Either by ensuring the continuing availability of information, or by deliberately caching content that might get deleted or removed, Web archiving services play an increasingly important role in today's information ecosystem. Among these, the Wayback Machine has been proactively archiving, since 2001, versions of a large number of Web pages, while newer services like archive.is allow users to create on-demand snapshots of specific Web pages, which serve as time capsules that can be shared across the Web. In this paper, we present a large-scale analysis of Web archiving services and their use on social media, aiming to shed light on the actors involved in this ecosystem, the content that gets archived, and how it is shared. To this end, we crawl and study: 1) 21M URLs, spanning almost two years, from archive.is; and 2) 356K archive.is plus 391K Wayback Machine URLs that were shared on four social networks: Reddit, Twitter, Gab, and 4chan's Politically Incorrect board ( pol ) over 14 months. We observe that news and social media posts are the most common types of content archived, likely due to their perceived ephemeral and or controversial nature. Moreover, URLs of archiving services are extensively shared on "fringe" communities within Reddit and 4chan to preserve possibly contentious content. Lastly, we find evidence of moderators nudging or even forcing users to use archives, instead of direct links, for news sources with opposing ideologies, potentially depriving them of ad revenue.
Archived content. @cite_24 study the evolution of JavaScript using historical data of 3M Web pages from the Wayback Machine, while @cite_29 analyze how Web trackers have evolved in the previous decade. @cite_14 predict whether an uncompromised website will become malicious also using the Wayback Machine. @cite_27 study how the German Web has evolved in the past 18 years using data from the Wayback Machine for 100 popular domains, highlighting the exponential growth of the number of pages. Then, @cite_31 characterize the accessibility of websites using a random sample of sites from the Wayback Machine between 1997 and 2002.
@cite_14 @cite_29 @cite_24 @cite_27 @cite_31
1420268584 2489352404 2101678831 2410230255 2221727122
The Internet Archive's Wayback Machine is the largest modern web archive, preserving web content since 1996. We discover and analyze several vulnerabilities in how the Wayback Machine archives data, and then leverage these vulnerabilities to create what are to our knowledge the first attacks against a user's view of the archived web. Our vulnerabilities are enabled by the unique interaction between the Wayback Machine's archives, other websites, and a user's browser, and attackers do not need to compromise the archives in order to compromise users' views of a stored page. We demonstrate the effectiveness of our attacks through proof-of-concept implementations. Then, we conduct a measurement study to quantify the prevalence of vulnerabilities in the archive. Finally, we explore defenses which might be deployed by archives, website publishers, and the users of archives, and present the prototype of a defense for clients of the Wayback Machine, ArchiveWatcher. The Internet Archive's (IA) Wayback Machine is the largest and oldest public web archive and has become a significant repository of our recent history and cultural heritage. Despite its importance, there has been little research about how it is discovered and used. Based on web access logs, we analyze what users are looking for, why they come to IA, where they come from, and how pages link to IA. We find that users request English pages the most, followed by the European languages. Most human users come to web archives because they do not find the requested pages on the live web. About 65 of the requested archived pages no longer exist on the live web. We find that more than 82 of human sessions connect to the Wayback Machine via referrals from other web sites, while only 15 of robots have referrers. Most of the links (86 ) from websites are to individual archived pages at specific points in time, and of those 83 no longer exist on the live web. Using Internet Archive's Wayback Machine, a random sample of websites from 1997-2002 were retrospectively analyzed for effects that technology has on accessibility for persons with disabilities and compared to government websites. Analysis of Variance (ANOVA) and Tukey's HSD were used to determine differences among years. Random websites become progressively inaccessible through the years (p The Web has been around and maturing for 25 years. The popular websites of today have undergone vast changes during this period, with a few being there almost since the beginning and many new ones becoming popular over the years. This makes it worthwhile to take a look at how these sites have evolved and what they might tell us about the future of the Web. We therefore embarked on a longitudinal study spanning almost the whole period of the Web, based on data collected by the Internet Archive starting in 1996, to retrospectively analyze how the popular Web as of now has evolved over the past 18 years. For our study we focused on the German Web, specifically on the top 100 most popular websites in 17 categories. This paper presents a selection of the most interesting findings in terms of volume, size as well as age of the Web. While related work in the field of Web Dynamics has mainly focused on change rates and analyzed datasets spanning less than a year, we looked at the evolution of websites over 18 years. We found that around 70 of the pages we investigated are younger than a year, with an observed exponential growth in age as well as in size up to now. If this growth rate continues, the number of pages from the popular domains will almost double in the next two years. In addition, we give insights into our data set, provided by the Internet Archive, which hosts the largest and most complete Web archive as of today. 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] This Note addresses the use of archived Internet content obtained via the Wayback Machine, a service provided by the Internet Archive that accesses the largest online digital collection of archived Web pages in the world. Given the dynamic nature of the World Wide Web, Internet content is constantly changed, amended, and removed. As a result, interim versions of Web pages have limited life spans. The Internet Archive indexes and stores Web pages to allow researchers to access discarded or since-altered versions. In the legal profession, archived Web pages have become an increasingly helpful form of proof. Intellectual property enforcers have recognized the value of the Internet Archive as a tool for tracking down infringers, but evidence from the Internet Archive has rarely been admitted at trial. This Note surveys the handful of judicial opinions and orders that comment on the admission of Internet Archive evidence and explores the conflict underlying these approaches. As an alternative to the courses they have taken, this Note urges courts to treat the introduction of archived Web pages as implicating a best evidence issue in addition to an authentication question. Under this approach, courts would decide using evidence sufficient to the purpose, but not necessarily admissible at trial, whether the archived page qualifies as a 'duplicate' of a page that once appeared on the Web. Beyond that, courts would apply authentication standards already developed to decide whether a reasonable jury could find, based only on admissible evidence, whether proffered evidence accurately represents the page stored on the Internet Archive server and, if necessary, whether the original page accurately represented material placed on the originating site by the site’s owner or operator. With this additional step, reliable evidence from the Wayback Machine can become as easily admitted as any other Internet-derived proof. The Web is characterized by an extremely dynamic nature, as it is proved by the rapid and significant growth it has experimented in the last decade and by its continuous evolution through creation or deletion of pages and hyperlinks. Consequently, analyzing the temporal evolution of the Web has become a crucial task that can provide search engines with valuable information for refining crawling policies, improving ranking models or detecting spam. Understanding how the Web evolves over time is a delicate challenge that requires to integrate theoretical efforts of modelization and empirical results. Obtaining such findings is very expensive in terms of bandwidth, computation time and human intervention. Robust software is required to gather the data and provide easy access to the collected information. Apart for commercial engines, there have been only a few attempts to perform such task and to make the data available. Several previous works (e.g., ntoulas2004what,toyoda2006what ) analyzed a sequence of crawls, studying degree and frequency of change both in the content of Web pages and in the hyperlink structure to propose measures of their novelty. In this paper we study a temporal dataset BSVLTAG that has recently been made public. It is made of twelve 100M pages snapshots of the .uk domain. The Web graphs of the single snapshots have been merged into a global graph with labels that provide constant time access to temporal information. bordino2008temporal describes the work done to assess the data and to study some aspects of its evolution at the level of Web pages. We now analyze the structure of this huge time-aware graph at the level of interconnection between hosts. We study the , i.e., the graph in which every node corresponds to a site, whereas a directed edge represents the existence of hyperlinks between pages belonging to two different hosts. Understanding the graph structure of the Web at this macroscopic level can provide valuable insights for improving Web site accessibility and navigation, or discovering related hosts. The notion of hostgraph was proposed by bharat2001who . A few studies analyzed hostgraphs ( baeza2005spain,liu2005china,toyoda2008thai ). baeza2007domain presents a comparison among the results of twelve characterization studies of several national domains. Over the years, the web has evolved from simple text content from one server to a complex ecosystem with different types of content from servers spread across several administrative domains. There is anecdotal evidence of users being frustrated with high page load times or when obscure scripts cause their browser windows to freeze. Because page load times are known to directly impact user satisfaction, providers would like to understand if and how the complexity of their websites affects the user experience. While there is an extensive literature on measuring web graphs, website popularity, and the nature of web traffic, there has been little work in understanding how complex individual websites are, and how this complexity impacts the clients' experience. This paper is a first step to address this gap. To this end, we identify a set of metrics to characterize the complexity of websites both at a content-level (e.g., number and size of images) and service-level (e.g., number of servers origins). We find that the distributions of these metrics are largely independent of a website's popularity rank. However, some categories (e.g., News) are more complex than others. More than 60 of websites have content from at least 5 non-origin sources and these contribute more than 35 of the bytes downloaded. In addition, we analyze which metrics are most critical for predicting page render and load times and find that the number of objects requested is the most important factor. With respect to variability in load times, however, we find that the number of servers is the best indicator. In a document network such as a citation network of scientific documents, web-logs, etc., the content produced by authors exhibits their interest in certain topics. In addition some authors influence other authors' interests. In this work, we propose to model the influence of cited authors along with the interests of citing authors. Moreover, we hypothesize that apart from the citations present in documents, the context surrounding the citation mention provides extra topical information about the cited authors. However, associating terms in the context to the cited authors remains an open problem. We propose novel document generation schemes that incorporate the context while simultaneously modeling the interests of citing authors and influence of the cited authors. Our experiments show significant improvements over baseline models for various evaluation criteria such as link prediction between document and cited author, and quantitatively explaining unseen text. Online advertising drives the economy of the World Wide Web. Modern websites of any size and popularity include advertisements to monetize visits from their users. To this end, they assign an area of their web page to an advertising company (so called ad exchange) that will use it to display promotional content. By doing this, the website owner implicitly trusts that the advertising company will offer legitimate content and it will not put the site's visitors at risk of falling victims of malware campaigns and other scams. In this paper, we perform the first large-scale study of the safety of the advertisements that are encountered by the users on the Web. In particular, we analyze to what extent users are exposed to malicious content through advertisements, and investigate what are the sources of this malicious content. Additionally, we show that some ad exchanges are more prone to serving malicious advertisements than others, probably due to their deficient filtering mechanisms. The observations that we make in this paper shed light on a little studied, yet important, aspect of advertisement networks, and can help both advertisement networks and website owners in securing their web pages and in keeping their visitors safe. The World Wide Web is becoming a source of information for researchers, who are more aware of the possibilities for collections of Internet content as resources. Some have begun creating archives of web content for social science and humanities research. However, there is a growing gulf between policies shared between global and national institutions creating web archives and the practices of researchers making use of the archives. Each set of stakeholders finds the others’ web archiving contributions less applicable to their own field. Institutions find the contributions of researchers to be too narrow to meet the needs of the institution’s audience, and researchers find the contributions of institutions to be too broad to meet the needs of their research methods. Resources are extended to advance both institutional and researcher tools, but the gulf between the two is persistent. Institutions generally produce web archives that are broad in scope but with limited access and enrichment tools. The design of common access interfaces, such as the Internet Archive’s Wayback Machine, limit access points to archives to only URL and date. This narrow access limits the ways in which web archives can be valuable for exploring research questions in the humanities and social sciences. Individual scholars, in catering to their own disciplinary and methodological needs, produce web archives that are narrow in scope, and whose access and enrichment tools are personalized to work within the boundaries of the project for which the web archive was built. There is no way to explore a subset of an archive by topic, event, or idea. The current search paradigm in web archiving access tools is built primarily on retrieval, not discovery. We suggest that there is a need for extensible tools to enhance access to and enrichment of web archives to make them more readily reusable and so, more valuable for both institutions and researchers, and that annotation activities can serve as one potential guide for development of such tools to bridge the divide. Purpose – The purpose of this paper is to suggest an alternative to the widely used Times Cited criterion for analysing citation networks. The approach involves taking account of the natures of the papers that cite a given paper, so as to differentiate between papers that attract the same number of citations.Design methodology approach – ArticleRank is an algorithm that has been derived from Google's PageRank algorithm to measure the influence of journal articles. ArticleRank is applied to two datasets – a citation network based on an early paper on webometrics, and a self‐citation network based on the 19 most cited papers in the Journal of Documentation – using citation data taken from the Web of Knowledge database.Findings – ArticleRank values provide a different ranking of a set of papers from that provided by the corresponding Times Cited values, and overcomes the inability of the latter to differentiate between papers with the same numbers of citations. The difference in rankings between Times Cited ... The web is one of the most popular vectors to spread malware. Attackers lure victims to visit compromised web pages or entice them to click on malicious links. These victims are redirected to sites that exploit their browsers or trick them into installing malicious software using social engineering. In this paper, we tackle the problem of detecting malicious web pages from a novel angle. Instead of looking at particular features of a (malicious) web page, we analyze how a large and diverse set of web browsers reach these pages. That is, we use the browsers of a collection of web users to record their interactions with websites, as well as the redirections they go through to reach their final destinations. We then aggregate the different redirection chains that lead to a specific web page and analyze the characteristics of the resulting redirection graph. As we will show, these characteristics can be used to detect malicious pages. We argue that our approach is less prone to evasion than previous systems, allows us to also detect scam pages that rely on social engineering rather than only those that exploit browser vulnerabilities, and can be implemented efficiently. We developed a system, called SpiderWeb, which implements our proposed approach. We show that this system works well in detecting web pages that deliver malware. With its seemingly limitless scope, the World Wide Web promises enormous advantages, along with enormous problems, to researchers who seek to use it as a source of data. Websites change continually and a high level of flux makes it challenging to capture a snapshot of the web, or even a cross-section of a small subset of the web. A web archive, such as those at the Internet Archive, promises to store and deliver repeated cross-sections of the entire web, and it also offers the potential for longitudinal analysis. Whether this potential is realized depends on the extent to which the archive has truly captured the web. Therefore, a crucial question for Internet researchers is: ‘How good are the archival data?’ We ask if there are systematic biases in the Internet Archive, using a case study to address this question. Specifically, we are interested in whether biases exist in the British websites stored in the Internet Archive data. We find that the Internet Archive contains a surprisingly small subset, about 24 , of the webpages of the website that we use for our case study (the travel site, TripAdvisor). Furthermore, the subset of data we found in the Internet Archive appears to be biased and is not a random sample of the webpages on the site. The archived data we examine has a bias toward prominent webpages. This bias could create serious problems for research using archived websites. JavaScript is used by web developers to enhance the interactivity of their sites, offload work to the users' browsers and improve their sites' responsiveness and user-friendliness, making web pages feel and behave like traditional desktop applications. An important feature of JavaScript, is the ability to combine multiple libraries from local and remote sources into the same page, under the same namespace. While this enables the creation of more advanced web applications, it also allows for a malicious JavaScript provider to steal data from other scripts and from the page itself. Today, when developers include remote JavaScript libraries, they trust that the remote providers will not abuse the power bestowed upon them. In this paper, we report on a large-scale crawl of more than three million pages of the top 10,000 Alexa sites, and identify the trust relationships of these sites with their library providers. We show the evolution of JavaScript inclusions over time and develop a set of metrics in order to assess the maintenance-quality of each JavaScript provider, showing that in some cases, top Internet sites trust remote providers that could be successfully compromised by determined attackers and subsequently serve malicious JavaScript. In this process, we identify four, previously unknown, types of vulnerabilities that attackers could use to attack popular web sites. Lastly, we review some proposed ways of protecting a web application from malicious remote scripts and show that some of them may not be as effective as previously thought. A citing sentence is one that appears in a scientific article and cites previous work. Citing sentences have been studied and used in many applications. For example, they have been used in scientific paper summarization, automatic survey generation, paraphrase identification, and citation function classification. Citing sentences that cite multiple papers are common in scientific writing. This observation should be taken into consideration when using citing sentences in applications. For instance, when a citing sentence is used in a summary of a scientific paper, only the fragments of the sentence that are relevant to the summarized paper should be included in the summary. In this paper, we present and compare three different approaches for identifying the fragments of a citing sentence that are related to a given target reference. Our methods are: word classification, sequence labeling, and segment classification. Our experiments show that segment classification achieves the best results. Abstract Documents in computer-readable form can be used to provide information about other documents, i.e. those they cite. To do this efficiently requires procedures for computer recognition of citing statements. This is not easy, especially for multi-sentence citing statements. Computer recognition procedures have been developed which are accurate to the following extent: 73 of the words in statements selected by computer procedures as being citing statements are words which are correctly attributable to the corresponding documents. The retrieval effectiveness of computer-recognized citing statements was tested in the following way. First, for eight retrieval requests in inorganiic chemistry, average recall by search of Chemical Abstracts Service indexing and Chemical Abstracts abstract text words was found to be 50 . Words from citing statements referring to the papers to be retrieved were then added to the index terms and abstract words as additional access points, and searching was repeated. Average recall increased to 70 . Only words from citing statements published within a year of the cited papers were used. The retrieval effect of citing statement words alone (published within a year) without index or abstract terms was the following: average recall was 40 . When just the words of the titles of the cited papers were added to those citing statement words, average recall increased to 50 . Citation relationship between scientific publications has been successfully used for scholarly bibliometrics, information retrieval and data mining tasks, and citation-based recommendation algorithms are well documented. While previous studies investigated citation relations from various viewpoints, most of them share the same assumption that, if paper1 cites paper2 (or author1 cites author2), they are connected, regardless of citation importance, sentiment, reason, topic, or motivation. However, this assumption is oversimplified. In this study, we employ an innovative "context-rich heterogeneous network" approach, which paves a new way for citation recommendation task. In the network, we characterize 1) the importance of citation relationships between citing and cited papers, and 2) the topical citation motivation. Unlike earlier studies, the citation information, in this paper, is characterized by citation textual contexts extracted from the full-text citing paper. We also propose algorithm to cope with the situation when large portion of full-text missing information exists in the bibliographic repository. Evaluation results show that, context-rich heterogeneous network can significantly enhance the citation recommendation performance. We present a study which investigated how and why users of Mozilla Firefox use multiple tabs and windows during web browsing. The detailed web browsing usage of 21 participants was logged over a period of 13 to 21 days each, and was supplemented by qualitative data from diary entries and interviews. Through an examination of several measures of their tab usage, we show that our participants had a strong preference for the use of tabs rather than multiple windows. We report the reasons they cited for using tabs, and the advantages over multiple windows. We identify several common tab usage patterns which browsers could explicitly support. Finally, we look at how tab usage affects web page revisitation. Most of our participants switched tabs more often than they used the back button, making tab switching the second most important navigation mechanism in the browser, after link clicking. In this paper we present the results of a study into the persistence and availability of web resources referenced from papers in scholarly repositories. Two repositories with different characteristics, arXiv and the UNT digital library, are studied to determine if the nature of the repository, or of its content, has a bearing on the availability of the web resources cited by that content. Memento makes it possible to automate discovery of archived resources and to consider the time between the publication of the research and the archiving of the referenced URLs. This automation allows us to process more than 160000 URLs, the largest known such study, and the repository metadata allows consideration of the results by discipline. The results are startling: 45 (66096) of the URLs referenced from arXiv still exist, but are not preserved for future generations, and 28 of resources referenced by UNT papers have been lost. Moving forwards, we provide some initial recommendations, including that repositories should publish URL lists extracted from papers that could be used as seeds for web archiving systems.