Open AccessProceedings Article
The PageRank Citation Ranking : Bringing Order to the Web
Lawrence Page,Sergey Brin,Rajeev Motwani,Terry Winograd +3 more
- Vol. 98, pp 161-172
TLDR
This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages.Abstract:
The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.read more
Citations
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Proceedings ArticleDOI
Ranking systems: the PageRank axioms
Alon Altman,Moshe Tennenholtz +1 more
TL;DR: A set of simple axioms that are satisfied by PageRank are presented, and moreover any page ranking algorithm that does satisfy them must coincide with PageRank, the first representation theorem of that kind, bridging the gap between page ranking algorithms and the mathematical theory of social choice.
Journal ArticleDOI
Anatomy of an online misinformation network.
Chengcheng Shao,Chengcheng Shao,Pik-Mai Hui,Lei Wang,Xinwen Jiang,Alessandro Flammini,Filippo Menczer,Giovanni Luca Ciampaglia +7 more
TL;DR: Hoaxy as discussed by the authors is an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter and quantifies how effectively the network can be disrupted by penalizing the most central nodes.
Proceedings ArticleDOI
Contextual search and name disambiguation in email using graphs
TL;DR: This paper provides a detailed instantiation of this framework for email data, where content, social networks and a timeline are integrated in a structural graph and shows that reranking schemes based on the graph-walk similarity measures often outperform baseline methods and that further improvements can be obtained by use of appropriate learning methods.
Book
Big Crisis Data: Social Media in Disasters and Time-Critical Situations
TL;DR: This book brings together computational methods from many disciplines: natural language processing, semantic technologies, data mining, machine learning, network analysis, human-computer interaction, and information visualization, focusing on methods that are commonly used for processing social media messages under time-critical constraints.
Journal ArticleDOI
Scraping the Social? Issues in live social research
Noortje Marres,Esther Weltevrede +1 more
TL;DR: In this paper, the authors explore how a "medium-specific" technique for online data capture may be rendered analytically productive for social research, and demonstrate this point in an exercise of online issue profiling, and more particularly by relying on Twitter to profile the issue of "austerity".
References
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Journal Article
The Anatomy of a Large-Scale Hypertextual Web Search Engine.
Sergey Brin,Lawrence Page +1 more
TL;DR: Google as discussed by the authors is a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems.
Journal ArticleDOI
Efficient crawling through URL ordering
TL;DR: In this paper, the authors study in what order a crawler should visit the URLs it has seen, in order to obtain more "important" pages first, and they show that a good ordering scheme can obtain important pages significantly faster than one without.
Proceedings ArticleDOI
Silk from a sow's ear: extracting usable structures from the Web
TL;DR: This paper presents the exploration into techniques that utilize both the topology and textual similarity between items as well as usage data collected by servers and page meta-information lke title and size.
Proceedings ArticleDOI
HyPursuit: a hierarchical network search engine that exploits content-link hypertext clustering
TL;DR: Experience with HyPursuit suggests that abstraction functions based on hypertext clustering can be used to construct meaningful and scalable cluster hierarchies, and is encouraged by preliminary results on clustering based on both document contents and hyperlink structures.
Journal ArticleDOI
The quest for correct information on the Web: hyper search engines
TL;DR: This paper presents a novel method to extract from a web object its “hyper” informative content, in contrast with current search engines, which only deal with the “textual’ informative content.