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HYPER Tables of Contents: 00010203040506070809101112131415

Proceedings of the 21st ACM Conference on Hypertext and Hypermedia

Fullname:Hypertext'10: Proceedings of the 21st ACM Conference on Hypertext and Hypermedia
Editors:Mark Chignell; Elaine Toms
Location:Toronto, Canada
Dates:2010-Jun-29 to 2010-Jul-01
Publisher:ACM
Standard No:ISBN: 1-4503-0041-3, 978-1-4503-0041-4; ACM DL: Table of Contents hcibib: HYPER10
Papers:59
Pages:318
Links:Conference Home Page
  1. Keynote
  2. Information searching
  3. Recommenders
  4. Adaptation
  5. Algorithms and methods
  6. Networked communities
  7. Tagging
  8. Frontiers
  9. Panel
  10. ELearning and navigation
  11. Discussion paper
  12. User models
  13. Poster session
  14. Demo session
  15. Panel: visions of hypertext
  16. Closing keynote address

Keynote

As we may have thought, and may (still) think BIBAKFull-Text 1-2
  Andrew Dillon
The promise of electronic documents is long lived yet curiously uninspiring in execution. In this address I will revisit the promises and consider the progress and problems faced over the last two decades in creating the information spaces imagined by the field's founders.
Keywords: e-books, human factors

Information searching

Is this a good title? BIBAKFull-Text 3-12
  Martin Klein; Jeffery Shipman; Michael L. Nelson
Missing web pages, URIs that return the 404 "Page Not Found" error or the HTTP response code 200 but dereference unexpected content, are ubiquitous in today's browsing experience. We use Internet search engines to relocate such missing pages and provide means that help automate the rediscovery process. We propose querying web pages' titles against search engines. We investigate the retrieval performance of titles and compare them to lexical signatures which are derived from the pages' content. Since titles naturally represent the content of a document they intuitively change over time. We measure the edit distance between current titles and titles of copies of the same pages obtained from the Internet Archive and display their evolution. We further investigate the correlation between title changes and content modifications of a web page over time. Lastly we provide a predictive model for the quality of any given web page title in terms of its discovery performance. Our results show that titles return more than 60% URIs top ranked and further relevant content returned in the top 10 results. We show that titles decay slowly but are far more stable than the pages' content. We further distill stop titles than can help identify insufficiently performing search engine queries.
Keywords: digital preservation, web page discovery, web page titles
Parallel browsing behavior on the web BIBAKFull-Text 13-18
  Jeff Huang; Ryen W. White
Parallel browsing describes a behavior where users visit Web pages in multiple concurrent threads. Web browsers explicitly support this by providing tabs. Although parallel browsing is more prevalent than linear browsing online, little is known about how users perform this activity. We study the use of parallel browsing through a log-based study of millions of Web users and present findings on their behavior. We identify a power law distribution in browser metrics comprising "outclicks" and tab switches, which signify the degree of parallel browsing. We find that users switch tabs at least 57.4% of the time, but user activity, measured in pageviews, is split among tabs rather than increasing overall activity. Finally, analysis of a subset of the logs focused on Web search shows that while the majority of users do not branch from search engine result pages, the degree of branching is higher for non-navigational queries. Our findings have design implications for Web sites and browsers, search interfaces, and log analysis.
Keywords: log mining, parallel browsing, tabs
A semiotic approach for the generation of themed photo narratives BIBAKFull-Text 19-28
  Charlie Hargood; David E. Millard; Mark J. Weal
A wide variety of systems could be considered 'narrative systems', either directly working towards generating rich narratives or, more frequently, because they present or handle information in a narrative context. These narratives, generated or otherwise handled, may contain themes; an essential part of the subtext of narrative communicating important concepts outside the capabilities of the literal meaning of the content and forming the thematic cohesion that aids the flow of the presented narrative. However despite this very little work has been undertaken to understand of take advantage of these themes, particularly in narrative generation where the presence of well defined themes may improve the richness of those generated narratives. In this paper we evaluate the performance of a system utilising a thematic model in order to generate simple narratives in the form of photo montages compared to a keyword based system that does not. The experiment demonstrates that the system utilising the thematic model is capable of successfully connoting themes within these narratives. It also shows that the relevance of the resulting narratives to the titles used to generate them is higher in the thematic system than those generated by the other system.
Keywords: folksonomies, narrative, narrative generation, semiotics, thematics
The impact of bookmarks and annotations on refinding information BIBAKFull-Text 29-34
  Ricardo Kawase; George Papadakis; Eelco Herder; Wolfgang Nejdl
Refinding information has been interwoven with web activity since its early beginning. Even though all common web browsers were equipped with a history list and bookmarks early enough to facilitate this need, most users typically use search engines to refind information. However, both bookmarks and search based tools have significant limitations that impact their usability: the former are known to be hard to manage over the course of time, whereas the latter require the user to recall a specific combination of keywords or context. Most importantly, though, both are particularly inappropriate in cases where a piece of information is contained within an unstructured web page. In this paper, we present in-context annotation as a more efficient alternative to these methodologies. To verify this claim, we conducted a study in which we compare the performance of experienced users in all three approaches while revisiting specific pieces of information in the web after a long period of time. The outcomes suggest that in-context annotation clearly outperforms both traditional strategies.
Keywords: evaluation, information refinding, user study, web annotation

Recommenders

Automatic construction of travel itineraries using social breadcrumbs BIBAKFull-Text 35-44
  Munmun De Choudhury; Moran Feldman; Sihem Amer-Yahia; Nadav Golbandi; Ronny Lempel; Cong Yu
Vacation planning is one of the frequent -- but nonetheless laborious -- tasks that people engage themselves with online; requiring skilled interaction with a multitude of resources. This paper constructs intra-city travel itineraries automatically by tapping a latent source reflecting geo-temporal breadcrumbs left by millions of tourists. For example, the popular rich media sharing site, Flickr, allows photos to be stamped by the time of when they were taken and be mapped to Points Of Interests (POIs) by geographical (i.e. latitude-longitude) and semantic (e.g., tags) metadata.
   Leveraging this information, we construct itineraries following a two-step approach. Given a city, we first extract photo streams of individual users. Each photo stream provides estimates on where the user was, how long he stayed at each place, and what was the transit time between places. In the second step, we aggregate all user photo streams into a POI graph. Itineraries are then automatically constructed from the graph based on the popularity of the POIs and subject to the user's time and destination constraints.
   We evaluate our approach by constructing itineraries for several major cities and comparing them, through a "crowd-sourcing" marketplace (Amazon Mechanical Turk), against itineraries constructed from popular bus tours that are professionally generated. Our extensive survey-based user studies over about 450 workers on AMT indicate that high quality itineraries can be automatically constructed from Flickr data.
Keywords: flickr, geo-tags, mechanical turk, orienteering problem, social media, travel itinerary
Speak the same language with your friends: augmenting tag recommenders with social relations BIBAKFull-Text 45-50
  Kaipeng Liu; Binxing Fang; Weizhe Zhang
Many existing tag recommendation approaches ignore the social relations between users. In this paper, we investigate the role of such additional information for the task of personalized tag recommendation. We inject the social relations between users and the content similarities between resources, along with the social annotations made by collaborative users, into a graph representation. To fully explore the structure of this graph, we exploit the methodology of random-walk computation of similarities between all the objects. We develop a personalized collaborative filtering algorithm that combines both the collaborative information and the personalized tag preferences. Experiments on Delicious data demonstrate the effectiveness of the proposed methods.
Keywords: personalization, social tagging, tag recommendation
Connecting users and items with weighted tags for personalized item recommendations BIBAKFull-Text 51-60
  Huizhi Liang; Yue Xu; Yuefeng Li; Richi Nayak; Xiaohui Tao
Tags are an important information source in Web 2.0. They can be used to describe users' topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.
Keywords: personalization, recommender systems, tags, web 2.0
Topic-based personalized recommendation for collaborative tagging system BIBAKFull-Text 61-66
  Yanhui Guo; James B. D. Joshi
Collaborative tagging has become a very popular way to share, annotate, and discover online resources in Web 2.0. Yet as the number of resources in Collaborative tagging system grows over time, sifting through the large amounts of resources and finding the right resources to recommend to the right user is becoming a challenging problem. In this paper, we investigate a probabilistic generative model for collaborative tagging, explore the implicit semantic connections in the sparse and noisy information space of heterogeneous users and unsupervised tagging. First, a modified Latent Dirichlet Allocation (LDA) model is used to cluster the tags and users simultaneously. The generalization of resource description and user could alleviate the tag noise and data sparseness of recommendation effectively. And then, considering that topic-based recommendation only takes the users' global interest into consideration without the capability of distinguishing users' interest in detail, we combine the global interests with the individual interest and community interest. Experimental results demonstrate the topic-based personalized recommendation method, which integrate both the commonality factor among users and the specialties of individuals, could alleviate data sparsity and provide a more flexible and effective recommendation than previous methods.
Keywords: collaborative tagging, latent topic models, personalization, recommendation

Adaptation

Providing resilient XPaths for external adaptation engines BIBAKFull-Text 67-76
  Iñaki Paz; Oscar Díaz
Approaches to Web application adaptation can be classified based on whether the application is aware of the adaptation or not. In the latter case, adaptation is referred to as external. External adaptation requires the use of addressing patterns that locate the target portion/data on the application pages to be adapted. Unfortunately, changes on the application normally also require updates to the addressing patterns. This raises pattern robustness as a main concern. This papers focuses on the (semi) automatic generation of change-resilience XPath patterns. Two different categories of changes are addressed, i.e. in space (e.g., different personalizations of a page) and in time (e.g., site upgrades), by exploiting two different techniques: induction and simulated annealing. These techniques permit to obtain XPath patterns "resilient-enough" to a "controlled set of page designs". SiSy, a tool that assists the user in obtaining resilient XPath expressions, was born out of this approach. The approach is tested for two websites (www.yahoo.com and www.elmundo.es), identifying 23 updates to which XPath expressions were resilient to 62% of the undertaken changes.
Keywords: change resilience, evolution, external adaptation, xpath
The influence of adaptation on hypertext structures and navigation BIBAKFull-Text 77-82
  Vinicius Faria Culmant Ramos; Paul M. E. de Bra
In adaptive hypertexts the user is guided in two ways: through the existence of link and through link annotation or hiding. Link structures have been investigated, starting with Botafogo et al, and the effect of link annotation has been studied, for instance by Brusilovsky et al. This paper studies the combined effect of link structure and annotation/hidin on the navigation patterns of users. It defines empirical hubs and studies their correlation with hubs as defined by Kleinberg without considering adaptation. The data for the analysis have been extracted from the logs of the course "Hypermedia Structures and Systems," an online adaptive course offered at the Eindhoven University of Technology.
Keywords: adaptive hypermedia, evaluation, navigation, structural analysis
The next generation authoring adaptive hypermedia: using and evaluating the MOT3.0 and PEAL tools BIBAKFull-Text 83-92
  Jonathan G. K. Foss; Alexandra I. Cristea
Adaptive hypermedia allows for customization to the needs of the user. The authoring process however is not trivial, and is often the main hurdle to overcome in order to bring this useful paradigm to a greater number of users. In this paper, we discuss the major problems occurring in authoring of adaptive hypermedia, and propose a set of generic authoring imperatives, to be consulted by any system implementing creation tools for customization of content. Based on these imperatives, in this paper we extensively illustrate and discuss recent extensions and improvements we have implemented in the My Online Teacher (MOT) adaptation authoring tool set, including the MOT3.0 content authoring and labeling tool and the PEAL adaptation strategy author. Furthermore, we evaluate, compare and discuss two long term uses of the MOT tool set, first in 2008 and the second in 2009.
Keywords: adaptive hypermedia, authoring tools, lag, laos, mot
Provenance meets adaptive hypermedia BIBAKFull-Text 93-98
  Evgeny Knutov; Paul De Bra; Mykola Pechenizkiy
In this paper we consider provenance modelling in Adaptive Hypermedia Systems (AHS). We revisit adaptation and data provenance questions and bring up new and complementary aspects of adaptation and provenance, showing similar and supplementing characteristics. We also scrutinize the provenance importance and issues in Adaptive Hypermedia (AH). The aim of this paper is to extend the conventional AH classification questions with the notion of data lineage which essentially plays an important role in adaptation.
Keywords: adaptation questions, adaptive hypermedia, provenance, w7 provenance model

Algorithms and methods

Assisting two-way mapping generation in hypermedia workspace BIBAKFull-Text 99-108
  Haowei Hsieh; Katherine Pauls; Amber Jansen; Gautam Nimmagadda; Frank Shipman
This paper reports our study of a two-way mapping generation tool called Mapping Assistant, as an extension to the Spatial Hypermedia system VITE. Mapping Assistant has been designed to overcome the problem arising due to the difficulty of users in generating an initial two-way mapping for VITE. We have developed VITE to allow users to interact with information in a semi-formal workspace. Creating two-way mapping profiles is a vital step for projecting structured information into a spatial hypermedia system. A previous study of VITE indicated that users spent much of their time developing an initial mapping before working on the information task. We designed the Mapping Assistant to assist users by generating a quick initial mapping from the data entered by the user and reduce the cognitive and mental load on the user. This research studies users' impression of the Mapping Assistant. The results indicate that the users liked the Mapping Assistant and found it useful, but comments from users also reveal possible directions for further improvement of the tool and its design.
Keywords: editable visualizations, information visualization, information workspace, spatial hypertext, two-way mappings
Analysis of graphs for digital preservation suitability BIBAKFull-Text 109-118
  Charles L. Cartledge; Michael L. Nelson
We investigate the use of autonomically created small-world graphs as a framework for the long term storage of digital objects on the Web in a potentially hostile environment. We attack the classic Erdos -- Renyi random, Barabási and Albert power law, Watts -- Strogatz small world and our Unsupervise. Small World (USW) graphs using different attacker strategies and report their respective robustness. Using different attacker profiles, we construct a game where the attacker is allowed to use a strategy of his choice to remove a percentage of each graph's elements. The graph is then allowed to repair some portion of its self. We report on the number of alternating attack and repair turns until either the graph is disconnected, or the game exceeds the number of permitted turns. Based on our analysis, an attack strategy that focuses on removing the vertices with the highest betweenness value is most advantageous to the attacker. Power law graphs can become disconnected with the removal of a single edge; random graphs with the removal of as few as 1% of their vertices, small-world graphs with the removal of 14% vertices, and USW with the removal of 17% vertices. Watts -- Strogatz small-world graphs are more robust and resilient than random or power law graphs. USW graphs are more robust and resilient than small world graphs. A graph of USW connected WOs filled with date could outlive the individuals and institutions that created the data in an environment where WOs are lost due to random failures or directed attacks.
Keywords: resilience, robustness, small world
iMapping: a zooming user interface approach for personal and semantic knowledge management BIBAKFull-Text 119-128
  Heiko Haller; Andreas Abecker
We present iMapping, a zooming based approach for visually organizing information objects. It was developed on top of semantic desktop technologies and especially targets the support of personal knowledge management. iMapping has been designed to combine the advantages of spatial hypertext and other proven visual mapping approaches like mind-mapping and concept mapping, which are incompatible in their original form. We describe the design and prototypical implementation of iMapping -- which is fundamentally based on deep zooming and nesting. iMapping bridges the gap between unstructured content like informal text notes and semantic models by allowing annotations with the whole range from vague associations to formal relations. First experimental evaluation of the iMapping user-interface approach indicates favorable user experience and functionality, compared with state-of-the-art Mind-Mapping software.
Keywords: human-computer interaction, interaction design, personal knowledge management, semantic desktop, spatial hypertext, visual knowledge mapping

Networked communities

Modularity for heterogeneous networks BIBAKFull-Text 129-134
  Tsuyoshi Murata
Online social media such as delicious and digg are represented as tripartite networks whose vertices are users, tags, and resources. Detecting communities from such tripartite networks is practically important. Modularity is often used as the criteria for evaluating the goodness of network divisions into communities. Although Newman-Girvan modularity is popular for unipartite networks, it is not suitable for n-partite networks. For bipartite networks, Barber, Guimera, Murata and Suzuki define bipartite modularities. For tripartite networks, Neubauer defines tripartite modularity which extends Murata's bipartite modularity. However, Neubauer's tripartite modularity still uses projections and it will lose information that original tripartite networks have. This paper proposes new tripartite modularity for tripartite networks that do not use projections. Experimental results show that better community structures can be detected by optimizing our tripartite modularity.
Keywords: complex network
Link prediction applied to an open large-scale online social network BIBAKFull-Text 135-140
  Dan Corlette; Frank M., III Shipman
In this paper, we describe experiments examining the practicality of applying link prediction to an open large-scale online social network. We rely on metrics that are strictly topological, making use of one previously identified metric and one of our own. We directly address the open nature of the network through a study of the linking dynamics over time between users and the effect the openness of the network (i.e. users entering/leaving the network) has on our ability to predict new friendship links. We follow users from the time they enter the network to 10 months after joining and examine the effect of applying link prediction at different points. Analysis shows that prediction results are best shortly after users have entered the network and that the precision and recall of link prediction results diminish the longer users have been members of the network. To the best of our knowledge, our analysis is the most comprehensive in terms of analyzing link prediction in an open large-scale online social network.
Keywords: link prediction, network dynamics, social networks
Community-based ranking of the social web BIBAKFull-Text 141-150
  Said Kashoob; James Caverlee; Krishna Kamath
The rise of social interactions on the Web requires developing new methods of information organization and discovery. To that end, we propose a generative community-based probabilistic tagging model that can automatically uncover communities of users and their associated tags. We experimentally validate the quality of the discovered communities over the social bookmarking system Delicious. In comparison to an alternative generative model (Latent Dirichlet Allocation (LDA), we find that the proposed community-based model improves the empirical likelihood of held-out test data and discovers more coherent interest-based communities. Based on the community-based probabilistic tagging model, we develop a novel community-based ranking model for effective community-based exploration of socially-tagged Web resources. We compare community-based ranking to three state-of-the-art retrieval models: (i) BM25; (ii) Cluster-based retrieval using K-means clustering; and (iii) LDA-based retrieval. We find that the proposed ranking model results in a significant improvement over these alternatives (from 7% to 22%) in the quality of retrieved pages.
Keywords: community, ranking, social, tagging
Social networks and interest similarity: the case of CiteULike BIBAKFull-Text 151-156
  Danielle H. Lee; Peter Brusilovsky
In collaborative filtering recommender systems, there is little room for users to get involved in the choice of their peer group. It leaves users defenseless against various spamming or ''shilling'' attacks. Other social Web-based systems, however, allow users to self-select peers and build a social network. We argue that users' self-defined social networks could be valuable to increase the quality of recommendation in CF systems. To prove the feasibility of this idea we examined how similar are interests of users connected by self-defined relationships in a collaborative tagging systems Citeulike. Interest similarity was measured by similarity of items and meta-data they share and tags they use. Our study shows that users connected by social networks exhibit significantly higher similarity on all explored levels (items, meta-data, and tags) than non-connected users. This similarity is the highest for directly connected users and decreases with the increase of distance between users. Among other interesting properties of information sharing is the finding that between-user similarity in social connections on the level of metadata and tags is much larger than similarity on the level of items. Overall, our findings support the feasibility of social network based recommender systems and offer some good hints to the prospective authors of these systems.
Keywords: citeulike, information sharing, social networks

Tagging

Of categorizers and describers: an evaluation of quantitative measures for tagging motivation BIBAKFull-Text 157-166
  Christian Körner; Roman Kern; Hans-Peter Grahsl; Markus Strohmaier
While recent research has advanced our understanding about the structure and dynamics of social tagging systems, we know little about (i) the underlying motivations for tagging (why users tag), and (ii) how they influence the properties of resulting tags and folksonomies. In this paper, we focus on problem (i) based on a distinction between two types of user motivations that we have identified in earlier work: Categorizers vs. Describers. To that end, we systematically define and evaluate a number of measures designed to discriminate between describers, i.e. users who use tags for describing resources as opposed to categorizers, i.e. users who use tags for categorizing resources. Subsequently, we present empirical findings from qualitative and quantitative evaluations of the measures on real world tagging behavior. In addition, we conducted a recommender evaluation in which we study the effectiveness of each of the presented measures and found the measure based on the tag content to be the most accurate in predicting the user behavior closely followed by a content independent measure. The overall contribution of this paper is the presentation of empirical evidence that tagging motivation can be approximated with simple statistical measures. Our research is relevant for (a) designers of tagging systems aiming to better understand the motivations of their users and (b) researchers interested in studying the effects of users' tagging motivation on the properties of resulting tags and emergent structures in social tagging systems.
Keywords: measures, social software, tagging, user motivation
Of kings, traffic signs and flowers: exploring navigation of tagged documents BIBAKFull-Text 167-172
  Jacek Gwizdka
Many popular Web 2.0 sites support navigation of tagged web resources. The tag-based navigation has been described as a lightweight reorientation of view on tags and the associated web resources. But is this navigation really lightweight? This paper briefly presents an interface created to support navigation of tagged documents. The paper then describes a study that explored users' understanding of the tag-based navigation process and the underlying information space. The results point to difficulties in promoting correct understanding of complex relationships between documents and tags and to the need for creating interfaces that support navigation continuity.
Keywords: information space metaphors, pivot browsing, tag clouds
Conversational tagging in twitter BIBAKFull-Text 173-178
  Jeff Huang; Katherine M. Thornton; Efthimis N. Efthimiadis
Users on Twitter, a microblogging service, started the phenomenon of adding tags to their messages sometime around February 2008. These tags are distinct from those in other Web 2.0 systems because users are less likely to index messages for later retrieval. We compare tagging patterns in Twitter with those in Delicious to show that tagging behavior in Twitter is different because of its conversational, rather than organizational nature. We use a mixed method of statistical analysis and an interpretive approach to study the phenomenon. We find that tagging in Twitter is more about filtering and directing content so that it appears in certain streams. The most illustrative example of how tagging in Twitter differs is the phenomenon of the Twitter micro-meme: emergent topics for which a tag is created, used widely for a few days, then disappears. We describe the micro-meme phenomenon and discuss the importance of this new tagging practice for the larger real-time search context.
Keywords: memes, tagging, trends, twitter
The impact of resource title on tags in collaborative tagging systems BIBAKFull-Text 179-188
  Marek Lipczak; Evangelos Milios
Collaborative tagging systems are popular tools for organization, sharing and retrieval of web resources. Their success is due to their freedom and simplicity of use. To post a resource, the user should only define a set of tags that would position the resource in the system's data structure -- folksonomy. This data structure can serve as a rich source of information about relations between tags and concepts they represent. To make use of information collaboratively added to folksonomies, we need to understand how users make tagging decisions. Three factors that are believed to influence user tagging decisions are: the tags used by other users, the organization of user's personal repository and the knowledge model shared between users. In our work we examine the role of another potential factor -- resource title. Despite all the advantages of tags, tagging is a tedious process. To minimize the effort, users are likely to tag with keywords that are easily available. We show that resource title, as a source of useful tags, is easy to access and comprehend. Given a choice of two tags with the same meaning, users are likely to be influenced by their presence in the title. However, a factor that seems to have stronger impact on users' tagging decisions is maintaining the consistency of the personal profile of tags. The results of our study reveal a new, less idealistic picture of collaborative tagging systems, in which the collaborative aspect seems to be less important than personal gains and convenience.
Keywords: collaborative tagging, folksonomies, modelling

Frontiers

A narrative-based alternative to tagging BIBAKFull-Text 189-194
  Nuno Tomás; Tiago Guerreiro; Joaquim A. Jorge; Daniel Gonçalves
The enormous dissemination of multimedia information over the past few years has led to mechanisms to support its organization, cataloging and search through descriptions or keywords. A popular way of associating such descriptions to content is tagging as can be found in popular sites such as Flickr (for images) or Delicious (bookmarks). This method allows users to associate tags to media, richly describing its content and may help in its retrieval at a later time. However, the process is mostly unstructured, leading to several problems. Nothing guarantees that the tags used are the most appropriate or the same tags are used in similar situations, making retrieval difficult..
   Our approach relies on narrative-based interfaces which use stories as an organizing principle for tagging media. Given that humans have used stories to communicate since the dawn of time, narrative is a natural form of interaction. By inter-relating bits of information into a coherent whole, stories convey data in a rich, structured way. A study carried out with 40 users over a period of three months shows that users convey almost six times more information when using narratives to describe their media than what is typical of traditional methods. Furthermore, our pilot study saw narratives increasing tag reuse to 94%. Finally, other problems found in tagging such as synonyms and polysemy were notably absent from story-generated tags.
Keywords: digital media, narrative-based interfaces, tagging
UrbanWeb: a platform for mobile context-aware social computing BIBAKFull-Text 195-200
  Frank Allan Hansen; Kaj Grønbæk
UrbanWeb is a novel Web-based context-aware hypermedia platform. It provides essential mechanisms for mobile social computing applications: the framework implements context as an extension to Web 2.0 tagging and provides developers with an easy to use platform for mobile context-aware applications. Services can be statically or dynamically defined in the user's context, data can be precached for data intensive mobile applications, and shared state supports synchronization between running applications such as games. The paper discusses how UrbanWeb acquires cues about the user's context from sensors in mobile phones, ranging from GPS data, to 2D barcodes, and manual entry of context information, as well as how to utilize this context in applications. The experiences show that the UrbanWeb platform efficiently supports a rich variety of urban computing applications in different scales of user populations.
Keywords: context-awareness, geo-spatial hypermedia, mobile web, multimedia blogging, physical hypermedia, social computing, urban computing
Hyperorders and transclusion: understanding dimensional hypertext BIBAKFull-Text 201-210
  James O. Goulding; Timothy J. Brailsford; Helen L. Ashman
ZigZag is a unique hyperstructural paradigm designed by the hypertext pioneer Ted Nelson. It has piqued a lot of interest in the hypertext community in recent years because of its aim of revolutionizing electronic access to information and knowledge bases. In ZigZag information is stored in cells that are arranged into lists organized along unlimited numbers of intersecting sets of associations called dimensions. To this infrastructure a mechanism of transclusion is added, allowing the data stored in cells to span, and hence be utilized, in different contexts. Proponents of ZigZag claim that it is a flexible and universal structure for information representation, and yet the system has not been widely adopted and has been implemented even more rarely. In this paper we address the question of whether there are intrinsic theoretical reasons as to why this is the case.
   While the basic features and specifications of ZigZag are well known, we delve in to the less understood area of its theoretical underpinnings to tackle this question. By modeling ZigZag within the framework of set theory we reveal a new class of hyperstructure that contains no referencable link objects whatsoever, instead grouping non-referencable binary associations into disjunct but parallel sets of common semantics (dimensions). We go on to further specialize these "dimensional models" into sets of finite partial functions, which are closed over a single domain, isolating the new class of hyperstructures we are calling hyperorders. This analysis not only sheds light on the benefits and limitations of the ZigZag hypermedia system, but also provides a framework to describe and understand a wider family of possible hyperstructure models of which it is an early example. Characteristics of Zigzag's transclusion mechanisms are also investigated, highlighting a previously unrecognized distinction, and potential irrevocable conflict, between two distinct uses of content reuse: instance and identity transclusion.
Keywords: hypermedia structure, hyperorder, hyperstructure, set theory, transclusion, zigzag

Panel

Evaluating hypertext: the quantitative-qualitative quandary BIBAKFull-Text 211-212
  Mark Chignell; Peter Brusilovsky; Steve Szigeti; Elaine Toms
This panel will examine issues regarding the evaluation of hypertext research. The panelists will begin by contrasting four different viewpoints on the role of evaluation in hypertext research. The discussion will then consider questions relating the what evaluation methods should be used and when.
Keywords: evaluation, hypertext research

ELearning and navigation

Design and evaluation of a hypervideo environment to support veterinary surgery learning BIBAKFull-Text 213-222
  Claudio A. B. Tiellet; André Grahl Pereira; Eliseo Berni Reategui; José Valdeni Lima; Teresa Chambel
In the search of alternative ways to learning veterinary surgery with live animals, hypervideo was considered a promising candidate as a learning tool. Video can enhance the realism and authenticity of a learning environment. By adding structure and interactivity to video, hypervideo allows to navigate video and to explore other related media to complement it. Hypervideo might then support the creation of a rich and realistic learning environment, through the interactive access, construction and communication of knowledge on veterinary surgery. In this paper, we present the design and evaluation of Hvet, a hypervideo environment to support learning of veterinary surgery. Design was based on cognitive and media theories, and evaluation was based on the use of Hvet by veterinary students, in order to test its efficacy in substitution of learning and training with live animals. Results support the hypothesis, showing the potential of hypervideo as a valuable and effective tool to support learning of surgery techniques and revealing the most appreciated design options.
Keywords: design, evaluation, high education, hypervideo, surgery, veterinary, video
The value of adaptive link annotation in e-learning: a study of a portal-based approach BIBAKFull-Text 223-228
  I-Han Hsiao; Peter Brusilovsky; Michael Yudelson; Alvaro Ortigosa
Adaptive link annotation is one of the most popular adaptive educational hypermedia techniques. It has been widely studied and demonstrated its ability to help students to acquire knowledge faster, improve learning outcomes, reduce navigation overhead, increase motivation, and encourage the beneficial non-sequential navigation. However, almost all studies of adaptive link annotation have been performed in the context of dedicated adaptive educational hypermedia systems. The role of this technique in the context of widely popular learning portals has not yet been demonstrated. In this paper, we attempt to fill this gap by investigating the value of adaptive navigation support embedded into the learning portal. We compare the effect of portal-based adaptive navigation support to both the effect of the adaptive navigation support in adaptive educational hypermedia systems and to non-adaptive learning portals.
Keywords: adaptive hypermedia, e-learning, motivation, navigation support, open corpus adaptive hypermedia., portal self-assessment
Agents, bookmarks and clicks: a topical model of web navigation BIBAKFull-Text 229-234
  Mark R. Meiss; Bruno Gonçalves; José J. Ramasco; Alessandro Flammini; Filippo Menczer
Analysis has shown that the standard Markovian model of Web navigation is a poor predictor of actual Web traffic. Using empirical data, we characterize several properties of Web traffic that cannot be reproduced with Markovian models but can be explained by an agent-based model that adds several realistic browsing behaviors. First, agents maintain bookmark lists used as teleportation targets. Second, agents can retreat along visited links, a branching mechanism that can reproduce behavior such the back button and tabbed browsing. Finally, agents are sustained by visiting pages of topical interest, with adjacent pages being related. This modulates the production of new sessions, recreating heterogeneous session lengths. The resulting model reproduces individual behaviors from empirical data, reconciling the narrowly focused browsing patterns of individual users with the extreme heterogeneity of aggregate traffic measurements, and leading the way to more sophisticated, realistic, and effective ranking and crawling algorithms.
Keywords: agent-based model, back button, bookmarks, bookrank, browsing, clicks, entropy, interest, navigation, pagerank, sessions, topicality, traffic, web links

Discussion paper

Criticism BIBAKFull-Text 235-244
  Mark Bernstein
Our methods for accumulating and testing evidence of a hypertext's successes and shortcomings are numerous but poorly understood. This paper surveys the most influential approaches to evaluating hypertexts and considers their impact on crafting a new literary economy.
Keywords: criticism, economics, fiction, hypertext narrative, publishing

User models

Capturing implicit user influence in online social sharing BIBAKFull-Text 245-254
  Ching-man Au Yeung; Tomoharu Iwata
Online social sharing sites are becoming very popular nowadays among Web users, who use these sites to share their favourite items and to discover interesting and useful items from other users. While an explicit social network is not necessarily present in these sites, it is still possible that users influence one another in the process of item adoption through various implicit mechanisms. In this paper, we study how we can capture the implicit influences among the users in a social sharing site. We propose a probabilistic model for user adoption behaviour, where we assume that when user adopts an item, he would pick a user and choose from the set of items that this user has adopted. By using the model, we estimate the probability that one user influences another user in the course of item adoption, based on the temporal adoption pattern of the users. We carry out empirical studies of the model on Delicious, a popular social bookmarking site. Experiments show that our model can be used to predict item adoption more accurately than using collaborative filtering techniques. We find that the strength of implicit influence various across different topics. We also show that our method is able to identify the influential users who are more likely to possess items interested by other users. Our model can be used to study the dynamics in a social sharing site and to complement collaborative filtering in recommendation systems.
Keywords: collaborative tagging, social influence, social sharing
Interpretation and visualization of user history in a spatial hypertext system BIBAKFull-Text 255-264
  DoHyoung Kim; Frank M. Shipman
We describe a new history mechanism based on experiences with the use of recorded interaction history in the Visual Knowledge Builder (VKB). Problems with the use of history in prior systems include difficulty in locating activity of interest in large tasks, the problem of history records being at a system activity level rather than a human activity level, and difficulty in supporting navigation and comprehension in the branching histories used to represent alternative directions. To support comprehension of the history, we describe automatic history clustering to group low-level system events into a more human-level representation of activity and the extraction of information for summarizing these groups of events. To further support navigation and comprehension of history, the mechanism includes multiple visualization techniques to match diverse uses of history. The new history mechanism is integrated into VKB 3.
Keywords: asynchronous collaboration, awareness, branching history, history, spatial hypertext, user activity records, visualization, vkb
Visit me, click me, be my friend: an analysis of evidence networks of user relationships in BibSonomy BIBAKFull-Text 265-270
  Folke Mitzlaff; Dominik Benz; Gerd Stumme; Andreas Hotho
The ongoing spread of online social networking and sharing sites has reshaped the way how people interact with each other. Analyzing the relatedness of different users within the resulting large populations of these systems plays an important role for tasks like user recommendation or community detection. Algorithms in these fields typically face the problem that explicit user relationships (like friend lists) are often very sparse. Surprisingly, implicit evidences (like click logs) of user relations have hardly been considered to this end.
   Based on our long-time experience with running BibSonomy [4], we identify in this paper different evidence networks of user relationships in our system. We broadly classify each network based on whether the links are explicitly established by the users (e.g., friendship or group membership) or accrue implicitly in the running system (e.g., when user u copies an entry of user v). We systematically analyze structural properties of these networks and whether topological closeness (in terms of the length of shortest paths) coincides with semantic similarity between users.
   Our results exhibit different characteristics and. provide preparatory work for the inclusion of new (and less sparse) information into the process of optimizing community detection or user recommendation algorithms.
Keywords: community detection, folksonomies, social networks, user recommendation

Poster session

SnoopyDB: narrowing the gap between structured and unstructured information using recommendations BIBAKFull-Text 271-272
  Wolfgang Gassler; Eva Zangerle; Michael Tschuggnall; Günther Specht
Knowledge is structured -- until it is stored to a wiki-like information system. In this paper we present the multi-user system SnoopyDB, which preserves the structure of knowledge without restricting the type or schema of inserted information. A self-learning schema system and recommendation engine support the user during the process of inserting information. These dynamically calculated recommendations develop an implicit schema, which is used by the majority of stored information. Further recommendation measures enhance the content both semantically and syntactically and motivate the user to insert more information than he intended to.
Keywords: human interaction, ranking, rdf, recommendations, semantic web, semistructured data
Citation based plagiarism detection: a new approach to identify plagiarized work language independently BIBAKFull-Text 273-274
  Bela Gipp; Jöran Beel
This paper describes a new approach towards detecting plagiarism and scientific documents that have been read but not cited. In contrast to existing approaches, which analyze documents' words but ignore their citations, this approach is based on citation analysis and allows duplicate and plagiarism detection even if a document has been paraphrased or translated, since the relative position of citations remains similar. Although this approach allows in many cases the detection of plagiarized work that could not be detected automatically with the traditional approaches, it should be considered as an extension rather than a substitute. Whereas the known text analysis methods can detect copied or, to a certain degree, modified passages, the proposed approach requires longer passages with at least two citations in order to create a digital fingerprint.
Keywords: citation analysis, citation order analysis, duplicate detection, language independent, plagiarism detection
Balancing content contextualization and accessibility in engineering assessment BIBAKFull-Text 275-276
  Chirag Variawa; Susan McCahan
It has been suggested that the teaching of engineering content should include integration across subject matter and contextualization of the material. However, contextualization can create a barrier to accessibility when there is a disconnect between the student's background experience and the context chosen by the instructor. This can have a particular impact when the contextualization is used in the process of assessing student learning. This study investigates the types of words that cause difficulty for students. The assessment shows that there are terms used on engineering tests that present possible barriers for students, such that the test may in part be assessing the student's cultural knowledge or vocabulary rather than engineering competency. We propose a number of strategies for remediating this situation including the use of hypertext to mitigate this type of accessibility barrier.
Keywords: accessibility, adult education, assessment, contextualization, diversity, engineering education, inclusivity, instruction, learning barrier, pedagogy, universal instructional design
Assessing users' interactions for clustering web documents: a pragmatic approach BIBAKFull-Text 277-278
  Luis A. Leiva; Enrique Vidal
In this paper we are interested in describing Web pages by how users interact within their contents. Thus, an alternate but complementary way of labelling and classifying Web documents is introduced. The proposed methodology is founded on unsupervised learning algorithms, aiming to automatically find natural clusters by means of users' implicit interaction data. Furthermore, it also copes with the dynamic nature and heterogeneity of both users' behaviour and the Web, updating the clustering model over time. We want to show that our framework can be easily integrated in any Website, just employing already-known methods and current technologies.
Keywords: document profiling, implicit modelling, unsupervised learning, web mining
Discovery of information disseminators and receptors on online social media BIBAKFull-Text 279-280
  Munmun De Choudhury
Today, there is significant sharing of information artifacts among users on various social media sites, including Digg, Twitter and Flickr. An interesting consequence of such rich and extensive social interaction is the evolving nature of "roles" that are acquired by users over time, in the context of variegated communication activities, such as commenting, replying, uploading a media artifact and so on. In this paper, we investigate the discovery of two roles that define information dissipation: disseminators and receptors. We propose a computational framework based on factorization of stacked representation of activities and test the outcomes on a dataset from Digg. Experiments show that our approach can, interestingly, reveal correlations with user activities occurring at a future point in time.
Keywords: digg, information diffusion, information disseminators, information roles, social media, social network analysis
Adaptation and search: from Dexter and AHAM to GAF BIBAKFull-Text 281-282
  Evgeny Knutov; Paul De Bra; Mykola Pechenizkiy
Adaptive Hypermedia Systems (AHS) have long been concentrating on adaptive guidance of links between domain concepts. Here we show parallels between navigation and linking in adaptive hypermedia on the one hand and information searching or querying on the other hand. We present a transition towards search in AHS by aligning the web search process with the layered structure of AHS and adaptation process.
Keywords: adaptation, dexter model, navigation, open corpus, search
Brickstreams: physical hypermedia driven customer insight BIBAKFull-Text 283-284
  Riddhiman Ghosh; Jhilmil Jain; Mohamed Dekhil
Brickstreams is a system that employs hypermedia structures in physical spaces, specifically in brick-and-mortar retail environments, to capture insight into customer behavior. By instrumenting and tracking interactions with tagged products in retail stores, and by using demographic and location intelligence, our system is able to bring the benefits of online clickstream analysis to the brick and mortar world. We have implemented a prototype of Brickstreams, realized through REST web services and mobile device clients.
Keywords: clickstream analysis, customer insight, physical hypermedia
Collaborative identification and annotation of government deep web resources: a hybrid approach BIBAKFull-Text 285-286
  Pengyi Zhang; Yan Qu; Chen Huang; Paul T. Jaeger; John Wells; W. Scott Hayes; James E. Hayes; Xin Jin
In this extended abstract, we propose a hybrid approach of automatic means and social computing to identify and annotate Deep Web resources -- mainly databases and database portals -- to provide easy access to and descriptions and instruction on how to use these resources.
Keywords: collaborative identification and annotation, government databases, hybrid approach, social computing
Visual summaries of data: a spatial hypertext approach to user feedback BIBAKFull-Text 287-288
  Annika L. Wolff; Paul Mulholland; Zdenek Zdrahal
In this paper we describe the SILVER toolkit, which is designed for tasks in which a user learns by analysing and interpreting a set of resources. The user categorises each resource according to the set of properties that they identify as being applicable to it. Due to the large amount of data generated by this type of task, the user may find it hard to identify patterns in their classification and tagging, to recognise their own inconsistencies or make comparisons between themselves and others. Principles of spatial hypertext can be used to provide visual summaries of the data that can assist the above activities.
Keywords: categorisation, id3 decision trees, inquiry learning, organisation, spatial hypertext
Dealing with the video tidal wave: the relevance of expertise for video tagging BIBAKFull-Text 289-290
  Sara Darvish; Alvin Chin
The vast amounts of video that need to be tagged preclude the exclusive use of professional indexers. Thus a significant amount of video will need to be tagged by non-experts. Are the tags created by experts demonstrably superior to those of non-experts, and when non-experts have to be used for tagging, is it better to rely on tags created by those who upload videos or on others who watch the videos? Two related studies were carried out, the first where domain experts and others tagged videos, and the second where experts and others rated the relevance of tags that had been assigned to videos in the first study. Expert tags were judged to be more relevant by both experts and non-experts, with non-expert viewers also creating significantly better tags than did owners (i.e., the people who uploaded the videos). While significant differences were observed, the mean overall judged relevance of tags was relatively low, even for experts. Thus there seems to be considerable scope for the use of tag recommendation systems and other tools that can make the tagging process more consistent.
Keywords: categorization, classification, collaborative tagging, tagging systems, video annotation
Spatial contiguity and implicit learning in hypertext BIBAKFull-Text 291-292
  Seungoh Paek; Daniel Hoffmann; Antonios Saravanos
The study is interested in how the spatial contiguity principle mediates implicit learning in a hypertext environment.
Keywords: hypertext, implicit learning, spatial contiguity
Objectivity classification in online media BIBAKFull-Text 293-294
  Elisabeth Lex; Andreas Juffinger; Michael Granitzer
In this work, we assess objectivity in online news media. We propose to use topic independent features and we show in a cross-domain experiment that with standard bag-of-word models, classifiers implicitly learn topics. Our experiments revealed that our methodology can be applied across different topics with consistent classification performance.
Keywords: classification, objectivity, online news media
Search your interests everywhere!: wikipedia-based keyphrase extraction from web browsing history BIBAKFull-Text 295-296
  Mitsumasa Kondo; Akimichi Tanaka; Tadasu Uchiyama
This paper proposes a method that can extract user interests from the user's Web browsing history. Our method allows easy access to multiple content domains such as blogs, movies, QA sites, etc. since the user does not need to input a separate search query in each domain/site. To extract user interests, the method first extracts candidate keyphrases from the user's web browsed documents. Second, important keyphrases obtained from a link structure analysis of Wikipedia content is extracted from the main contents of web documents. This technique is based on the idea that important keyphrases in Wikipedia are important keyphrases in the real world. Finally, keyphrases contained in the documents important to the user are set in order as user interests. An experiment shows that our method offers improvements over a conventional method and can recommend interests attractive to the user.
Keywords: keyphrase extraction
On the robustness of google scholar against spam BIBAKFull-Text 297-298
  Jöran Beel; Bela Gipp
In this research-in-progress paper we present the current results of several experiments in which we analyzed whether spamming Google Scholar is possible. Our results show, it is possible: We 'improved' the ranking of articles by manipulating their citation counts and we made articles appear in searchers for keywords the articles did not originally contained by placing invisible text in modified versions of the article.
Keywords: academic search engines, citation spam, search engines, spam, spamdexing
Leveraging multi-faceted tagging to improve search in folksonomy systems BIBAKFull-Text 299-300
  Fabian Abel; Ricardo Kawase; Daniel Krause
In this paper we present ranking algorithms for folksonomy systems that exploit additional contextual information attached to tag assignments available. We evaluate the algorithms in the TagMe! system, a tagging front-end for Flickr, and show that our algorithms, which exploit categories, spatial information, and URIs describing the semantics of tag assignments, perform significantly better than the FolkRank that does not consider such contextual information.
Keywords: context, faceted tagging, folksonomies, ranking, search, social media
Automatic extraction of structure, content and usage data statistics of web sites BIBAKFull-Text 301-302
  Ioannis Paparrizos; Vassiliki Koutsonikola; Lefteris Angelis; Athena Vakali
In this paper we present a web mining tool which automatically extracts the structure, content and usage data statistics of web sites. This work inspired by the fact that web mining consists of three axes: web structure mining, web content mining and web usage mining. Each one of those axes is using the structure, content and usage data respectively. The scope is to use the developed multi-thread web crawler as a tool to automatically extract from web pages data that are associated with each one of those three axes in order afterwards to compute several useful descriptive statistics and apply advanced mathematical and statistical methods. A description of our system is provided as well as some experimentation results.
Keywords: classification algorithm, crawling, structure, content and usage data, web mining
Enhancing search applications by utilizing mind maps BIBAKFull-Text 303-304
  Jöran Beel; Bela Gipp
In this paper we present how sharing and utilizing mind maps could enhance search applications such as document search engines and recommender systems. In addition, we briefly present the first research results which indicate that mind maps can be used to determine document relatedness and therefore can enhance document recommender systems. We also discuss some challenges that information retrieval on mind maps will probably have to overcome.
Keywords: information retrieval, mind maps, search applications, social media
Crossmedia personalized learning contexts BIBAKFull-Text 305-306
  Alcina Prata; Nuno Guimarães; Teresa Chambel
The trends in convergence, integration and co-existence of various media technologies are creating new opportunities for the globalization of learning practices. The emerging era of lifelong learning is calling for flexible environments. Interactive television (iTV) holds a great potential in this scenario, but there is still limited research in terms of cognitive and interaction aspects. With the aim to link these opportunities, in flexible, adequate and effective learning contexts, a new paradigm to generate crossmedia personalized learning contexts from iTV, based on cognitive and affective aspects, is being studied. This paper presents the results obtained from the use of the e-iTV system, designed to illustrate and explore this paradigm.
Keywords: crossmedia learning environments, educational hypermedia, human-computer interaction, iTV, personalized web content
Webpage relationships for information retrieval within a structured domain BIBAKFull-Text 307-308
  Vincent W. L. Tam; John Shepherd
In this paper, we describe a technique for improving the effectiveness of information retrieval within individual websites. Our proposed approach exploits the link structures within the site and the idea that relevant content maybe spread across several related pages within the site. We present experiments which compare our approach to other web search techniques.
Keywords: domain specific search, hyperlink structure

Demo session

Show my code in the web BIBAKFull-Text 309-310
  Min-Jung Bae; Jeong-Hoon Ji; Gyun Woo
This paper proposes a method to show the code in the web in a very compact way. The visualization method provides two pictures for a source code, each of which is based on the Flower of Life and the Hilbert Curve. Each visualization result captures the nesting structure and the size of the code. According to the experiment, the complexity of the visualization has a signicant correlation with the traditional software metrics.
Keywords: flower of life, hilbert curve, source code, visualization, web service
Emberlight: share and publish spatial hypertext to the web BIBAKFull-Text 311-312
  J. Nathan Matias; Frederick Cheung
Emberlight publishes spatial hypertext to the web, providing basic versioning and collaboration for users of desktop spatial hypertext software. In this demo session, we will seek feedback on the system, consider integration collaborations, talk about new research avenues, and discuss funding ideas.
Keywords: collaboration, comparison, shywiki, spatial hypertext, tinderbox, version management, viki, vkb, vue
HVet: a hypervideo environment to support veterinary surgery learning BIBAKFull-Text 313-314
  Claudio A. B. Tiellet; André Grahl Pereira; Eliseo Berni Reategui; José Valdeni Lima; Teresa Chambel
In this demo, we present HVet, a hypervideo environment to support learning of veterinary surgery as an alternative to learning with live animals. By adding structure and interactivity, hypervideo allows to navigate video and to explore other related media to complement it, supporting the creation of a rich and realistic learning environment, with interactive access, construction and communication of knowledge.
Keywords: design, high education, hypervideo, surgery, veterinary

Panel: visions of hypertext

Past visions of hypertext and their influence on us today BIBAKFull-Text 315
  Darren Lunn; Mark Bernstein; Cathy Marshall; J. Nathan Matias; James M. Nyce; Frank Tompa
In July 1945, Vannevar Bush published the seminal paper As We May Think in Atlantic Monthly [2]. In this paper Bush proposed MEMEX, a device where information and records could be stored and linked together through 'trails' and 'associations' rather than 'artificial' indexing mechanisms. This idea is credited with being the inspiration, and precursor, for the modern World Wide Web (WWW) invented by Tim Berners-Lee, but as Harper notes, for most of the article, Bush was not concerned solely with the technical aspects of his MEMEX system. Instead, as with most computer visionaries, he was more concerned with how the computer system and its interfaces could help humanity [3]. We must therefore consider if, as a research field, we are still trying to build MEMEX as Bush envisioned it, or are we more influenced by a vision of information storage and presentation, of which Bush's paper was one of many?
Keywords: history, hypertext, memex

Closing keynote address

The social life of hypertext BIBAKFull-Text 317
  Irene Greif
We live in a world where networks of people mingle with networks of documents, creating networks of ideas that are linked to the people and documents that subscribe to them. New tools are being created that facilitate the interactions between these networks, greatly expanding the role of hypertext as a social media tool. Interactive visualization is a particularly powerful tool that capitalizes on the immense visual processing power of the human brain. With Web 2.0 and related technologies the world of ideas is being shaped by the wisdom of crowds. People understand data better when we scale up the audience. While one can learn a lot simply watching visual displays of information, there is also a pent up desire to analyze. People want their own controls, so that they can see data in their own way by looking at it differently. ManyEyes is a system that features a range of visualizations, where people can upload data and see that data in a variety of ways. When people find interesting views of the data they can annotate them and share their comments with others, thus building a community around visualization and interpretation. Sharing visualizations and interpretations lets people have deeper discussions in the communities that they belong to, facilitating conversations on politics, economics, health, and a host of other issues. We have found that visualizations are particularly powerful when used to analyze words. Dynamic visualizations draw people in and lead to interesting new conclusions. Scalable real world deployments let research keep up with the wisdom of crowds, and this keynote will explore some of the emerging research in this area. More information about the Many Eyes project can be found at www.many-eyes.com.
Keywords: collaboration, text analysis, visualization, web 2.0