Web analytics

In the past few years, the data analysis in the academic field has gained interest, because higher education institutions generate large volumes of information through historic data of students, information systems and the tools used by the learning processes. The analysis of this information supports the decision making, which positively impacts the academic performance of students and teachers. In addition, if the results of the analysis are shared with the institution community, it is possible to individualize the needs of the students and professors. Thus, the professional improving process can be applied to each person. This analysis needs to be focused on an education context such as Learning Analytics (LA) and Education Data Mining (EDM), which address the Knowledge Discovery process (KDP). Because of this, we present in this paper the implementation of LA in an Open Data (OD) environment to analyze the information of a higher education institution. The analysis is focused on the academic performance of the students from different perspectives (social, economic, family, among others). In order to improve the results, the analysis process is done in real time through Web Analytics (WA) for each member of the institution according to its needs.

In the past, focus of e-learning researches was mostly on technologies and materials which are directly related with learning environment such as learning management system (LMS), content management system (CMS), course contents etc. However, after emergence of big data concept, direction of researches has shifted to extract the hidden knowledge to be used by decision makers. Thus, user habits, content quality, LMS/CMS qualifications and many other issues can be improved using data stored in e-learning environment. When it comes to analyzing LMS side, Google Analytics is one of the best tools to examine performance and also to improve e-learning services. In this study, it is aimed to observe changes in user habits between 2011 and 2016 using Google Analytics data of Enocta Academic Education Platform which offers course content and LMS services for organizations and universities in Turkey. Thus, it is aimed to give advices to LMS providers in terms of improving their software consi...

An overview is presented of resources and web analytics strategies useful in setting solutions for capturing usage statistics and assessing audiences for open access academic journals. A set of complementary metrics to citations is contemplated to help journal editors and managers to provide evidence of the performance of the journal as a whole, and of each article in particular, in the web environment. The measurements and indicators selected seek to generate added value for editorial management in order to ensure its sustainability. The proposal is based on three areas: counts of visits and downloads, optimization of the website alongside with campaigns to attract visitors, and preparation of a dashboard for strategic evaluation. It is concluded that, from the creation of web performance measurement plans based on the resources and proposals analysed, journals may be in a better position to plan the data-driven web optimization in order to attract authors and readers and to offer the

Gathering and analysing data about the usage of websites can assist in understanding customer behaviour, improving services and potentially increasing profit. However, changing technologies and evolving web analytics methods and processes present a challenge to organisations embarking on web analytics projects. In this paper we examine current theory and practice in the field of Web Analytics (WA) to identify methods and techniques, issues and challenges. Our analysis identifies the need to move from a data-centric view of WA towards a more user- and business-focused view. We propose a framework for establishing sustainable WA programmes, which widens the focus of the WA process to fully account for business requirements and to focus attention on achieving actionable outcomes.

Open-source technology has influenced data analytics at each step from data storage to data analysis, and visualization. Open source for telco big data analytics enables sharp insights by enhancing problem discoverability and solution feasibility. This research paper talks about different technology stacks using open source for telco big data analytics that are used to deploy various tools including data collection, data storage, data processing, data analysis, and data visualization. This open source pipeline micro-services architecture built with modular technology stack and orchestrated by Kubernetes, can ingest data from multiple sources, process real-time data and provide business and network intelligence. Major idea of using open source technology in our architecture is to reduce cost and manage easily. Kubernetes is an industry adopted open source container orchestrator that offers fault-tolerance, application scaling, and load-balancing. The results can be displayed on the intuitive open source dashboard like Grafana for telecom operators. Our architecture is flexible and can be easily customized based on the telecommunication industry needs. Using the proposed architecture, the telecommunication sectors can get quick decision making with nearly 30% lower CapEX which is made possible using COTS hardware.

A large and growing body of literature shows that audience metrics exert a significant influence in many newsrooms around the world. Scholars assume that this might affect the quality of news, but findings on how audience metrics influence news quality and media performance are scattered. Based on a widely used set of news quality criteria, this article is the first to focus on this question. It reviews and discusses the existing findings by considering the influence of audience metrics across four analytical dimensions: A) the allocation of resources and recognition; B) the volume, practices and rhythms of news production; C) the selection and placement of topics; and D) the formats and styles of news presentation. The analysis reveals that journalists' use of audience metrics has a mainly negative impact on news quality. This effect is the result of both the growing economic pressures on newsrooms and a dominant rhetoric that equates measures of audience size with audience interests and good journalistic work.

Trabajo de fin del Máster en Gestión de Contenidos Digitales, Facultad de Biblioteconomía y Documentación, Universidad de Barcelona (UB) y Universidad Pompeu Fabra (UPF), curso 2015-2016. Tutor: Dr. Cristóbal Urbano Salido (UB) Resumen [ES]: A través de la analítica web se pueden establecer indicadores clave de rendimiento para los sitios universitarios, los que junto a otras métricas de inteligencia competitiva provenientes de la cibermetría y las redes sociales, permiten dimensionar de manera global la presencia de las casas de estudios superiores en internet y caracterizar el comportamiento de su audiencia. Como insumo para la arquitectura de información, sin embargo, este método debe complementarse con otras técnicas de investigación de usuarios que entreguen datos cualitativos. El trabajo presenta un proyecto para el estudio de caso del portal institucional de la Universidad de Chile, con el objetivo de entregar recomendaciones para su rediseño y el optimizar los ámbitos de extensión, postgrado e internacionalización. Resum [CA]: A través de l'analítica web es poden establir indicadors clau de rendiment per als llocs universitaris, els que al costat d'altres mètriques d'intel·ligència competitiva provinents de la cibermetria i les xarxes socials, permeten dimensionar de manera global la presència de les cases d'estudis superiors en internet i caracteritzar el comportament de la seva audiència. Com a input per a l'arquitectura d'informació, però, aquest mètode s'ha de complementar amb altres tècniques d'investigació d'usuaris que lliurin dades qualitatives. El treball presenta un projecte per a l'estudi de cas del portal institucional de la Universitat de Xile, amb l'objectiu de lliurar recomanacions per al seu redisseny i d'optimitzar els àmbits d'extensió, postgrau i internacionalització. Abstract [EN]: Using web analytics it is possible to establish Key Performance Indicators (KPIs) for university websites, which together with other metrics of competitive intelligence that come from cyber-metrics and social media, allow us to measure on a global scale the presence of higher education institutions on the Internet, and to characterize the behavior of their audience. As an input for information architecture, however, this method should be complemented by other user research techniques that deliver qualitative data. This document presents a project case study on the institutional website of the University of Chile, with the goal of providing recommendations for redesign, and optimization of the areas of outreach, graduate studies and internationalization.

This report is aimed to provide a wide view of the current situation of ICT and its future trends in Croatia, currently the newest member of the EU. This sector is going to be a pivot point for many sectors since its introduction to the EU. As a result, the country will be seeing an overhaul process by modernizing its structure, policies and expansion plan in sectors like health care, education and so on.

In recent years, many sociotechnical theories have been introduced and applied, to underpin information systems (IS) studies, particularly, in the qualitative paradigm. The increasing interest and attention is mainly because of the shift from simply application of interpretivism in the analysis of qualitative data. The qualitative methods allow researchers to freely, creatively or innovatively explore means in the data collection, increasing its richness. The theories are often employed as lenses to guide data collection, analysis of data and interpretation of the findings from the analysis, which thereby influence and shape the way phenomena are studied and interpreted. However, none of the theories focus on organisational structure for performance and strategy, wholly, except contingency theory (CT). Conversely, there are challenges on how to apply the theory in IS studies. This has made some researchers including postgraduate candidates to either avoid it, otherwise, it distorts the outcome of their studies in an attempt to manipulatively make use of the theory. This is the primary motivation for the use of contingency theory in information system studies. Some of the challenges as revealed in this article include understanding of the tenets of CT in the context of IS, categorisation of IS primary drivers, such as technology, process and people to align with CT tenets, and understanding the factors which influence the applicability of the theory in IS studies. This article presents a guide which can be followed in the application of CT in IS studies. The guide can also assist managers in understanding the influencing factors in their organisations' strategies and performances.

Gathering and analysing data about the usage of websites can assist in understanding customer behaviour, improving services and potentially increasing profit. However, changing technologies and evolving web analytics methods and processes present a challenge to organisations embarking on web analytics projects. In this paper we examine current theory and practice in the field of Web Analytics (WA) to identify methods and techniques, issues and challenges. Our analysis identifies the need to move from a data-centric view of WA towards a more user- and business-focused view. We propose a framework for establishing sustainable WA programmes, which widens the focus of the WA process to fully account for business requirements and to focus attention on achieving actionable outcomes.

Presentamos aquí el análisis y estadísticas más recientes de usuarios digitales, medios, redes sociales y uso de Internet en Ecuador incluyendo categorías de e-commerce, transacciones, mejores prácticas, tendencias y recomendaciones para marcas y su gestión de marketing, comunicación, transformación, investigación e inversión. Autor: Juan Pablo Del Alcázar Ponce. Institución: Mentinno.

The increasing volume of user-generated content on the web has made sentiment analysis an important tool for the extraction of information about the human emotional state. A current research focus for sentiment analysis is the improvement of granularity at aspect level, representing two distinct aims: aspect extraction and sentiment classification of product reviews and sentiment classification of target-dependent tweets. Deep learning approaches have emerged as a prospect for achieving these aims with their ability to capture both syntactic and semantic features of text without requirements for high-level feature engineering , as is the case in earlier methods. In this article, we aim to provide a comparative review of deep learning for aspect-based sentiment analysis to place different approaches in context.

3rd International Conference on NLP & Big Data (NLPD 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Big data. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only

[EDIT: Update October 28th 11:47 UTC: Yesterdays 5-10% drop in numbers has been fixed for me, within 24 hours! Kudos to Academia.edu Support, and good luck to everyone else]

A summary of events that have unfolded in between March 11th and 24th 2021. Until today, May 27th, problems continue to be worked on

Updated June 6th

"Web 2.0 brought a new way to people to use the web through User Generated Content. The ease to edit content gives rise to content in perpetual movement, result of a collective intelligence. Virtual communities through their different exchanges lead to new social interactions on the web, the final result of this trend is the creation and emergence of micro blogging, social media and social networks.

Integration of social media into population has been facilitated by the omniscience of the web that went mobile with Smartphones, tablets and useful specific tools associated to them, such as Geolocation and Augmented Reality. Nowadays, Facebook, Google+, LinkedIn and twitter are among the tools most used on a daily basis.

Marketers react by creating new ways to evaluate Return on Investment, new Web Analytical tools to gather and interpret all the data now available as a result of information collected from users browsing. This is still challenged by the emergence of Web3.0. Another effect of the socialisation and exchange is that the classic Word of Mouth Marketing access a new dimension because of the myriad of connections each user has on social networks to become Viral Marketing.

On a sociological perspective, Social Networks are a great opportunity to leverage Social Capital even if this usage is not the most popular and is mainly employed by students, managers and executives. It gives also opportunity to individuals to brand themselves by being proactive trough pertinent communication on specific topics.

The real success of social networks is due to the ease given to the population to maintain their connections and sustain their group affiliation. Digital natives‟ generation are also natural users of these tools. There are some psychological factors that affect people and reassure them by seeing that others have similar life and make them feel well integrated into society. The result of this search for conformity is that people will broadcast more spontaneously communications with consensual topic, universal value or moral attached to their message or post."

In the practice of Digital Marketing (DM), Web Analytics (WA) and Key Performance Indicators (KPIs) can and should play an important role in marketing strategy formulation. It is the aim of this article to survey the various DM metrics to determine and address the following question: What are the most relevant metrics and KPIs that companies need to understand and manage in order to increase the effectiveness of their DM strategies? Therefore, to achieve these objectives, a Systematic Literature Review has been carried out based on two main themes (i) Digital Marketing and (ii) Web Analytics. The search terms consulted in the databases have been (i) DM and (ii) WA obtaining a result total of n = 378 investigations. The databases that have been consulted for the extraction of data were Scopus, PubMed, PsyINFO, ScienceDirect and Web of Science. In this study, we define and identify the main KPIs in measuring why, how and for what purpose users interact with web pages and ads. The main contribution of the study is to lay out and clarify quantitative and qualitative KPIs and indicators for DM performance in order to achieve a consensus on the use and measurement of these indicators.

Le Web Usage Mining est l’application des techniques du datamining aux données d’usage du web dans le but de découvrir les réelles attentes des utilisateurs d’un site web. Ce dernier est de plus en plus vu comme une source de fort revenu pour l’annonceur et donc pour le propriétaire du site qui
dispose d’un large champ d’action pour rentabiliser son site, tout en s’alignant aux comportements observés chez les visiteurs de son site web.

Ce travail se propose de fournir au webmaster un modèle statistique mettant en relief les variables qui
réaliseraient le mieux un objectif avancé par le propriétaire du site web. Le but est de guider un webmaster à agir correctement, non arbitrairement, pour atteindre son objectif, souvent lucratif.

A partir d’un échantillon donné de visites effectuées sur un site web étudié, nous avons construit un modèle de régression logistique, qui a pour ambition de modéliser la probabilité d’atteindre l’objectif souhaité en fonction de certaines variables décrivant la visite, le visiteur, et le site lui-même.

Dans un premier temps, le modèle a été choisi par une sélection pas à pas descendante. Ensuite, un algorithme de validation croisée a été appliqué pour décider du pouvoir prédictif du modèle. La lecture des résultats a permis d’énoncer quelques recommandations au webmaster.

Im Internetzeitalter ist der Webauftritt eines Unternehmens ein unverzichtbares Instrument der Information, Kommunikation und Transaktion geworden. Mit der stark steigenden Nutzung und der Abwicklung des Geschäfts über das Internet wird die Analyse und das Controlling der Website-Nutzung und des elektronischen Geschäfts – das Web Analytics – für Website-Betreiber eine wichtige Aufgabe.
Dank client- und serverseitigen Datensammlungsmethoden kann jeder einzelne Klick der Besucher aufgezeichnet und mittels Web-Analytics-Software ausgewertet werden. Dies dient neben der Analyse der Website-Nutzung und des Besucherverhaltens der Steuerung und der Optimierung der webbezogenen Wertschöpfungskette. Als sozioökonomisches Informationssystem dient Web Analytics Unternehmen zur Wirksamkeitsmessung und Optimierung von Online-Marketing-Massnahmen (z.B. Werbekampagnen, Suchmaschinenoptimierung und -marketing) sowie bei der kontinuierlichen Verbesserung der Website hinsichtlich Inhalt, Navigation und Benutzerfreundlichkeit.
Diese und weitere Nutzenvorteile konnten dank einer empirischen Untersuchung unter 740 Web-Analytics-Fachleuten gezeigt werden. So hilft Web Analytics bei 10 von 11 Befragten, geschäfts- und websitebezogene Ziele anhand von KPIs (Key Performance Indicators) zu messen und zu erreichen. Dabei sind Kundengewinnung und -bindung, die Informationsbereitstellung und die Transaktionsabwicklung über die Website zentrale Ziele. Die Strukturgleichungsmodellierung zeigte auf, dass transaktionsorientierte Kennzahlen wie die Konversionsrate (der Anteil an Besuchern, die zu Käufern konvertierten), am wichtigsten sind, genauso wie die Analyse der Traffic-Quellen. Web Analytics erfahrene und affine Unternehmen sind marketing- resp. kundenorientierter, sie schöpfen die Nutzenpotentiale eher aus und haben weniger Anwenderprobleme. Wie die Untersuchung zeigte, steckt Web Analytics nicht aus technischer, sondern aus der Anwendungssicht in Theorie und Praxis noch in den Kinderschuhen. Die Webanalyse
wird in vielen Unternehmen nur als Nebenjob betrieben und oft mangelt es an Erfahrung sowie an Ressourcen wie Zeit, Budget und Know-how. Web Analytics wird organisatorisch meist dem (Online-)Marketing zugeordnet, ist jedoch eine fachübergreifende Aufgabe. Die interdisziplinäre Zusammenarbeit ist hierbei eine Herausforderung
und der Datenschutz ist im Web Analytics ein kritisches Problem.

2
nd
International Conference on NLP & Data Mining (NLDM 2022) will provide an excellent
international forum for sharing knowledge and results in theory, methodology and applications of
Natural Language Computing and Data Mining.
Authors are solicited to contribute to the conference by submitting articles that illustrate research
results, projects, surveying works and industrial experiences that describe significant advances in
the following areas, but are not limited to.

In this paper, we describe our own model of a cost-effective
and simple developed navigation system that supports the independent walking of the visually impaired in indoor spaces. This system is installed on a white cane. It follows a coloured navigation line that is set on the floor. There are colour sensors installed on the tip on the white cane, which sense the colour of the line and inform the user whether he/she is going on the right path. This colour -recognition system is controlled by a one-chip microprocessor.We also developed a direction -identification technique. Using this technique, the user knows when to turn in a particular direction. Therefore, this system will be extremely valuable in supporting the activities of the visually impaired in indoor environments.

In these days the business web sites have become more essential as a marketing tool since the majority
of people meet their requirements according to the information on the internet. With this point of
view, the aim of this research consists analyzing the web sites of the restaurants which are serving in
the cities that are included in UNESCO Creative Cities Network. The restaurants including this
research are located in three countries which are in Creative Networks. These cities and the countries
are located in has been identified: Pharma-Italy, Gaziantep-Turkey, Zahle-Lebanon. In each of the
cities, 20 restaurants have been analyzed. It has been defined 39 features derived from former studies
for this research, the analyze has been done according to these features websites of restaurants in
Phama, Gaziantep, and Zahle. As a result of this research, the websites of the restaurants which are in
the cities mentioned don’t have enough website contents to serve for gastronomy tourism. Only 65 %
of restaurants in Pharma, 55 % of restaurants in Gaziantep, and 35 % of restaurants in Zahle which
are the issue in this research have websites. Moreover, it has been understood that the percentage of
the restaurant in creative cities which have all the 39 features in their websites is 19,04. It has been
indicated that the websites of the restaurant in Pharma has 25%, in the Gaziantep’s restaurants 20,79
%, and in the Zahle’s restaurants 11,32 % has defined features.

„The Influence of Algorithmic vs Qualitative Audience Feedback on Journalists’ Work“, presentation at the 68th annual conference of the International Communication Association (ICA) in Prague, 28 May 2018 (together with Folker Hanusch and Edson Tandoc, Jr.).

This current study compares a strongly market-oriented newsroom and a weakly market-oriented newsroom in terms of how they used web analytics in news work. Using ethnographic methods, the study finds that web analytics influenced editorial decisions in both newsrooms. However, the two newsrooms differed in the extent to which they used analytics and in their reasons for doing so. These differences are examined using the framework of market theory in news construction.

In the Big Data era, search engine optimization deals with the encapsulation of datasets that are related to website performance in terms of architecture, content curation, and user behavior, with the purpose to convert them into actionable insights and improve visibility and findability on the Web. In this respect, big data analytics expands the opportunities for developing new methodological frameworks that are composed of valid, reliable, and consistent analytics that are practically useful to develop well-informed strategies for organic traffic optimization. In this paper, a novel methodology is implemented in order to increase organic search engine visits based on the impact of multiple SEO factors. In order to achieve this purpose, the authors examined 171 cultural heritage websites and their retrieved data analytics about their performance and user experience inside them. Massive amounts of Web-based collections are included and presented by cultural heritage organizations through their websites. Subsequently, users interact with these collections, producing behavioral analytics in a variety of different data types that come from multiple devices, with high velocity, in large volumes. Nevertheless, prior research efforts indicate that these massive cultural collections are difficult to browse while expressing low visibility and findability in the semantic Web era. Against this backdrop, this paper proposes the computational development of a search engine optimization (SEO) strategy that utilizes the generated big cultural data analytics and improves the visibility of cultural heritage websites. One step further, the statistical results of the study are integrated into a predictive model that is composed of two stages. First, a fuzzy cognitive mapping process is generated as an aggregated macro-level descriptive model. Secondly, a micro-level data-driven agent-based model follows up. The purpose of the model is to predict the most effective combinations of factors that achieve enhanced visibility and organic traffic on cultural heritage organizations' websites. To this end, the study contributes to the knowledge expansion of researchers and practitioners in the big cultural analytics sector with the purpose to implement potential strategies for greater visibility and findability of cultural collections on the Web.

In this paper we show apply text mining techniques, Correspondence Analysis and Fuzzy C-Means Clustering in order to identify associations among countries and titles of documents available at a profile in Academia.edu. All analysis was carried out by R software and several R scripts are presented.

Capitolul de început al volumului prezintă cadrul general al cercetării:
obiectivele proiectului mai sus menţionat, activităţile întreprinse pentru
îndeplinirea lor şi metodologia de cercetare.
Cel de-al doilea capitol tratează contextul legislativ şi politic al
alegerilor locale din 2012: modificările legislaţiei referitoare la alegerea
reprezentanţilor autorităţilor administraţiei publice locale şi o trecere în
revistă a competitorilor electorali locali.
Capitolele trei şi patru, mai substanţiale, cuprind rezultatele efective
ale cercetărilor noastre cu privire la reflectarea campaniei electorale în
mass-media locală (presa tipărită şi televiziune) şi la observarea procesului
electoral din 10 iunie.
Capitolul final prezintă concluziile cercetărilor noastre şi câteva
recomandări posibile în vederea îmbunătăţirii organizării şi desfăşurării
alegerilor la nivel local.

Cross-Device Measurement bezeichnet die Messbarkeit des Verhaltens von Nutzern auf Webseiten oder in mobilen Anwendungen über verschiedene Geräte hinweg. Es kann in Bezug auf aktuelle Technologien mit Cross-Device Tracking gleichgesetzt werden. Laut John McDermott1 beschreibt Cross-Device Tracking unzählige Methoden, mit denen Plattformen, Publisher und Werbetechnologie-Unternehmen versuchen, Internetnutzer über verschiedene Smartphones, Tablets und Desktop Computer hinweg zu verfolgen. Das Ziel sei es zu wissen, dass die Person an Smartphone X auch Tablet Y und PC Z benutzt und somit Firmen erlaubt, diese Person gezielt wieder zu erreichen. Doch neben den Möglichkeiten Retargeting einzusetzen, ist insbesondere die lückenlose Zuordnung von Konversionen zu den tatsächlichen Touch-Points innerhalb der User-Journey der Hauptgrund, wieso das Cross-Device Tracking mittlerweile eine derart wichtige Rolle für Online Marketing Verantwortliche einnimmt.

Massive Open Online Courses (MOOCs) provide anyone with internet access the chance to study at university level for free. In such learning environments and due to their ubiquitous nature, learners produce vast amounts of data representing their learning process. Learning Analytics (LA) can help identifying, quantifying and understanding these data traces. Within the implemented web-based tool, called LA Cockpit, basic metrics to capture the learners' activity for the Austrian MOOC platform iMooX were defined. Data is aggregated in an approach of behavioral and web analysis as well as paired with state-of-the-art visualization techniques to build a LA dashboard. It should act as suitable tool to bridge the distant nature of learning in MOOCs. Together with the extendible design of the LA Cockpit it shall act as a future-proof framework to be reused and improved over time. Aimed towards administrators and educators, the dashboard contains interactive widgets letting the user explore their datasets themselves rather than presenting categories. This supports the data literacy and improves the understanding of the underlying key figures, thereby helping them generate actionable insights from the data. The web analytical feature of the LA Cockpit captures mouse activity in individual course-wide heat maps to identify regions of learner's interest and help separating structure and content. Activity over time is aggregated in a calendar view, making timely reoccurring patterns otherwise not deductible, now visible. Through the additional feedback from the LA Cockpit on the learners' behavior within the courses, it will become easier to improve the teaching and learning process by tailoring the provided content to the needs of the online learning community.

Attracting visitors to a website is a complex and multidimensional task for each decision maker in the digital marketing sector. Even an organization in relation with its competitors holds the reins in the provision of the most qualitative products and services rather than others, the hard reality though, depicts that if the online users are not able to navigate easily on the organization’s website, they will jump to another. This fact also brings low visibility and traffic metrics on the organization’s website, which unintentionally leads to the poor communicational promotion of products and services. In this paper, the authors combine the fragmented pieces of the usability and the levels of traffic that a website has, based on the utility of the Search Engine Optimization process for improving the website’s usability and traffic as well. To this respect, the SEO process addresses and examines the website’s usability in design, architecture, and content, for improving greater volume and quality of online users’ visits to the website through search engines. Following a user-centered digital marketing approach, the authors examine, if the level of traffic of a website, related to its level of usability that expresses, based exclusively on its user’s perceptions and suggestions about that under-examined website. Implementing all user’s suggestions and thereafter, adopting Google Analytics as a web usage mining tool for measuring the optimization, the results indicate that following the website’s user’s perceptions and suggestions about it for improving its usability, the total pageviews, the organic traffic, and also the referral traffic of the website rose significantly. To this end, highlighting the utility and practicality of this paper, it is useful to refer that it could be used as a practical toolbox for each digital marketing team, in order to estimate in a well-organized and descriptive manner, the users’ perceptions as regards to a website in order to improve its usability levels and thus its traffic.

Certificate of acceptance for the manuscript (sustainability-1180369) titled:
Environmental Laws and Morals in relation to Sustainability Awareness
Authored by:
Rita Yi Man Li; Yi Lut Li; M. James C. Crabbe; Otilia Manta; Muhammad Shoaib
has been accepted in Sustainability (ISSN 2071-1050) on 18 May 2021

Çalışmanın amacı görsel ilgi kapsamında mouse (fare) imleciyle oluşturulan tıklamaları inceleyerek, konaklama işletmelerinin web sitelerini ziyaret eden turistlerin davranışlarını analiz etmektir. Böylelikle konaklama işletmeleri web sitelerini ziyaret edenlerin davranışlarından anlamlı ve ilişkilendirilebilir enformasyon elde ederek hizmet üretim ve pazarlama süreçlerinde kullanabileceklerdir. Tezde kullanılan yöntem görsel ilginin analiz edilmesinde kullanılan yeni yöntemlerden bir tanesidir. Uluslararası yazında sıkça kullanılan bu yöntemin ulusal turizm yazınına tanıtılması da tezin yenilikçi olduğunun göstergesidir. Bünyesinde Belek'te 4, Side'de 4, Kemer'de 3, Kapadokya'da 1, Bodrum'da 1 olmak üzere 13 oteli barındıran ulusal bir otel grubuna ait web sitesinin ana sayfasını bir sene boyunca ziyaret eden ziyaretçilerin verileri değerlendirilmiştir. İncelenen veriler algısal değildir ve tamamı gerçek verilerden oluşmaktadır. İncelemeye dâhil edilen örneklem sayısı toplam 97891 (56210 Türkçe, 12132 Rusça, 2603 Almanca, 26946 İngilizce ana sayfa ziyaretçisi) kişiden oluşmaktadır. Durum çalışması olarak değerlendirilebilecek çalışmada veriler Yandex.Metrica adı verilen bir analitik programyla toplanmış ve aynı servis kullanılarak elde edilen tıklama haritaları segmentlere ayrılarak süzülmüştür. Bu segmentler, dil, yaş, cinsiyet, ziyaretçi sıklığı, ziyaretçi kaynağı olarak gruplandırılmıştır. Böylece site ziyaretçilerinin ilgili değişkenlere göre hangi davranışları sergilediği incelenmiştir. Ziyaretçilerin genel görsel ilgi yönelimleri incelendiğinde Türkçe ve Rusça ana sayfayı ziyaret edenlerin davranışlarının diğer dillere ait sayfaları ziyaret edenlerden daha çok birbirine benzerlik gösterdiği sonucu ortaya çıkmıştır. Gerçek veriler üzerinden hareket edilerek yapılan bu saptama, turistik ürün ve hizmet üreten turizm arz unsurları açısından önemlidir. Satın alma gücü daha düşük yaş gruplarının (örneğin 18 yaş altı) rezervasyon butonuna daha az görsel ilgi yönelttiği, siteyi bir kereden fazla ziyaret eden kullanıcıların ise rezervasyona daha çok görsel ilgi gösterdiği tespit edilmiştir. Ayrıca siteye arama motoru ile erişenlerin diğer yöntemlerle erişenlere nazaran daha çok alt sayfaya ve daha fazla oranda rezervasyon butonuna görsel ilgi gösterdiği bulunan bir diğer sonuçtur. Son olarak araştırmamız neticesinde elde edilen sonuçlar bağlamında uygulamacılara ve araştırmacılara turist davranışı ile ilgili önemli ipuçları sunulmuştur.

The paper proposes an approach to modelling the behaviour and segmentation of online multiplayer systems’ users, based on frequency and patterns of visits. The results presented are based on the analysis of time series both in real and virtual time, with the objective to quantitatively capture the characteristics of usage of online multiplayer platforms.