3,992 research outputs found
Collaborative Categorization on the Web
Collaborative categorization is an emerging direction for research and innovative
applications. Arguably, collaborative categorization on the Web is an especially
promising emerging form of collaborative Web systems because of both, the
widespread use of the conventional Web and the emergence of the Semantic Web
providing with more semantic information on Web data. This paper discusses this issue
and proposes two approaches: collaborative categorization via category merging and
collaborative categorization proper. The main advantage of the first approach is that it
can be rather easily realized and implemented using existing systems such as Web
browsers and mail clients. A prototype system for collaborative Web usage that uses
category merging for collaborative categorization is described and the results of field
experiments using it are reported. The second approach, called collaborative
categorization proper, however, is more general and scales better. The data structure and
user interface aspects of an approach to collaborative categorization proper are
discussed
Revisiting revisitation in computer interaction: organic bookmark management.
According to Milic-Frayling et al. (2004), there are two general ways of user browsing i.e. search (finding a website where the user has never visited before) and revisitation (returning to a website where the user has visited in the past). The issue of search is relevant to search engine technology, whilst revisitation concerns web usage and browser history mechanisms. The support for revisitation is normally through a set of functional built-in icons e.g. History, Back, Forward and Bookmarks. Nevertheless, for returning web users, they normally find it is easier and faster to re-launch an online search again, rather than spending time to find a particular web site from their personal bookmark and history records. Tauscher and Greenberg (1997) showed that revisiting web pages forms up to 58% of the recurrence rate of web browsing. Cockburn and McKenzie (2001) also stated that 81% of web pages have been previously visited by the user. According to Obendorf et al. (2007), revisitation can be divided into four classifications based on time: short-term (72.6% revisits within an hour), medium-term (12% revisits within a day and 7.8% revisits within a week), and long-term (7.6% revisits longer than a week)
Genesis of Altmetrics or Article-level Metrics for Measuring Efficacy of Scholarly Communications: Current Perspectives
The article-level metrics (ALMs) or altmetrics becomes a new trendsetter in
recent times for measuring the impact of scientific publications and their
social outreach to intended audiences. The popular social networks such as
Facebook, Twitter, and Linkedin and social bookmarks such as Mendeley and
CiteULike are nowadays widely used for communicating research to larger
transnational audiences. In 2012, the San Francisco Declaration on Research
Assessment got signed by the scientific and researchers communities across the
world. This declaration has given preference to the ALM or altmetrics over
traditional but faulty journal impact factor (JIF)-based assessment of career
scientists. JIF does not consider impact or influence beyond citations count as
this count reflected only through Thomson Reuters' Web of Science database.
Furthermore, JIF provides indicator related to the journal, but not related to
a published paper. Thus, altmetrics now becomes an alternative metrics for
performance assessment of individual scientists and their contributed scholarly
publications. This paper provides a glimpse of genesis of altmetrics in
measuring efficacy of scholarly communications and highlights available
altmetric tools and social platforms linking altmetric tools, which are widely
used in deriving altmetric scores of scholarly publications. The paper thus
argues for institutions and policy makers to pay more attention to altmetrics
based indicators for evaluation purpose but cautions that proper safeguards and
validations are needed before their adoption
Of course we share! Testing Assumptions about Social Tagging Systems
Social tagging systems have established themselves as an important part in
today's web and have attracted the interest from our research community in a
variety of investigations. The overall vision of our community is that simply
through interactions with the system, i.e., through tagging and sharing of
resources, users would contribute to building useful semantic structures as
well as resource indexes using uncontrolled vocabulary not only due to the
easy-to-use mechanics. Henceforth, a variety of assumptions about social
tagging systems have emerged, yet testing them has been difficult due to the
absence of suitable data. In this work we thoroughly investigate three
available assumptions - e.g., is a tagging system really social? - by examining
live log data gathered from the real-world public social tagging system
BibSonomy. Our empirical results indicate that while some of these assumptions
hold to a certain extent, other assumptions need to be reflected and viewed in
a very critical light. Our observations have implications for the design of
future search and other algorithms to better reflect the actual user behavior
Agents, Bookmarks and Clicks: A topical model of Web traffic
Analysis of aggregate and individual Web traffic has shown that PageRank is a
poor model of how people navigate the Web. Using the empirical traffic patterns
generated by a thousand users, we characterize several properties of Web
traffic that cannot be reproduced by Markovian models. We examine both
aggregate statistics capturing collective behavior, such as page and link
traffic, and individual statistics, such as entropy and session size. No model
currently explains all of these empirical observations simultaneously. We show
that all of these traffic patterns can be explained by an agent-based model
that takes into account several realistic browsing behaviors. First, agents
maintain individual lists of bookmarks (a non-Markovian memory mechanism) that
are used as teleportation targets. Second, agents can retreat along visited
links, a branching mechanism that also allows us to reproduce behaviors such as
the use of a back button and tabbed browsing. Finally, agents are sustained by
visiting novel pages of topical interest, with adjacent pages being more
topically related to each other than distant ones. This modulates the
probability that an agent continues to browse or starts a new session, allowing
us to recreate heterogeneous session lengths. The resulting model is capable of
reproducing the collective and individual behaviors we observe in the empirical
data, reconciling the narrowly focused browsing patterns of individual users
with the extreme heterogeneity of aggregate traffic measurements. This result
allows us to identify a few salient features that are necessary and sufficient
to interpret the browsing patterns observed in our data. In addition to the
descriptive and explanatory power of such a model, our results may lead the way
to more sophisticated, realistic, and effective ranking and crawling
algorithms.Comment: 10 pages, 16 figures, 1 table - Long version of paper to appear in
Proceedings of the 21th ACM conference on Hypertext and Hypermedi
Organizing information on the next generation web - Design and implementation of a new bookmark structure
The next-generation Web will increase the need for a highly organized and ever evolving method to store references to Web objects. These requirements could be realized by the development of a new bookmark structure. This paper endeavors to identify the key requirements of such a bookmark, specifically in relation to Web documents, and sets out a suggested design through which these needs may be accomplished. A prototype developed offers such features as the sharing of bookmarks between users and groups of users. Bookmarks for Web documents in this prototype allow more specific information to be stored such as: URL, the document type, the document title, keywords, a summary, user annotations, date added, date last visited and date last modified. Individuals may access the service from anywhere on the Internet, as long as they have a Java-enabled Web browser
Revealing User Behaviour on the World-Wide Web
This paper presents the results of a qualitative study of user behaviour on the World-Wide Web. Eight participants were filmed whilst performing user-defined tasks and then asked to review the video-taped session during prompted recall. This data forms the basis for a series of descriptions of user behaviour and the postulation of a number of underlying cognitive mechanisms. Our results indicate that people: lack ready made search strategies, prefer alternatives that are visible, immediately available and familiar, choose the path of least resistance, exhibit social forms of behaviour, engage in parallel activities, object to misleadingly presented information, have trouble orienting, are late in using appropriate strategies, are sensitive to matters of time, and are emotionally involved in the activity. The paper ends with a discussion of how these results can contribute to our understanding of hypermedia
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