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Journal articles on the topic 'Web Analytics'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 March 2023

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1

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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4

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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Kumar, Vikas, and Gabriel Ayodeji Ogunmola. "Web Analytics for Knowledge Creation." International Journal of Cyber Behavior, Psychology and Learning 10, no. 1 (January 2020): 1–14. http://dx.doi.org/10.4018/ijcbpl.2020010101.

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Digitization efforts across the world have resulted in the need for businesses to own a website. All Fortune 500 companies run websites for either information dissemination or for transacting business. This has led to the increase in the number of websites as well as a growing competition to outdo each other. In order to gain competitive advantage, businesses need to have a detailed track of the activities going on their website to suffice their decisive knowledge. However, to monitor and to optimise the website performance, organisations need strong web analytics tools and skills. This work presents a comprehensive review of the web analytics tools and techniques, which are vital to report the website performance and usage. Present day practices of web analytics have been outlined from the perspective of business organisations, with suitable examples. A comparative analysis of the most important web analytics tools have been presented, including the free as well as subscription based tools. Future challenges and opportunities to web analytics practices have also been presented.

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Udartseva, O. M. "World library policy in web analytics: Current state and trends." Scientific and Technical Libraries, no. 7 (September 4, 2020): 87–110. http://dx.doi.org/10.33186/1027-3689-2020-7-87-110.

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The libraries’ web-outposts open up new opportunities, enable libraries to interact efficiently with their users and to promote their information products in the virtual space. The systematic assessment is integral to high performance of libraries’ web-divisions. The author explores the intensity of applying evaluation methods to the libraries’ web-sites. She examines the current state and popular trends in libraries’ representation in the virtual space using the relevant methods of web-analytics. The findings of the 2019 survey “Modern trends in the development of library resources in the web space”, comprising 387 Russian and foreign libraries of various organizational and legal status, are discussed. Particular attention is paid to the presence of libraries in the web space and resource management using web-analytic instruments. Based on her research findings, the author concludes that the major accomplishment for the libraries today is the very fact of their presence in the web space in the form of official websites and accounts in social media. Though the respondents confirmed that they used web-based analytical tools to evaluate their own web-based representation, the survey demonstrates that just a small part of the analytical tools potentiality is actually used.

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Znakhur, Liudmyla, and Serhii Znakhur. "Implementation and rating of Web-analysis solutions based on cloud services." Bulletin of Kharkov National Automobile and Highway University, no. 96 (May 24, 2022): 35. http://dx.doi.org/10.30977/bul.2219-5548.2022.96.0.35.

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Problem. The total cost of ownership WEB-analytics of e-commerce sites is a very important aspect of the Internet business effectiveness. The thesis includes the modern solutions, architectures for solving the cross-cutting problem of creating and implementing WEB-analytics of e-commerce sites. Goal. The goal is to determine the optimal architecture of cloud services for the implementation of WEB-analytics of e-commerce sites. The object of research is the introduction of informationtechnology, services for building and implementation of ML models based on data WEB-analytics of e-commerce sites. The subject of the research is the architecture development for WEB-analytics and ML analysis of Google Analyticsdata. The scientific novelty of the work is to develop a methodology for rating cloud providers solutions which are compared according to the parameters of functionality and cost of the ownership. Methodology. The system analysis and analytical and empirical methods of research were used for development and testing of cloud solutions. Results. Solving includes investigation of the necessary tools, standards and indicators of WEB-analytics, architectures, technologies, services for the implementation of sites and integration of Google Analytics, ML solutions. Cloud solutions of different architectures were developed and tested. Practical value. Rating methodology was used for the best Cloud solutions estimation.

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Chawla, Swati, and Dr Gurdev Singh. "Understanding and Elevating Web Practice Through Web Analytics Final." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 2 (April 30, 2012): 1–5. http://dx.doi.org/10.24297/ijct.v2i1.2610.

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Web analytics is the measurement, collection, analysis and summarizing of internet data for purposes of understanding and optimizing web usage. To check the web analytics the website IJCT is considered. This paper is the first step to analyze the availability and performability of the site. Availability depicts that for how much time the system is up i.e. check the utilization of the system on which that site works.Â Performability is the method to analyze each and every module separately and clearly in an efficient manner. Availability and performability collectively check the reliability of the system to ensure the performance measurement of that system. Web analytics is not just a tool for measuring and depicting website traffic but can be used as a tool for business research and market research, as well as a means to check and improve upon the effectiveness and utilization of a web site .The tool used for the web analytics for this site is AWStats. AWStats is an open source Web analytics reporting tool, which used for analyzing the amount of data from Internet services such as web, streaming media, mail and FTP servers .This tool check the performance of the IJCT separately by dividing one month module to days in month, week in month ,hours in month ,contributionÂ of various countries, traffic generated etc. This paper deal with the securitization of IJCT for January month to indicate how many events and functionality occurs during surfing on this journal by various users on the Web. This critique helps us to identify the throughput of IJCT. Â Here it is clear that users do not actually read: instead, they download and upload the data. A study of different online journals defines that this website scored massive response instead of the short time span. It completely and efficiently elaborate the usage of the IJCT by stating user visited, number of visits,Â number of hits ,bandwidth and many more.

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Ma, Hong. "Tech Services on the Web: Google Analytics http://www.google.com/analytics/." Technical Services Quarterly 30, no. 1 (January 2013): 119–20. http://dx.doi.org/10.1080/07317131.2013.735978.

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Maldonado, Mark, and Ayad Barsoum. "Machine Learning for Web Proxy Analytics." International Journal of Cyber Research and Education 1, no. 2 (July 2019): 30–41. http://dx.doi.org/10.4018/ijcre.2019070103.

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Proxy servers used around the globe are typically graded and built for small businesses to large enterprises. This does not dismiss any of the current efforts to keep the general consumer of an electronic device safe from malicious websites or denying youth of obscene content. With the emergence of machine learning, we can utilize the power to have smart security instantiated around the population's everyday life. In this work, we present a simple solution of providing a web proxy to each user of mobile devices or any networked computer powered by a neural network. The idea is to have a proxy server to handle the functionality to allow safe websites to be rendered per request. When a website request is made and not identified in the pre-determined website database, the proxy server will utilize a trained neural network to determine whether or not to render that website. The neural network will be trained on a vast collection of sampled websites by category. The neural network needs to be trained constantly to improve decision making as new websites are visited.

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Grinev, Maxim, Maria Grineva, Martin Hentschel, and Donald Kossmann. "Analytics for the real-time web." Proceedings of the VLDB Endowment 4, no. 12 (August 2011): 1391–94. http://dx.doi.org/10.14778/3402755.3402778.

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Polgar, Jana. "Use of Web Analytics in Portals." International Journal of Web Portals 2, no. 4 (October 2010): 40–44. http://dx.doi.org/10.4018/jwp.2010100104.

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Web analytics are typically branded as a tool for measuring website traffic. They can be equally used as a tool for business research, results of advertising campaigns, and market research. Web analytics provide data on the number of visitors, page views, measure a visitor’s navigation through a website, etc. This collection of data is typically compared against some metrics to indicate whether the web site is delivering expected values, what improvements should be considered, and so on. These metrics are also used to improve a web site or marketing campaign’s audience response. Tracking portal visits are important in order to obtain a better understanding of which parts of the portal are delivering value. However, portals have unique attributes associated with the page composition techniques, page, and portlet refresh. Portal always presents multiple topics on the same page, which pose specific challenges to explore exciting opportunities allowing the web designer to gain insights about portal usage and user behaviour. Furthermore, portals are inherently multidimensional, and effective tools to monitor and analyse portal data usage must be able to support multidimensional analysis.

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Phippen, A., L. Sheppard, and S. Furnell. "A practical evaluation of Web analytics." Internet Research 14, no. 4 (September 2004): 284–93. http://dx.doi.org/10.1108/10662240410555306.

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Fundingsland Jr, Edwin Lauritz, Joseph Fike, Joshua Calvano, Jeffrey Beach, Deborah Lai, and Shuhan He. "Methodological Guidelines for Systematic Assessments of Health Care Websites Using Web Analytics: Tutorial." Journal of Medical Internet Research 24, no. 4 (April 15, 2022): e28291. http://dx.doi.org/10.2196/28291.

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With the growing importance of communicating with the public via the web, many industries have used web analytics to provide information that organizations can use to better achieve their goals. Although the importance of health care websites has also grown, the health care industry has been slower to adopt the use of web analytics. Web analytics are the measurement, collection, analysis, and reporting of internet data used to measure direct user interaction. Our objective is to provide generalized methods for using web analytics as key performance metrics to evaluate websites and outline actionable recommendations for improvement. By deconstructing web analytic categories such as engagement, users, acquisition, content, and platform, we describe how web analytics are used to evaluate websites and how improvements can be made using this information. Engagement is how a user interacts with a website. It can be evaluated using the daily active users to monthly active users (DAU/MAU) ratio, bounce rate, pages viewed, and time on site. Poor engagement indicates potential problems with website usability. Users pertains to demographic information regarding the users interacting with a website. This data can help administrators understand who is engaging with their website. Acquisition refers to the overall website traffic and the method of traffic, which allows administrators to see how people are accessing their website. This information helps websites expand their methods of attracting users. Content refers to the overall relevancy, accuracy, and trustworthiness of a website’s content. If a website has poor content, it will likely experience difficulty with user engagement. Finally, platform refers to the technical aspects of how people access a website. It includes both the internet browsers and devices used. By providing detailed descriptions of these categories, we have identified how web administrators can use web analytics to systematically assess their websites. We have also provided generalized recommendations for actionable improvements. By introducing the potential of web analytics to augment usability and the conversion rate, we hope to assist health care organizations in better communicating with the public and therefore accomplishing the goals of their websites.

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Zhang, Zili, Li Liu, Li Li, and Xiangliang Zhang. "Special issue: Mobile web data analytics (part I)." Web Intelligence 16, no. 2 (June 11, 2018): 89–90. http://dx.doi.org/10.3233/web-180380.

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Zhang, Zili, Li Liu, Li Li, and Xiangliang Zhang. "Special issue: Mobile web data analytics (part II)." Web Intelligence 16, no. 3 (September 11, 2018): 147–48. http://dx.doi.org/10.3233/web-180381.

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Yang, Le, and Joy M. Perrin. "Tutorials on Google Analytics: How to Craft a Web Analytics Report for a Library Web Site." Journal of Web Librarianship 8, no. 4 (August 30, 2014): 404–17. http://dx.doi.org/10.1080/19322909.2014.944296.

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Belair-Gagnon, Valerie. "News on the fly: journalist-audience online engagement success as a cultural matching process." Media, Culture & Society 41, no. 6 (November 22, 2018): 757–73. http://dx.doi.org/10.1177/0163443718813473.

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Looking at web analytics in newsrooms, journalism studies scholarship has explored the notion of success in using web analytics and metrics in measuring journalist-audience engagement. Scholars have looked at the role of organizational structures, cognition, and emotion in defining success with analytics. This article analyzes how journalists interpret journalist-audience engagement success using web analytics and what this reliance on web analytics might mean for contemporary news production. Using direct observation of newsrooms and interviews with news media workers, this article argues that media workers interpret success in audience engagement using web analytics as a process of cultural matching between web analytics companies, media workers, and audiences. This article shows that analytics in journalism have highlighted some of the shared values and practices across the matchers and revealed the challenges of measuring success in audience-journalist engagement.

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Xun, Jiyao. "Return on web site visit duration: Applying web analytics data." Journal of Direct, Data and Digital Marketing Practice 17, no. 1 (September 2015): 54–70. http://dx.doi.org/10.1057/dddmp.2015.33.

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Ahmed, Nesreen, and Ryan Rossi. "Interactive Visual Graph Analytics on the Web." Proceedings of the International AAAI Conference on Web and Social Media 9, no. 1 (August 3, 2021): 566–69. http://dx.doi.org/10.1609/icwsm.v9i1.14653.

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We present a web-based network visual analytics platform called GraphVis that combines interactive visualizations with analytic techniques to reveal important patterns and insights for sense making, reasoning, and decision-making. The platform is designed with simplicity in mind and allows users to visualize and explore networks in seconds with a simple drag-and-drop of a graph file into the web browser. GraphVis is fast and flexible, web-based, requires no installation, while supporting a wide range of graph formats as well as state-of-the-art visualization and analytic techniques. In particular, the multi-level network analysis engine of GraphVis gives rise to a variety of new possibilities for exploring, analyzing, and understanding complex networks interactively in real-time. Finally, we also highlight other key aspects including filtering, querying, ranking, manipulating, exporting, partitioning (community/role discovery), as well as tools for dynamic network analysis and visualization, interactive graph generators (including two new block model approaches), and a variety of multi-level network analysis and statistical techniques.

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Barba, Ian, Ryan Cassidy, Esther De Leon, and B. Justin Williams. "Web Analytics Reveal User Behavior: TTU Libraries’ Experience with Google Analytics." Journal of Web Librarianship 7, no. 4 (October 2013): 389–400. http://dx.doi.org/10.1080/19322909.2013.828991.

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Kalinin, Alexandr A., Selvam Palanimalai, Junqi Zhu, Wenyi Wu, Nikhil Devraj, Chunchun Ye, Nellie Ponarul, Syed S. Husain, and Ivo D. Dinov. "SOCRAT: A Dynamic Web Toolbox for Interactive Data Processing, Analysis and Visualization." Information 13, no. 11 (November 19, 2022): 547. http://dx.doi.org/10.3390/info13110547.

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Many systems for exploratory and visual data analytics require platform-dependent software installation, coding skills, and analytical expertise. The rapid advances in data-acquisition, web-based information, and communication and computation technologies promoted the explosive growth of online services and tools implementing novel solutions for interactive data exploration and visualization. However, web-based solutions for visual analytics remain scattered and relatively problem-specific. This leads to per-case re-implementations of common components, system architectures, and user interfaces, rather than focusing on innovation and building sophisticated applications for visual analytics. In this paper, we present the Statistics Online Computational Resource Analytical Toolbox (SOCRAT), a dynamic, flexible, and extensible web-based visual analytics framework. The SOCRAT platform is designed and implemented using multi-level modularity and declarative specifications. This enables easy integration of a number of components for data management, analysis, and visualization. SOCRAT benefits from the diverse landscape of existing in-browser solutions by combining them with flexible template modules into a unique, powerful, and feature-rich visual analytics toolbox. The platform integrates a number of independently developed tools for data import, display, storage, interactive visualization, statistical analysis, and machine learning. Various use cases demonstrate the unique features of SOCRAT for visual and statistical analysis of heterogeneous types of data.

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Meng, Juan, Yan Jin, Yen-I. Lee, and Solyee Kim. "Can Google Analytics Certification Cultivate PR Students’ Competency in Digital Analytics? A Longitudinal Pedagogical Research." Journalism & Mass Communication Educator 74, no. 4 (December 29, 2018): 388–406. http://dx.doi.org/10.1177/1077695818816916.

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This longitudinal pedagogical research investigates students’ perceptions and learning outcomes by integrating web and social analytics–based learning activities (i.e., Google Analytics courses and certification test) into Public Relations Research course design. Results from the pretest before introducing the analytics learning assignment confirmed that students’ knowledge on web and social analytics is low but their desire to learn is high. Results from the posttest after passing the certification test indicated students are eager to have more experience-based learning activities to apply knowledge related to web and social analytics in public relations research and practice. More pedagogical recommendations are discussed.

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Nakatani, Kazuo, and Ta‐Tao Chuang. "A web analytics tool selection method: an analytical hierarchy process approach." Internet Research 21, no. 2 (January 28, 2011): 171–86. http://dx.doi.org/10.1108/10662241111123757.

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Demkina, O. V., and N. G. Shalamova. "INVESTIGATION OF THE WEB ANALYTICS ROLE IN IMPROVING THE EFFICIENCY OF THE ORGANIZATION`S PERFORMANCE." Vestnik Universiteta, no. 5 (June 10, 2019): 56–61. http://dx.doi.org/10.26425/1816-4277-2019-5-56-61.

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Web analytics allows you to collect and analyze information about visitors of Internet resources.The main metrics, used in web analytics, have been considered in the article, including domestic organizations in various fields of activity. The issue of increasing the profitability of an organization based on improving the web analytics system, focused on three aspects, has been examined: analysis of user behavior, analysis of the organization’s performance results, and analysis of user satisfaction. To determine the state of web analytics in the organization, as well as its influence on the profitability of a company, a matrix of web analytics influence on the profitability of the organization based on the A. Koshik matrix, − has been developed.

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Gamalielsson, Jonas, Björn Lundell, Simon Butler, Christoffer Brax, Tomas Persson, Anders Mattsson, Tomas Gustavsson, Jonas Feist, and Erik Lönroth. "Towards open government through open source software for web analytics: The case of Matomo." JeDEM - eJournal of eDemocracy and Open Government 13, no. 2 (December 22, 2021): 133–53. http://dx.doi.org/10.29379/jedem.v13i2.650.

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Web analytics technologies provide opportunities for organisations to obtain information about users visiting their websites in order to understand and optimise web usage. Use of such technologies often leads to issues related to data privacy and potential lock-in to specific suppliers and proprietary technologies. Use of open source software (OSS) for web analytics can create conditions for avoiding issues related to data privacy and lock-in, and thereby provides opportunities for a long-term sustainable solution for organisations both in the public and private sectors. The paper characterises use of and engagement with OSS projects for web analytics. Specifically, we contribute a characterisation of use of OSS licensed web analytics technologies in Swedish government authorities, and a characterisation of organisational engagement with the Matomo OSS project for web analytics.

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O’Brien, Patrick, Scott W.H. Young, Kenning Arlitsch, and Karl Benedict. "Protecting privacy on the web." Online Information Review 42, no. 6 (October 8, 2018): 734–51. http://dx.doi.org/10.1108/oir-02-2018-0056.

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Purpose The purpose of this paper is to examine the extent to which HTTPS encryption and Google Analytics services have been implemented on academic library websites, and discuss the privacy implications of free services that introduce web tracking of users. Design/methodology/approach The home pages of 279 academic libraries were analyzed for the presence of HTTPS, Google Analytics services and privacy-protection features. Findings Results indicate that HTTPS implementation on library websites is not widespread, and many libraries continue to offer non-secured connections without an automatically enforced redirect to a secure connection. Furthermore, a large majority of library websites included in the study have implemented Google Analytics and/or Google Tag Manager, yet only very few connect securely to Google via HTTPS or have implemented Google Analytics IP anonymization. Practical implications Librarians are encouraged to increase awareness of this issue and take concerted and coherent action across five interrelated areas: implementing secure web protocols (HTTPS), user education, privacy policies, informed consent and risk/benefit analyses. Originality/value Third-party tracking of users is prevalent across the web, and yet few studies demonstrate its extent and consequences for academic library websites.

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Black, Elizabeth L. "Web Analytics: A Picture of the Academic Library Web Site User." Journal of Web Librarianship 3, no. 1 (March 13, 2009): 3–14. http://dx.doi.org/10.1080/19322900802660292.

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Lapworth, Emily. "Assessing large-scale digitization using Web analytics." Digital Library Perspectives 37, no. 2 (March 29, 2021): 133–50. http://dx.doi.org/10.1108/dlp-09-2020-0095.

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Purpose The purpose of this study is to assess the use of digital collections created via the large-scale digitization of archival collections. The large-scale digitization method specifically examined is the reuse of archival description from finding aids to create digital collections that consist mainly of compound digital objects, equivalent to a folder of items, minimally described at the aggregate level. This paper compares Web analytics data for two large-scale digital collections and one digital collection with rich, item-level description. Design/methodology/approach This study analyzed one year of Web analytics for three digital collections. The main research question of this study is: Are digital collections of minimally described compound objects used less than digital collections of richly described single objects? Findings This study found that the large-scale digital collections analyzed received less use than the traditional item-level collection, when examined at the item level. At the object level, the large-scale collections did not always receive less use than the traditional item-level collection. Research limitations/implications This study is limited to three different digital collections from one institution. Web analytics also represent a limited interpretation of “use.” Practical implications This study presents a method for other institutions to assess their own large-scale digitization efforts and contributes to the profession’s understanding of the impact of large-scale digitization. Originality/value This paper is unique because it uses Web analytics to compare the use of large-scale digital collections to the use of traditional boutique digital collections.

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Shehzad, Hafiz Muhammad Faisal, Vishwa Pratap Singh, Mazhar Javed Awan, Awais Yasin, and Amna Khalil. "Flight web searches analytics through big data." International Journal of Computer Applications in Technology 68, no. 3 (2022): 260. http://dx.doi.org/10.1504/ijcat.2022.10049751.

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Khalil, Amna, Mazhar Javed Awan, Awais Yasin, Vishwa Pratap Singh, and Hafiz Muhammad Faisal Shehzad. "Flight web searches analytics through big data." International Journal of Computer Applications in Technology 68, no. 3 (2022): 260. http://dx.doi.org/10.1504/ijcat.2022.124949.

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Redkina, N. S. "The development tendencies of web analytics tools." Automatic Documentation and Mathematical Linguistics 51, no. 3 (June 2017): 112–16. http://dx.doi.org/10.3103/s0005105517030050.

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Diaz-Aviles, Ernesto. "Living analytics methods for the social web." ACM SIGIR Forum 47, no. 2 (December 21, 2013): 139. http://dx.doi.org/10.1145/2568388.2568412.

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Camisetty, Akhilesh, Chaitanya Chandurkar, Maoyuan Sun, and David Koop. "Enhancing Web-based Analytics Applications through Provenance." IEEE Transactions on Visualization and Computer Graphics 25, no. 1 (January 2019): 131–41. http://dx.doi.org/10.1109/tvcg.2018.2865039.

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Mikusz, Mateusz, Sarah Clinch, Rachel Jones, Mike Harding, Christopher Winstanley, and Nigel Davies. "Repurposing Web Analytics to Support the IoT." Computer 48, no. 9 (September 2015): 42–49. http://dx.doi.org/10.1109/mc.2015.260.

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García-Dorado, José Luis, Javier Ramos, Miguel Rodríguez, and Javier Aracil. "DNS weighted footprints for web browsing analytics." Journal of Network and Computer Applications 111 (June 2018): 35–48. http://dx.doi.org/10.1016/j.jnca.2018.03.008.

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Tian, Chun Hua, Rong Zeng Cao, Hao Zhang, Feng Li, Wei Ding, and Bonnie Ray. "Service analytics framework for web-delivered services." International Journal of Services Operations and Informatics 4, no. 4 (2009): 317. http://dx.doi.org/10.1504/ijsoi.2009.029182.

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Loftus, Wayne. "Demonstrating Success: Web Analytics and Continuous Improvement." Journal of Web Librarianship 6, no. 1 (January 2012): 45–55. http://dx.doi.org/10.1080/19322909.2012.651416.

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Tidal, Junior. "Using Web Analytics for Mobile Interface Development." Journal of Web Librarianship 7, no. 4 (October 2013): 451–64. http://dx.doi.org/10.1080/19322909.2013.835218.

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Best, Daniel, Joseph Bruce, Scott Dowson, Oriana Love, and Liam McGrath. "Web-Based Visual Analytics for Social Media." Proceedings of the International AAAI Conference on Web and Social Media 6, no. 4 (August 3, 2021): 2–5. http://dx.doi.org/10.1609/icwsm.v6i4.14363.

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Abstract:

Social media provides a rich source of data that reflects current trends on a multitude of topics. The data can be harvested from Twitter, Facebook, blogs, and other social applications. The high rate of adoption of social media has created a domain that is difficult to analyze, due to the ever-expanding volume of data. Information visualization is key in drawing out features of interest in social media. The Scalable Reasoning System is an application that couples a back-end server equipped with analysis algorithms and an intuitive visual in- terface to allow for investigation. We provide a componentized system that can be rapidly adapted to user needs. The in- formation in which they are most interested is featured prominently in the application. As an example, we have developed a weather and traffic monitoring application for use by emergency operators in the city of Seattle.

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Murphy, Hilary Catherine. "Book Review: Cult of Analytics: Driving Online Marketing Strategies Using Web Analytics." International Journal of Market Research 52, no. 6 (November 2010): 842–44. http://dx.doi.org/10.2501/s1470785310201685.

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C, Siva, Maheshwari K.G, Nalinipriya G, and Priscilla Mary J. "Dynamic Analytics and Forecasting Model for Covid-19 Using Machine Learning Algorithms." Webology 18, no. 05 (October 29, 2021): 1212–25. http://dx.doi.org/10.14704/web/v18si05/web18302.

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In our day to day life, the availability of correctly labelled data as well as handling of categorical data are mostly acknowledged as two main challenges in dynamic analysis. Therefore, clustering techniques are applied on unlabelled data to group them in accordance with the homogeneity. There are many prediction methods that are being popularly used in handling forecasting problems in real time environment. The outbreak of coronavirus disease (COVID19)-2019 creates the need for a medical emergency of worldwide concern with a rapidly high danger of open out and strike the entire world. Recently, the ML prediction models were used in many real time applications which necessitate the identification and categorization for real time environment. In medical field Prediction models are vital role to obtain observations of spread and significances of infectious diseases. Machine learning related forecasting mechanisms have showed their importance to develop the decision making on the upcoming course of actions. The K-means algorithm and hierarchy were applied directly on the renewed dataset using R programming language to create the covid patient cluster. Confirmed Covid patients count are passed to Prophet package, then the prophet model has been created. This forecasts model predicts the future covid count, which is essential for the clinical and healthcare leaders to make the appropriate measures in advance. The results of the experiments indicate that the quality of Hierarchical clustering outperforms than the K-Means clustering algorithm in the structured structured dataset. Thus, the prediction model also used to support model predictions help for the officials to take timely actions and make decisions to contain the COVID-19 dilemma. This work concludes Hierarchical clustering algorithm is the best model for clustering the covid data set obtained from world health organization (WHO).

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Zemlyanskaya, N. B., D. A. Komonov, and M. V. Sazonova. "System of monitoring of Internet resources as instrument of digital marketing." Vestnik Universiteta, no. 2 (April 7, 2019): 20–23. http://dx.doi.org/10.26425/1816-4277-2019-2-20-23.

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The concept of digital marketing as targeted and interactive marketing of goods and services which is directed to improve the operating mechanism of sales of products through the application of different digital technologies has been considered. Working process with information, necessary for improvement of content of the website and optimization of sales propositions has been shown. The main indicators of web analytics, including its analytical cycle have been considered in detail. The fundamental objectives, tools and services of web analytics, allowing to organize effectively its work, have been determined.

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Bekavac, Ivan, and Daniela Garbin Praničević. "Web analytics tools and web metrics tools: An overview and comparative analysis." Croatian Operational Research Review 6, no. 2 (October 31, 2015): 373–86. http://dx.doi.org/10.17535/crorr.2015.0029.

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