Predicting link directions via a recursive subgraph-based ranking

Link directions are essential to the functionality of networks and their prediction is helpful towards a better knowledge of directed networks from incomplete real-world data. We study the problem of predicting the directions of some links by using the existence and directions of the rest of links. We propose a solution by first ranking nodes in a specific order and then predicting each link as stemming from a lower-ranked node towards a higher-ranked one. The proposed ranking method works recursively by utilizing local indicators on multiple scales, each corresponding to a subgraph extracted from the original network. Experiments on real networks show that the directions of a substantial fraction of links can be correctly recovered by our method, which outperforms either purely local or global methods.Comment: 6 pages, 5 figures; revised arguments for methods section; figures replotted; minor revision

Comparing webometric with web-independent rankings: a case study with German universities

In this paper we examine if hyperlink-based (webometric) indicators can be used to rank academic websites. Therefore we analyzed the interlinking structure of German university websites and compared our simple hyperlink-based ranking with official and web-independent rankings of universities. We found that link impact could not easily be seen as a prestige factor for universities.Comment: 3 pages, ACM Web Science 201

Robustness and modular structure in networks

Complex networks have recently attracted much interest due to their prevalence in nature and our daily lives [1, 2]. A critical property of a network is its resilience to random breakdown and failure [3-6], typically studied as a percolation problem [7-9] or by modeling cascading failures [10-12]. Many complex systems, from power grids and the Internet to the brain and society [13-15], can be modeled using modular networks comprised of small, densely connected groups of nodes [16, 17]. These modules often overlap, with network elements belonging to multiple modules [18, 19]. Yet existing work on robustness has not considered the role of overlapping, modular structure. Here we study the robustness of these systems to the failure of elements. We show analytically and empirically that it is possible for the modules themselves to become uncoupled or non-overlapping well before the network disintegrates. If overlapping modular organization plays a role in overall functionality, networks may be far more vulnerable than predicted by conventional percolation theory.Comment: 14 pages, 9 figure

Imaging Informatics and the Human Brain Project: the Role of Structure, Review

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Collaboration analysis of World National Library websites via webometric methods

This article aimed to study National Library Websites (NLW) using webometric methods. The in-links and co-links to national library websites were analyzed to study: firstly, the visibility of these National libraries on the web. Secondly, the collaboration on national and international level amongst the studied national libraries websites. This study found that according to the in-link count of 38 national library websites, 3 were extremely popular and we can call them the most visible national library websites as they come below: 1. United States of America (http://www.loc.gov); 2. Australia (http://www.nla.gov.au); 3. United Kingdom (http://www.bl.uk). The results of the study also showed that, there were 5 clusters (2 cross continental and 3 international) in the studied national library websites. On the other hand, the multidimensional scaling map showed 4 major collaboration clusters: 2 cross national (both European) and 2 international (European, Asian, American, Australian). African national library websites were not seen in these clusters. It means that, African national libraries have a little collaboration with others through their websites. However, due to the problems of search engines which are used for data collection in webometric studies, this method needs to be used with cautio

Abusive Language Detection in Online Conversations by Combining Content-and Graph-based Features

In recent years, online social networks have allowed worldwide users to meet and discuss. As guarantors of these communities, the administrators of these platforms must prevent users from adopting inappropriate behaviors. This verification task, mainly done by humans, is more and more difficult due to the ever growing amount of messages to check. Methods have been proposed to automatize this moderation process, mainly by providing approaches based on the textual content of the exchanged messages. Recent work has also shown that characteristics derived from the structure of conversations, in the form of conversational graphs, can help detecting these abusive messages. In this paper, we propose to take advantage of both sources of information by proposing fusion methods integrating content-and graph-based features. Our experiments on raw chat logs show that the content of the messages, but also of their dynamics within a conversation contain partially complementary information, allowing performance improvements on an abusive message classification task with a final F-measure of 93.26%

Selective linking from social platforms to university websites: a case study of the Spanish academic system

Mention indicators have frequently been used in Webometric studies because they provide a powerful tool for determining the degree of visibility and impact of web resources. Among mention indicators, hypertextual links were a central part of many studies until Yahoo! discontinued the ¿linkdomain¿ command in 2011. Selective links constitute a variant of external links where both the source and target of the link can be selected. This paper intends to study the influence of social platforms (measured through the number of selective external links) on academic environments, in order to ascertain both the percentage that they constitute and whether some of them can be used as substitutes of total external links. For this purpose, 141 URLs belonging to 76 Spanish universities were compiled in 2010 (before Yahoo! stopped their link services), and the number of links from 13 selected social platforms to these universities were calculated. Results confirm a good correlation between total external links and links that come from social platforms, with the exception of some applications (such as Digg and Technorati). For those universities with a higher number of total external links, the high correlation is only maintained on Delicious and Wikipedia, which can be utilized as substitutes of total external links in the context analyzed. Notwithstanding, the global percentage of links from social platforms constitute only a small fraction of total links, although a positive trend is detected, especially in services such as Twitter, Youtube, and Facebook.Orduña Malea, E.; Ontalba Ruipérez, JA. (2013). Selective linking from social platforms to university websites: a case study of the Spanish academic system. Scientometrics. 95(2):593-614. doi:10.1007/s11192-012-0851-1S593614952Aguillo, I. F. (2009a). Measuring the institutions’ footprint in the web. Library Hi Tech, 27(4), 540–556.Aguillo, IF. (2009b). 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