The prediction of graph evolution is an important and challenging problem in the analysis of networks and of the Web in particular. But while the appearance of new links is part of virtually every model of Web growth, the disappearance of links has received much less attention in the literature. To fill this gap, our approach DecLiNe (an acronym for DECay of LInks in NEtworks) aims to predict link decay in networks, based on structural analysis of corresponding graph models. In analogy to the link prediction problem, we show that analysis of graph structures can help to identify indicators for superfluous links under consideration of common network models. In doing so, we introduce novel metrics that denote the likelihood of certain links in social graphs to remain in the network, and combine them with state-of-the-art machine learning methods for predicting link decay. Our methods are independent of the underlying network type, and can be applied to such diverse networks as the Web, social networks and any other structure representable as a network, and can be easily combined with case-specific content analysis and adopted for a variety of social network mining, filtering and recommendation applications. In systematic evaluations with large-scale datasets of Wikipedia we show the practical feasibility of the proposed structure-based link decay prediction algorithms.
& Spurious links & -- & -- & @cite_7 @cite_16 & Spam & @cite_20 & -- & @cite_20 & Disconnection & -- & @cite_19 & -- Decay of & Reverts & @cite_17 @cite_6 & @cite_17 & -- , Web links & Link removal & -- & -- &
@cite_7 @cite_6 @cite_19 @cite_16 @cite_20 @cite_17
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Identifying and removing spurious links in complex networks is meaningful for many real applications and is crucial for improving the reliability of network data, which, in turn, can lead to a better understanding of the highly interconnected nature of various social, biological, and communication systems. In this paper, we study the features of different simple spurious link elimination methods, revealing that they may lead to the distortion of networks’ structural and dynamical properties. Accordingly, we propose a hybrid method that combines similarity-based index and edge-betweenness centrality. We show that our method can effectively eliminate the spurious interactions while leaving the network connected and preserving the network's functionalities. Many web links mislead human surfers and automated crawlers because they point to changed content, out-of-date information, or invalid URLs. It is a particular problem for large, well-known directories such as the dmoz Open Directory Project, which maintains links to representative and authoritative external web pages within their various topics. Therefore, such sites involve many editors to manually revisit and revise links that have become out-of-date. To remedy this situation, we propose the novel web mining task of identifying outdated links on the web. We build a general classification model, primarily using local and global temporal features extracted from historical content, topic, link and time-focused changes over time. We evaluate our system via five-fold cross-validation on more than fifteen thousand ODP external links selected from thirteen top-level categories. Our system can predict the actions of ODP editors more than 75 of the time. Our models and predictions could be useful for various applications that depend on analysis of web links, including ranking and crawling. The emergence of the web has fundamentally affected most aspects of information communication, including scholarly communication. The immediacy that characterizes publishing information to the web, as well as accessing it, allows for a dramatic increase in the speed of dissemination of scholarly knowledge. But, the transition from a paper-based to a web-based scholarly communication system also poses challenges. In this paper, we focus on reference rot, the combination of link rot and content drift to which references to web resources included in Science, Technology, and Medicine (STM) articles are subject. We investigate the extent to which reference rot impacts the ability to revisit the web context that surrounds STM articles some time after their publication. We do so on the basis of a vast collection of articles from three corpora that span publication years 1997 to 2012. For over one million references to web resources extracted from over 3.5 million articles, we determine whether the HTTP URI is still responsive on the live web and whether web archives contain an archived snapshot representative of the state the referenced resource had at the time it was referenced. We observe that the fraction of articles containing references to web resources is growing steadily over time. We find one out of five STM articles suffering from reference rot, meaning it is impossible to revisit the web context that surrounds them some time after their publication. When only considering STM articles that contain references to web resources, this fraction increases to seven out of ten. We suggest that, in order to safeguard the long-term integrity of the web-based scholarly record, robust solutions to combat the reference rot problem are required. In conclusion, we provide a brief insight into the directions that are explored with this regard in the context of the Hiberlink project. Scholars are increasingly citing electronic “web references” which are not preserved in libraries or full text archives. WebCite is a new standard for citing web references. To “webcite” a document involves archiving the cited Web page through www.webcitation.org and citing the WebCite permalink instead of (or in addition to) the unstable live Web page. This journal has amended its “instructions for authors” accordingly, asking authors to archive cited Web pages before submitting a manuscript. Almost 200 other journals are already using the system. We discuss the rationale for WebCite, its technology, and how scholars, editors, and publishers can benefit from the service. Citing scholars initiate an archiving process of all cited Web references, ideally before they submit a manuscript. Authors of online documents and websites which are expected to be cited by others can ensure that their work is permanently available by creating an archived copy using WebCite and providing the citation information including the WebCite link on their Web document(s). Editors should ask their authors to cache all cited Web addresses (Uniform Resource Locators, or URLs) “prospectively” before submitting their manuscripts to their journal. Editors and publishers should also instruct their copyeditors to cache cited Web material if the author has not done so already. Finally, WebCite can process publisher submitted “citing articles” (submitted for example as eXtensible Markup Language [XML] documents) to automatically archive all cited Web pages shortly before or on publication. Finally, WebCite can act as a focussed crawler, caching retrospectively references of already published articles. Copyright issues are addressed by honouring respective Internet standards (robot exclusion files, no-cache and no-archive tags). Long-term preservation is ensured by agreements with libraries and digital preservation organizations. The resulting WebCite Index may also have applications for research assessment exercises, being able to measure the impact of Web services and published Web documents through access and Web citation metrics. @PARASPLIT [J Med Internet Res 2005;7(5):e60]