, Andrea Mauri
Venue: WWW
Year: 2013

An essential aspect for building effective crowdsourcing com- putations is the ability of "controlling the crowd", i.e. of dynamically adapting the behaviour of the crowdsourcing systems as response to the quantity and quality of completed tasks or to the availability and reliability of performers. Most crowdsourcing systems only provide limited and predefined controls; in contrast, we present an approach to crowdsourcing which provides fine-level, powerful and flexible controls. We model each crowdsourcing application as composition of elementary task types and we progressively transform these high level specifications into the features of a reactive execution environment that supports task planning, assignment and completion as well as performer monitoring and exclusion. Controls are specified as active rules on top of data structures which are derived from the model of the application; rules can be added, dropped or modified, thus guaranteeing maximal flexibility with limited effort.
Multimedia information retrieval on the social web
Authors: Teresa Bracamonte
Venue: WWW
Year: 2013

Efforts have been made to obtain more accurate results for multimedia searches on the Web. Nevertheless, not all multimedia objects have related text descriptions available. This makes bridging the semantic gap more difficult. Approaches that combine context and content information of multimedia objects are the most popular for indexing and later retrieving these objects. However, scaling these techniques to Web environments is still an open problem. In this thesis, we propose the use of user-generated content (UGC) from the Web and social platforms as well as multimedia content information to describe the context of multimedia objects. We aim to design tag-oriented algorithms to automatically tag multimedia objects, filter irrelevant tags, and cluster tags in semantically-related groups. The novelty of our proposal is centered on the design of Web-scalable algorithms that enrich multimedia context using the social information provided by users as a result of their interaction with multimedia objects. We validate the results of our proposal with a large-scale evaluation in crowdsourcing platforms.
Using link semantics to recommend collaborations in academic social networks
Authors: Michele A. Brandão, Mirella M. Moro, Giseli Rabello Lopes, José Palazzo Moreira de Oliveira
Venue: WWW
Year: 2013

Social network analysis (SNA) has been explored in many contexts with different goals. Here, we use concepts from SNA for recommending collaborations in academic networks. Recent work shows that research groups with well connected academic networks tend to be more prolific. Hence, recommending collaborations is useful for increasing a group's connections, then boosting the group research as a collateral advantage. In this work, we propose two new metrics for recommending new collaborations or intensification of existing ones. Each metric considers a social principle (homophily and proximity) that is relevant within the academic context. The focus is to verify how these metrics influence in the resulting recommendations. We also propose new metrics for evaluating the recommendations based on social concepts (novelty, diversity and coverage) that have never been used for such a goal. Our experimental evaluation shows that considering our new metrics improves the quality of the recommendations when compared to the state-of-the-art.
Automated exploration and analysis of ajax web applications with WebMole
Authors: Gabriel Le Breton, Fabien Maronnaud, Sylvain Hallé
Venue: WWW
Year: 2013

WebMole is a browser-based tool that automatically and exhaustively explores all pages inside a web application. Contrarily to classical web crawlers, which only explore pages accessible through regular anchors, WebMole can find its way through Ajax applications that use JavaScript-triggered links, and handles state changes that do not involve a page reload. User-defined functions called oracles can be used to bound the range of pages explored by WebMole to specific parts of an application, as well as to evaluate Boolean test conditions on all visited pages. Overall, WebMole can prove a more flexible alternative to automated testing suites such as Selenium WebDriver.
Vaccine attitude surveillance using semantic analysis: constructing a semantically annotated corpus
Authors: Stephanie Brien, Nona Naderi, Arash Shaban-Nejad, Luke Mondor, Doerthe Kroemker, David L. Buckeridge
Venue: WWW
Year: 2013

This paper reports work in progress to semantically annotate blog posts about vaccines to use in the Vaccine Attitude Surveillance using Semantic Analysis (VASSA) framework. The VASSA framework combines semantic web and natural language processing (NLP) tools and techniques to provide a coherent semantic layer across online social media for assessment and analysis of vaccination attitudes and beliefs. We describe how the blog posts were sampled and selected, our schema to semantically annotate concepts defined in our ontology, details of the annotation process, and inter-annotator agreement on a sample of blog posts.
From search to observation
Authors: Ian C. Brown, Wendy Hall, Lisa J. Harris
Venue: WWW
Year: 2013

In this paper, we propose a set of concepts underlying the process and requirements of observation: that is, the process of employing web observatories for research. We refer to observation as a new concept, distinct from search, which we believe is worthy of study in its own right and note that the process of observation moves the focus of information retrieval away from universal coverage and towards improved quality of results and thus has many potential facets not necessarily present in traditional search.
Social machines: a unified paradigm to describe social web-oriented systems
Authors: Vanilson Arruda Burégio, Silvio Romero de Lemos Meira, Nelson Souto Rosa
Venue: WWW
Year: 2013

Blending computational and social elements into software has gained significant attention in key conferences and journals. In this context, "Social Machines" appears as a promising model for unifying both computational and social processes. However, it is a fresh topic, with concepts and definitions coming from different research fields, making a unified understanding of the concept a somewhat challenging endeavor. This paper aims to investigate efforts related to this topic and build a preliminary classification scheme to structure the science of Social Machines. We provide a preliminary overview of this research area through the identification of the main visions, concepts, and approaches; we additionally examine the result of the convergence of existing contributions. With the field still in its early stage, we believe that this work can collaborate to the process of providing a more common and coherent conceptual basis for understanding Social Machines as a paradigm. Furthermore, this study helps detect important research issues and gaps in the area.
The role of web hosting providers in detecting compromised websites
Authors: Davide Canali, Davide Balzarotti, Aurélien Francillon
Venue: WWW
Year: 2013

Compromised websites are often used by attackers to deliver malicious content or to host phishing pages designed to steal private information from their victims. Unfortunately, most of the targeted websites are managed by users with little security background - often unable to detect this kind of threats or to afford an external professional security service.
Static typing & JavaScript libraries: towards a more considerate relationship
Authors: Benjamin Canou, Emmanuel Chailloux, Vincent Botbol
Venue: WWW
Year: 2013

In this paper, after relating a short history of the mostly unhappy relationship between static typing and JavaScript (JS), we explain a new attempt at conciliating them which is more respectful of both worlds than other approaches. As an example, we present Onyo, an advanced binding of the Enyo JS library for the OCaml language. Onyo exploits the expressiveness of OCaml's type system to properly encode the structure of the library, preserving its design while statically checking that it is used correctly, and without introducing runtime overhead.
Generation of coalition structures to provide proper groups' formation in group recommender systems
Authors: Lucas Augusto M. C. Carvalho, Hendrik T. Macedo
Venue: WWW
Year: 2013

Group recommender systems usually provide recommendations to a fixed and predetermined set of members. In some situations, however, there is a set of people (N) that should be organized into smaller and cohesive groups, so it is possible to provide more effective recommendations to each of them. This is not a trivial task. In this paper we propose an innovative approach for grouping people within the recommendation problem context. The problem is modeled as a coalitional game from Game Theory. The goal is to group people into exhaustive and disjoint coalitions so as to maximize the social welfare function of the group. The optimal coalition structure is that with highest summation over all social welfare values. Similarities between recommendation system users are used to define the social welfare function. We compare our approach with K-Means clustering for a dataset from Movielens. Results have shown that the proposed approach performs better than K-Means for both average group satisfaction and Davies-Bouldin index metrics when the number of coalitions found is not greater than 4 (K <= 4) for a population size of 12 (N = 12).