Relevant bibliographies by topics / Web Analytics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Web Analytics'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 March 2023

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Journal articles on the topic "Web Analytics"

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Sharma, Manu, and Sudhanshu Joshi. "Online Advertisement Using Web Analytics Software." International Journal of Business Analytics 7, no. 2 (April 2020): 13–33. http://dx.doi.org/10.4018/ijban.2020040102.

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This article describes a analytic-hierarchy-process (AHP) application to identify and evaluate the best online advertising analytics software. This technique is multi-criteria and used in this study by comparing the top four web advertising analytics software. AHP uses pair-wise comparison of matrices. There are six criteria identified for evaluation: Ad scheduling, ad targeting, creative banner rotation, features, performance, cost and for each criterion, a matrix of pair-wise comparison with web-analytics software i.e. Google analytics, Accenture Analytics, Funnel and, Moat Analytics were evaluated. AHP is an effective method for multi-objective decision-making, and optimization. Thus, it helps web advertisers to evaluate the existing web advertising analytics software for posting their web advertisements.
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Iyer, Lakshmi S., and Rajeshwari M. Raman. "Intelligent Analytics." International Journal of Business Intelligence Research 2, no. 1 (January 2011): 31–45. http://dx.doi.org/10.4018/jbir.2011010103.

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Organizations use web analytic tools and technologies to measure, collect, analyze, and report web usage data to help optimize websites. Traditionally, most of this data tends to be non-transactional and non-identifiable. In this regard, there has not been much integration with transactional data that is collected, stored, analyzed, and reported through Business Intelligence (BI). Emerging trends in web analytics provide organizations the ability to aggregate and analyze web analytics data with transactional data to provide valuable insights for building better customer relationship strategies. In this paper, the authors give an overview of web analytics tools, key players, new technology trends and capabilities to integrate web analytics with BI so organizations can leverage intelligent analytics for new marketing initiatives. While the benefits are significant, there are some challenges associated with the integration and a few possible solutions to address.
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Peterson, Eric T. "Competing on web analytics." Journal of Direct, Data and Digital Marketing Practice 10, no. 3 (January 2009): 214–22. http://dx.doi.org/10.1057/dddmp.2008.38.

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Tandoc, Edson C. "Why Web Analytics Click." Journalism Studies 16, no. 6 (August 14, 2014): 782–99. http://dx.doi.org/10.1080/1461670x.2014.946309.

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Jansen, Bernard J. (Jim). "Understanding User-Web Interactions via Web Analytics." Synthesis Lectures on Information Concepts, Retrieval, and Services 1, no. 1 (January 2009): 1–102. http://dx.doi.org/10.2200/s00191ed1v01y200904icr006.

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Mandal, Sukumar. "Real Time Visualization of DSpace Usage: An Integrated Framework for Libraries." Asian Journal of Information Science and Technology 9, no. 1 (February 5, 2019): 55–57. http://dx.doi.org/10.51983/ajist-2019.9.1.2619.

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Web analytics is also known as cloud analytics which helps to display the information regarding site metrics from massive data. This can be achieved in two ways via the user’s web browser such as statistical and visualization of a particular digital web based interface. This paper explores high level digital archiving software by integration of DSpace with web analytics popular tool Piwik. The paper discusses to create a single window web analytic interface to represent the user log and present the DSpace Usage. For this the researchers select DSpace, an open source software as it is free and popular. They integrate DSpace software with Piwik web analytic tool. Piwik, a web analytic interface tool has been chosen due to its successful integration with DSpace and it is also a free web analytics tool. The whole integration is being performed in Ubuntu operating system due to its reliability and good rate of performance. After successful integration of DSpace with Piwik in Ubuntu Operating System, researchers found that there are multiple colourful link icons showing the different community, sub-community, collection and metadata. It will also display statistical visual graph showing unique visitors, average visit duration, page views, downloads, average generation time page views, unique page views total searches on your website, unique keywords downloads, etc. Through this web analytic interface, DSpace usage may be measured easily and the users’ trend at present will be displayed to rectify any demerits behind this.
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Ogunmola, Gabriel Ayodeji, and Vikas Kumar. "Web Analytics and Online Retail." International Journal of Technoethics 11, no. 2 (July 2020): 18–33. http://dx.doi.org/10.4018/ijt.2020070102.

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Currently, all major e-retailers and even the start-ups have incorporated web analytics services on their websites to monitor customer behaviour while extracting personal data. However, the web analytics data collection methods and the applications of such collected data have raised a lot of concerns regarding the ethical use of this data. The present work identifies some important ethical challenges and unethical practices that have cropped up with the usage of these techniques. The research also suggests the measures to reduce the volume and type of personal data that can be monitored by the websites/applications at the user level. It also elaborates on measures and requirements that need to be undertaken by the online retailers at the policy level to meet the country and industry standards, while keeping their practices ethical.
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Yap, Alexander Y. "Web Portals for Financial Analytics." International Journal of Web Portals 5, no. 3 (July 2013): 1–18. http://dx.doi.org/10.4018/ijwp.2013070101.

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As more investors and traders globally manage their own stock portfolio without the help of human brokers, there is an increasing need to acquire and use financial knowledge and financial data analytics to ensure that a self-maintained financial portfolio is soundly managed. There are a growing number of special web portals that provide financial analytics services for investors and traders who demand detailed analyses of their stocks and other financial derivatives. The objective of this paper is to examine how end-users value the overall usefulness of web portals that provide financial analytics services and capabilities. This research endeavors to identify different unique features of financial analytics web portals, and ask users which of these features prove to be highly useful for their needs in analyzing when to buy, hold, and sell stocks.
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Tandoc, Edson C., and Ryan J. Thomas. "The Ethics of Web Analytics." Digital Journalism 3, no. 2 (May 2014): 243–58. http://dx.doi.org/10.1080/21670811.2014.909122.

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Trišić, Marko, Bojan Milosavljević, and Ljubiša Lukić. "Web analytics of social networks." Trendovi u poslovanju 2, no. 2 (2014): 55–63. http://dx.doi.org/10.5937/trendpos1402055t.

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Dissertations / Theses on the topic "Web Analytics"

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Mužík, Zbyněk. "Web Analytics." Master's thesis, Vysoká škola ekonomická v Praze, 2006. http://www.nusl.cz/ntk/nusl-295.

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Práce se zabývá problematikou měření ukazatelů souvisejících s provozem webových stránek a aplikací a technologickými prostředky k tomu sloužícími ? Web Analytics (WA). Hlavním cílem práce je otestovat a porovnat vybrané zástupce těchto nástrojů a podrobit je srovnání podle objektivních kriterií, dále také kritické zhodnocení možností WA nástrojů obecně. V první části se práce zaměřuje na popis různých způsobů měření provozu na WWW a definuje související metriky. Poskytuje také přehled dostupných WA nástrojů. Následně je vytvořen hodnotící model pro WA nástroje a podle něj je ohodnoceno šest zástupců těchto nástrojů. Hodnocení má podobu uživatelského testování na datech ze dvou reálných webových stránek. Majitelům těchto dvou webových stránek je učiněno doporučení pro volbu vhodného WA nástroje na základě jejich preferencí. Dalším výstupem práce jsou reporty, vygenerované testovanými nástroji, popisující aktivity na zkoumaných webových stránkách.
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Dakela, Sibongiseni. "Web analytics strategy: a model for adopting and implementing advanced Web Analytics." Doctoral thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/10288.

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Includes bibliographical references (leaves 290-306).
Web Analytics (WA) is an evaluative technique originating from and driven by business in its need to get more value out of understanding the usage of its Web sites and strategies therein. It is the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimising Web usage for the online visitor, the online customer and the business with Web site presence. Current WA practice is criticised because it involves mostly raw statistics and therefore the practice tends to be inconsistent and misleading. Using grounded action research, personal observations and a review of online references, the study reviews the current state of WA to to propose an appropriate model and guidelines for a Web Analytics adoption and implementation in an electronic commerce organisation dealing with online marketing.
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Greco, Melania <1989&gt. ""Web Analytics per il marketing"." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/7804.

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Web Analytics come strumento per l'elaborazione di un piano di marketing per una realtà virtuale. Viene approfondito il rapporto one to one con l'utente finale in una realtà virtuale dove l'esperienza d'acquisto non passa attraverso il contatto diretto con l'oggetto ma attraverso un percorso di customer relationship management che parte dalla segmentazione fino ad arrivare ad attività di direct marketing pensate ad hoc.
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Carle, William R. II. "Active Analytics: Adapting Web Pages Automatically Based on Analytics Data." UNF Digital Commons, 2016. http://digitalcommons.unf.edu/etd/629.

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Web designers are expected to perform the difficult task of adapting a site’s design to fit changing usage trends. Web analytics tools give designers a window into website usage patterns, but they must be analyzed and applied to a website's user interface design manually. A framework for marrying live analytics data with user interface design could allow for interfaces that adapt dynamically to usage patterns, with little or no action from the designers. The goal of this research is to create a framework that utilizes web analytics data to automatically update and enhance web user interfaces. In this research, we present a solution for extracting analytics data via web services from Google Analytics and transforming them into reporting data that will inform user interface improvements. Once data are extracted and summarized, we expose the summarized reports via our own web services in a form that can be used by our client side User Interface (UI) framework. This client side framework will dynamically update the content and navigation on the page to reflect the data mined from the web usage reports. The resulting system will react to changing usage patterns of a website and update the user interface accordingly. We evaluated our framework by assigning navigation tasks to users on the UNF website and measuring the time it took them to complete those tasks, one group with our framework enabled, and one group using the original website. We found that the group that used the modified version of the site with our framework enabled was able to navigate the site more quickly and effectively.
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Dibrova, Alisa. "Web analytics. Website analysis with Google Analytics and Yandex Metrics." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22200.

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The scope of my research is web analytics. This paper describes the process of usability analysis of the website belonging to a company Sharden Hus situated in Stockholm. From the many existing tools of web analysis I chose two the most popular ones, Google Analytics and Yandex Metrics. In similar projects that I have read, the website redesign was based on both quantitative, statistical, and qualitative (user interviews, user tests) data. In contrast to the previously carried out projects on websites improvement with the help of similar tools, I decided to base the changes on the website only on quantitative data obtained with Google and Yandex counters. This was done in order to determine whether and how Google and Yandex tools can improve the website performance. And to see if web analytics counters may provide with sufficient statistical data enough for it's correct interpretation by a web analytics designer which would lead to the improvement of the web site performance.The results of my study showed that Google and Yandex counters isolated from qualitative methods can improve the website performance. In particular, the number of visits from the territory of Sweden was increased to almost double; the overall bounce rate reduced; the number of visits to the page containing order forms significantly increased.
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Govind. "Entity-level Event Impact Analytics." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMC260/document.

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Notre société est de plus en plus présente sur le Web. En conséquence, une grande partie des événements quotidiens a vocation à être numérisée. Dans ce cadre, le Web contient des descriptions de divers événements du monde réel et provenant du monde entier. L'ampleur de ces événements peut varier, allant de ceux pertinents uniquement localement à ceux qui retiennent l'attention du monde entier. La presse et les médias sociaux permettent d’atteindre une diffusion presque mondiale. L’ensemble de toutes ces données décrivant des événements sociétaux potentiellement complexes ouvre la porte à de nombreuses possibilités de recherche pour analyser et mieux comprendre l'état de notre société.Dans cette thèse, nous étudions diverses tâches d’analyse de l’impact des événements sociétaux. Plus précisément, nous abordons trois facettes dans le contexte des événements et du Web, à savoir la diffusion d’événements dans des communautés de langues étrangères, la classification automatisée des contenus Web et l’évaluation et la visualisation de la viralité de l’actualité. Nous émettons l'hypothèse que les entités nommées associées à un événement ou à un contenu Web contiennent des informations sémantiques précieuses, qui peuvent être exploitées pour créer des modèles de prédiction précis. À l'aide de nombreuses études, nous avons montré que l'élévation du contenu Web au niveau des entités saisissait leur essence essentielle et offrait ainsi une variété d'avantages pour obtenir de meilleures performances dans diverses tâches. Nous exposons de nouvelles découvertes sur des tâches disparates afin de réaliser notre objectif global en matière d'analyse de l’impact des événements sociétaux
Our society has been rapidly growing its presence on the Web, as a consequence we are digitizing a large collection of our daily happenings. In this scenario, the Web receives virtual occurrences of various events corresponding to their real world occurrences from all around the world. Scale of these events can vary from locally relevant ones up to those that receive global attention. News and social media of current times provide all essential means to reach almost a global diffusion. This big data of complex societal events provide a platform to many research opportunities for analyzing and gaining insights into the state of our society.In this thesis, we investigate a variety of social event impact analytics tasks. Specifically, we address three facets in the context of events and the Web, namely, diffusion of events in foreign languages communities, automated classification of Web contents, and news virality assessment and visualization. We hypothesize that the named entities associated with an event or a Web content carry valuable semantic information, which can be exploited to build accurate prediction models. We have shown with the help of multiple studies that raising Web contents to the entity-level captures their core essence, and thus, provides a variety of benefits in achieving better performance in diverse tasks. We report novel findings over disparate tasks in an attempt to fulfill our overall goal on societal event impact analytics
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Berky, Levente. "Vizualizace dat pro Ansible Automation Analytics." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445590.

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Tato práce se zaměřuje na vytvoření webové komponenty k vykreslení grafů ze strukturovanýho datovýho formátu (dále jen schéma) a vytvoření uživatelského rozhraní pro editaci schématu pro Ansible Automation Analytics. Práce zkoumá aktuální implementaci Ansible Automation Analytics a odpovídající API. Dále zkoumá vhodné knihovny pro vykreslování grafů a popisuje základy použitých technologií. Praktická část popisuje požadavky na komponentu a popisuje vývoj a implementaci pluginu. Dále práce popisuje proces testování a~plány budoucího vývoje pluginu.
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Weida, Petr. "Využití Google Analytics v eshopu." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-85117.

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The main aim of this work is describing and explaining the possibilities of web analytics as a tool for effective evaluation of the web and campaigns performance. The benefit appreciate everybody, who makes decision on further web development and its marketing based on measured data. The work is divided into three main parts. The first describes how set up Google Analytics for measuring the web, the second part shows how read and interpret the measured data. In the third practical part are both applied for analyzing prohifi.cz shop.
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Yan, Hui. "Data analytics and crawl from hidden web databases." Thesis, University of Macau, 2015. http://umaclib3.umac.mo/record=b3335862.

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Roatis, Alexandra. "Efficient Querying and Analytics of Semantic Web Data." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112218/document.

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L'utilité et la pertinence des données se trouvent dans l'information qui peut en être extraite.Le taux élevé de publication des données et leur complexité accrue, par exemple dans le cas des données du Web sémantique autodescriptives et hétérogènes, motivent l'intérêt de techniques efficaces pour la manipulation de données.Dans cette thèse, nous utilisons la technologie mature de gestion de données relationnelles pour l'interrogation des données du Web sémantique.La première partie se concentre sur l'apport de réponse aux requêtes sur les données soumises à des contraintes RDFS, stockées dans un système de gestion de données relationnelles. L'information implicite, résultant du raisonnement RDF est nécessaire pour répondre correctement à ces requêtes.Nous introduisons le fragment des bases de données RDF, allant au-delà de l'expressivité des fragments étudiés précédemment.Nous élaborons de nouvelles techniques pour répondre aux requêtes dans ce fragment, en étendant deux approches connues de manipulation de données sémantiques RDF, notamment par saturation de graphes et reformulation de requêtes.En particulier, nous considérons les mises à jour de graphe au sein de chaque approche et proposerons un procédé incrémental de maintenance de saturation. Nous étudions expérimentalement les performances de nos techniques, pouvant être déployées au-dessus de tout moteur de gestion de données relationnelles.La deuxième partie de cette thèse considère les nouvelles exigences pour les outils et méthodes d'analyse de données, issues de l'évolution du Web sémantique.Nous revisitons intégralement les concepts et les outils pour l'analyse de données, dans le contexte de RDF.Nous proposons le premier cadre formel pour l'analyse d'entrepôts RDF. Notamment, nous définissons des schémas analytiques adaptés aux graphes RDF hétérogènes à sémantique riche, des requêtes analytiques qui (au-delà de cubes relationnels) permettent l'interrogation flexible des données et schémas, ainsi que des opérations d'agrégation puissantes de type OLAP. Des expériences sur une plateforme entièrement implémentée démontrent l'intérêt pratique de notre approche
The utility and relevance of data lie in the information that can be extracted from it.The high rate of data publication and its increased complexity, for instance the heterogeneous, self-describing Semantic Web data, motivate the interest in efficient techniques for data manipulation.In this thesis we leverage mature relational data management technology for querying Semantic Web data.The first part focuses on query answering over data subject to RDFS constraints, stored in relational data management systems. The implicit information resulting from RDF reasoning is required to correctly answer such queries. We introduce the database fragment of RDF, going beyond the expressive power of previously studied fragments. We devise novel techniques for answering Basic Graph Pattern queries within this fragment, exploring the two established approaches for handling RDF semantics, namely graph saturation and query reformulation. In particular, we consider graph updates within each approach and propose a method for incrementally maintaining the saturation. We experimentally study the performance trade-offs of our techniques, which can be deployed on top of any relational data management engine.The second part of this thesis considers the new requirements for data analytics tools and methods emerging from the development of the Semantic Web. We fully redesign, from the bottom up, core data analytics concepts and tools in the context of RDF data. We propose the first complete formal framework for warehouse-style RDF analytics. Notably, we define analytical schemas tailored to heterogeneous, semantic-rich RDF graphs, analytical queries which (beyond relational cubes) allow flexible querying of the data and the schema as well as powerful aggregation and OLAP-style operations. Experiments on a fully-implemented platform demonstrate the practical interest of our approach
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Books on the topic "Web Analytics"

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Kaushik, Avinash. Web Analytics. New York: John Wiley & Sons, Ltd., 2009.

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Mortensen, Dennis R. Yahoo! Web Analytics. New York: John Wiley & Sons, Ltd., 2009.

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Web analytics: Méthode pour l'analyse Web. Paris: Pearson, 2012.

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Sostre, Pedro. Web Analytics For Dummies. New York: John Wiley & Sons, Ltd., 2007.

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Jennifer, LeClaire, ed. Web analytics for dummies. Hoboken, NJ: Wiley Pub., 2007.

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Miller, Stephen. Piwik Web Analytics Essentials. Birmingham: Packt Publishing, Limited, 2012.

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Jim Jansen, Bernard J. Understanding User-Web Interactions via Web Analytics. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-02264-7.

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Understanding user-Web interactions via Web analytics. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2009.

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Amthor, Axel, and Thomas Brommund. Mehr Erfolg durch Web Analytics. München: Carl Hanser Verlag GmbH & Co. KG, 2010. http://dx.doi.org/10.3139/9783446424081.

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L, Ledford Jerri, ed. Google Analytics. Indianapolis, IN: Wiley Technology Pub., 2007.

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Book chapters on the topic "Web Analytics"

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Jansen, Bernard J. Jim. "Understanding Web Analytics." In Understanding User-Web Interactions via Web Analytics, 1–4. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-02264-7_1.

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Jim Jansen, Bernard J. "Web Analytics Strategy." In Understanding User-Web Interactions via Web Analytics, 35–40. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-02264-7_6.

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Fletcher, Peter. "Analytics Techniques." In Practical Web Traffic Analysis, 8–37. Berkeley, CA: Apress, 2002. http://dx.doi.org/10.1007/978-1-4302-5366-2_2.

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Sankar, M. Mallika, Fezeena Khadir, and P. Senthilmurugan. "Web and Social Media Analytics." In Marketing Analytics, 303–21. New York: Apple Academic Press, 2022. http://dx.doi.org/10.1201/9781003300632-14.

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Jim Jansen, Bernard J. "Web Analytics as Competitive Intelligence." In Understanding User-Web Interactions via Web Analytics, 41–49. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-02264-7_7.

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Jim Jansen, Bernard J. "The History of Web Analytics." In Understanding User-Web Interactions via Web Analytics, 21–24. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-02264-7_3.

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Jim Jansen, Bernard J. "Data Collection for Web Analytics." In Understanding User-Web Interactions via Web Analytics, 25–28. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-02264-7_4.

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Dawson, Catherine. "Web and mobile analytics." In A–Z of Digital Research Methods, 390–97. Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9781351044677-59.

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Bélair-Gagnon, Valérie. "Web analytics in journalism." In The Institutions Changing Journalism, 153–64. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003140399-14.

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Katsiri, Eli, George Papastefanatos, Manolis Terrovitis, and Timos Sellis. "Airport Context Analytics." In Web Reasoning and Rule Systems, 179–84. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11113-1_13.

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Conference papers on the topic "Web Analytics"

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Kumar, Lakhwinder, Hardeep Singh, and Ramandeep Kaur. "Web analytics and metrics." In the International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2345396.2345552.

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Akkus, Istemi Ekin, Ruichuan Chen, Michaela Hardt, Paul Francis, and Johannes Gehrke. "Non-tracking web analytics." In the 2012 ACM conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2382196.2382268.

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Tommasini, Riccardo, Robin Keskisärkkä, Jean-Paul Calbimonte, Eva Blomqvist, Emanuele Della Valle, and Albert Bifet. "Continuous Analytics of Web Streams." In WWW '19: The Web Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3308560.3320088.

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Kirsh, Ilan, and Mike Joy. "Splitting the Web Analytics Atom." In WIMS 2020: The 10th International Conference on Web Intelligence, Mining and Semantics. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3405962.3405984.

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Glass, Kristin, and Richard Colbaugh. "Web Analytics for Security Informatics." In 2011 European Intelligence and Security Informatics Conference (EISIC). IEEE, 2011. http://dx.doi.org/10.1109/eisic.2011.66.

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Padmanaban, R., M. Thirumaran, Victoria Sanjana, and A. Moshika. "Security Analytics For Heterogeneous Web." In 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN). IEEE, 2019. http://dx.doi.org/10.1109/icscan.2019.8878832.

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Cegan, Lukas, and Petr Filip. "Webalyt: Open web analytics platform." In 2017 27th International Conference Radioelektronika (RADIOELEKTRONIKA). IEEE, 2017. http://dx.doi.org/10.1109/radioelek.2017.7937605.

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Le Quoc, Do, Franz Gregor, Jatinder Singh, and Christof Fetzer. "SGX-PySpark: Secure Distributed Data Analytics." In WWW '19: The Web Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3308558.3314129.

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Li, Cheng-Te, and Hsun-Ping Hsieh. "Geo-Social Media Analytics." In WWW '15: 24th International World Wide Web Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2740908.2741985.

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Boldi, Paolo. "Large-scale Network Analytics." In WWW '15: 24th International World Wide Web Conference. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2740908.2741703.

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Reports on the topic "Web Analytics"

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Young, Scott W. H., Jason A. Clark, Sara Mannheimer, and Lisa Janicke Hinchliffe. A National Forum on Web Privacy and Web Analytics: Action Handbook. Montana State University, April 2019. http://dx.doi.org/10.15788/20190416.15446.

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Young, Scott W. H., Jason A. Clark, Sara Mannheimer, and Lisa Janicke Hinchliffe. A Roadmap for Achieving Privacy in the Age of Analytics: A White Paper from A National Forum on Web Privacy and Web Analytics. Montana State University, April 2019. http://dx.doi.org/10.15788/20190416.15445.

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Mazorchuk, Mariia S., Tetyana S. Vakulenko, Anna O. Bychko, Olena H. Kuzminska, and Oleksandr V. Prokhorov. Cloud technologies and learning analytics: web application for PISA results analysis and visualization. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4451.

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This article analyzes the ways to apply Learning Analytics, Cloud Technologies, and Big Data in the field of education on the international level. This paper provides examples of international analytical researches and cloud technologies used to process the results of those researches. It considers the PISA research methodology and related tools, including the IDB Analyzer application, free R intsvy environment for processing statistical data, and cloud-based web application PISA Data Explorer. The paper justifies the necessity of creating a stand-alone web application that supports Ukrainian localization and provides Ukrainian researchers with rapid access to well-structured PISA data. In particular, such an application should provide for data across the factorial features and indicators applied at the country level and demonstrate the Ukrainian indicators compared to the other countries’ results. This paper includes a description of the application core functionalities, architecture, and technologies used for development. The proposed solution leverages the shiny package available with R environment that allows implementing both the UI and server sides of the application. The technical implementation is a proven solution that allows for simplifying the access to PISA data for Ukrainian researchers and helping them utilize the calculation results on the key features without having to apply tools for processing statistical data.
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Pascuccfi, Valerio. CyclusJS: A Distributed Web-based Fuel Cycle Visual Analytics. Research Performance Final Report/. Office of Scientific and Technical Information (OSTI), August 2022. http://dx.doi.org/10.2172/1881220.

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Shynenko, Mykola, and Olga Pinchuk. Activity of users of the web resource "Electronic Library of the National Academy of Sciences of Ukraine" during crisis events. Institute for Digitalization of Education, 2022. http://dx.doi.org/10.33407/lib.naes.733438.

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The monitoring of the use of the web resource "Electronic Library of the National Academy of Sciences of Ukraine" is aimed at providing informational and methodological support by means of the Google Analytics service in order to track the processes of visiting and using electronic resources, as well as to increase the efficiency of the development, improvement and maintenance of the electronic library site. A comparative analysis of the use of library resources for the period from March 1-May 31, 2022 to September 1-November 30, 2022 during the full-scale Russian invasion of Ukraine was performed. Also, to identify trends in changes in the activity of users of the web resource, a comparative analysis of the use of library resources was performed for the period: 2021. - 2022. The monitoring of the use of the website of the electronic library of the National Academy of Sciences of Ukraine is carried out according to the following indicators: overview of visitors, demographics of visitors, behavior of visitors on the website of the electronic library, technologies for visiting the site, mobile devices used, traffic, information of the statistical module. For scientists, post-graduate students, heads of scientific institutions of the National Academy of Sciences of Ukraine and specialists in the field of librarianship.
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Morrison, John F. Analyzing Interviews with Terrorists. RESOLVE Network, November 2020. http://dx.doi.org/10.37805/rve2020.7.

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For years the dominant narrative has been that there is a dearth of primary sources in terrorism studies. This is now changing. The talk about the scarcity of data is gradually being replaced by discussions of a “data revolution” and a “golden age” of terrorism research. We are now publishing more research based on the analysis of primary source data than ever before. Included in this has been some ground-breaking interview research with recent and former terrorists—research that could define how we think about terrorist involvement for years to come. With this increased access to data, if our research is to have any analytical value and concurrently respected both within and outside of academia, we need to actively consider how we analyze it. This chapter discusses some of the issues that need to be taken into consideration when analyzing first-hand interviews, including the importance of specificity, different available analytic techniques, the role of triangulation, and ethical practices.
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Runion, Kyle, Safra Altman, and Elizabeth Murray. Analytic methods for establishing restoration trajectories. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45562.

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This special report identifies metrics (standard and novel) and analytic approaches to developing trajectories and then describes the conceptual process of using those metrics and approaches to develop restoration trajectories to inform adaptive management in salt-marsh systems. We identify the composite time series trajectory (CTST) approach, in which metrics are measured from restoration sites of different ages within a small spatial range, and the retrospective single-site trajectory (RSST) approach, in which the same restoration metrics are measured over time at one restoration site. In all, we assessed the metrics of 39 studies of salt-marsh restoration in the United States between 1991 and 2019.
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Busso, Matías, Julian P. Cristia, Pablo Garofalo, and Julián Messina. The Effectiveness of Adult Retraining: Evidence from a Meta-Analytic Review. Inter-American Development Bank, August 2022. http://dx.doi.org/10.18235/0004418.

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We report the results of a meta-analytic review of the effectiveness of programs designed to retrain workers. The review focuses on studies that rely on identification strategies designed to obtain credible causal effects. We analyze a total of 40 programs that provided skills to unemployed workers and focus on two outcomes: the probability of finding a job and wages. We find that the probability of finding a job of program participants increases on average by 2.6 percentage points after the program and wages increase by 0.08 of a standard deviation. Programs that provide technical skills, those that combine in-classroom with on-the-job training and those provided in partnership with the private sector seem to be more effective.
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Downing, W. Logan, Howell Li, William T. Morgan, Cassandra McKee, and Darcy M. Bullock. Using Probe Data Analytics for Assessing Freeway Speed Reductions during Rain Events. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317350.

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Rain impacts roadways such as wet pavement, standing water, decreased visibility, and wind gusts and can lead to hazardous driving conditions. This study investigates the use of high fidelity Doppler data at 1 km spatial and 2-minute temporal resolution in combination with commercial probe speed data on freeways. Segment-based space-mean speeds were used and drops in speeds during rainfall events of 5.5 mm/hour or greater over a one-month period on a section of four to six-lane interstate were assessed. Speed reductions were evaluated as a time series over a 1-hour window with the rain data. Three interpolation methods for estimating rainfall rates were tested and seven metrics were developed for the analysis. The study found sharp drops in speed of more than 40 mph occurred at estimated rainfall rates of 30 mm/hour or greater, but the drops did not become more severe beyond this threshold. The average time of first detected rainfall to impacting speeds was 17 minutes. The bilinear method detected the greatest number of events during the 1-month period, with the most conservative rate of predicted rainfall. The range of rainfall intensities were estimated between 7.5 to 106 mm/hour for the 39 events. This range was much greater than the heavy rainfall categorization at 16 mm/hour in previous studies reported in the literature. The bilinear interpolation method for Doppler data is recommended because it detected the greatest number of events and had the longest rain duration and lowest estimated maximum rainfall out of three methods tested, suggesting the method balanced awareness of the weather conditions around the roadway with isolated, localized rain intensities.
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Sett, Dominic, Florian Waldschmidt, Alvaro Rojas-Ferreira, Saut Sagala, Teresa Arce Mojica, Preeti Koirala, Patrick Sanady, et al. Climate and disaster risk analytics tool for adaptive social protection. United Nations University - Institute for Environment and Human Security, March 2022. http://dx.doi.org/10.53324/wnsg2302.

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Adaptive Social Protection (ASP) as discussed in this report is an approach to enhance the well-being of communities at risk. As an integrated approach, ASP builds on the interface of Disaster Risk Management (DRM), Climate Change Adaptation (CCA) and Social Protection (SP) to address interconnected risks by building resilience, thereby overcoming the shortcomings of traditionally sectoral approaches. The design of meaningful ASP measures needs to be informed by specific information on risk, risk drivers and impacts on communities at risk. In contrast, a limited understanding of risk and its drivers can potentially lead to maladaptation practices. Therefore, multidimensional risk assessments are vital for the successful implementation of ASP. Although many sectoral tools to assess risks exist, available integrated risk assessment methods across sectors are still inadequate in the context of ASP, presenting an important research and implementation gap. ASP is now gaining international momentum, making the timely development of a comprehensive risk analytics tool even more important, including in Indonesia, where nationwide implementation of ASP is currently under way. OBJECTIVE: To address this gap, this study explores the feasibility of a climate and disaster risk analytics tool for ASP (CADRAT-ASP), combining sectoral risk assessment in the context of ASP with a more comprehensive risk analytics approach. Risk analytics improve the understanding of risks by locating and quantifying the potential impacts of disasters. For example, the Economics of Climate Adaptation (ECA) framework quantifies probable current and expected future impacts of extreme events and determines the monetary cost and benefits of specific risk management and adaptation measures. Using the ECA framework, this report examines the viability and practicality of applying a quantitative risk analytics approach for non-financial and non-tangible assets that were identified as central to ASP. This quantitative approach helps to identify cost-effective interventions to support risk-informed decision making for ASP. Therefore, we used Nusa Tenggara, Indonesia, as a case study, to identify potential entry points and examples for the further development and application of such an approach. METHODS & RESULTS: The report presents an analysis of central risks and related impacts on communities in the context of ASP. In addition, central social protection dimensions (SPD) necessary for the successful implementation of ASP and respective data needs from a theoretical perspective are identified. The application of the quantitative ECA framework is tested for tropical storms in the context of ASP, providing an operational perspective on technical feasibility. Finally, recommendations on further research for the potential application of a suitable ASP risk analytics tool in Indonesia are proposed. Results show that the ECA framework and its quantitative modelling platform CLIMADA successfully quantified the impact of tropical storms on four SPDs. These SPDs (income, access to health, access to education and mobility) were selected based on the results from the Hazard, Exposure and Vulnerability Assessment (HEVA) conducted to support the development of an ASP roadmap for the Republic of Indonesia (UNU-EHS 2022, forthcoming). The SPDs were modelled using remote sensing, gridded data and available global indices. The results illustrate the value of the outcome to inform decision making and a better allocation of resources to deliver ASP to the case study area. RECOMMENDATIONS: This report highlights strong potential for the application of the ECA framework in the ASP context. The impact of extreme weather events on four social protection dimensions, ranging from access to health care and income to education and mobility, were successfully quantified. In addition, further developments of CADRAT-ASP can be envisaged to improve modelling results and uptake of this tool in ASP implementation. Recommendations are provided for four central themes: mainstreaming the CADRAT approach into ASP, data and information needs for the application of CADRAT-ASP, methodological advancements of the ECA framework to support ASP and use of CADRAT-ASP for improved resilience-building. Specific recommendations are given, including the integration of additional hazards, such as flood, drought or heatwaves, for a more comprehensive outlook on potential risks. This would provide a broader overview and allow for multi-hazard risk planning. In addition, high-resolution local data and stakeholder involvement can increase both ownership and the relevance of SPDs. Further recommendations include the development of a database and the inclusion of climate and socioeconomic scenarios in analyses.
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