Surfing Behavior Research Articles

Technology Readiness Motivators and Online Behavioural Advertising: A Perceived Benefits-Risk Assessment Using Privacy Calculus Theory

Purpose: The present research intended to find whether the technology readiness motivators, Optimism, and innovativeness, impact the user's intention to accept Online Behavioural Advertising (OBA), an area that requires additional research. Theoretical framework: Even though these personalized advertisements provide an enhanced user experience, they provide users with advertisements based on their online surfing behavior, and unfortunately, at the same time, it also creates privacy concerns. At the same time, Privacy Calculus Theory (PCT) is considered an appropriate theory when it comes to a rational benefits-costs assessment of the privacy-centred decision-making by internet users. Design/Methodology: Based on an extensive literature review, a conceptual model is being proposed, and a scenario-based questionnaire was developed and pursued on internet users' experience of the subject matter. Six hundred ten valid responses were received, and PLS-SEM was used to analyze the results. Findings: The results show that Optimism and innovativeness have a direct and indirect effect on the intention to accept Online Behavioural Advertising (OBA). Technology readiness Motivators have a detrimental impact on the intention to accept OBA. Research, Practical and Social implications: Based on our findings, we may be able to gain a deeper understanding of the theory behind targeted, data-driven digital advertising and the way in which it pertains to online shopping. Presented here is evidence to support the theory that the predisposition of users toward new technology could be the reason for users ranking perceived benefits higher than risk. Originality/Value: This study attributes original work in the sense that it is the first time that an individual’s predisposition towards technology has been taken into consideration while analysing the acceptance of OBA grounded on the Privacy Calculus framework.

A Study on Embodied Experience of Surfing Tourism Based on Grounded Theory-Take China's Hainan Province as an Example.

In the context of the rapid development of surfing tourism in China, the behavior explanation of surfing tourists has not attracted attention from the academic circle. Based on the theory of embodiment, this study takes surfing tourism in Hainan Province as the first case to explain the process and results of body experience in surfing tourism behavior. Based on the grounded theory analysis of the collected online travel notes and on-site interview text materials related to tourism experience, 21 categories and 6 main categories were extracted, and the story line of the surfing tourism experience was constructed based on embodied experience. The results show that the embodied phenomena and processes of the surfing tourism experience affect the quality of tourists' experience. Surfing tourists experience four typical processes, namely embodied perception, embodied awakening, embodied emotion and embodied extension, and represent the body's meaning, self-identity and social value through surfing behavior. The research theoretically proposes the embodied experience model and a new category of surfing tourism and provides a reference value for the practice of the surfing tourism industry.

Green-up selection by red deer in heterogeneous, human-dominated landscapes of Central Europe.

The forage maturation hypothesis (FMH) assumes that herbivores cope with the trade‐off between digestibility and biomass in forage by selecting vegetation at intermediate growth. The green wave hypothesis (GWH) extends the FMH to suggest how spatiotemporal heterogeneity in plant quality shapes migratory movements of herbivores. Growing empirical support for these hypotheses mainly comes from studies in vast landscapes with large‐scale habitat heterogeneity. It is unclear, however, to what extent ungulates surf green waves in human‐altered landscapes with small‐scale heterogeneity in terms of land use and topography. We used plant phenological proxies derived from Sentinel 2 satellite data to analyze the habitat selection of 93 collared red deer (Cervus elaphus) in montane and alpine habitats. Using a step selection analysis, we investigated how plant phenology, that is, the instantaneous rate of green‐up (IRG) and normalized difference vegetation index (NDVI), and a set of variables describing topography and human presence influenced red deer resource selection in open habitats. We learned that red deer selected areas with high biomass at green‐up and avoided habitats with possible exposure to human activity. Additionally, landscape structure and topography strongly influenced spatial behavior of red deer. We further compared cumulative access to high‐quality forage across migrant strategies and found migrants gained better access than residents. Many migratory individuals surfed the green wave, and their surfing behavior, however, became less pronounced with decreasing distance to settlements. Within the constraints of topography and human land use, red deer track spring green‐up on a fine spatiotemporal scale and follow the green wave across landscapes in migration movements. Thus, they benefit from high‐quality forage even in human‐dominated landscapes with small‐scale heterogeneity and vegetation emerging in a heterogenic, dynamic mosaic.

Anti-Scraping Techniques

Web scraping refers to a software program that mimics human web surfing behavior by pointing to a website and collecting large amounts of data that would otherwise be difficult for a human to extract. A typical program will extract both unstructured and semi-structured data, as well as images, and convert the data into a structured format. The activity is deemed illegal, but the change in legality has not stopped people from doing the same. This paper aims to list challenges and proposes techniques to developing anti-scraping application.

Real-time user clickstream behavior analysis based on apache storm streaming

This paper presents an approach to analyzing consumers’ e-commerce site usage and browsing motifs through pattern mining and surfing behavior. User-generated clickstream is first stored in a client site browser. We build an ingestion pipeline to capture the high-velocity data stream from a client-side browser through Apache Storm, Kafka, and Cassandra. Given the consumer’s usage pattern, we uncover the user’s browsing intent through n-grams and Collocation methods. An innovative clustering technique is constructed through the Expectation-Maximization algorithm with Gaussian Mixture Model. We discuss a framework for predicting a user’s clicks based on the past click sequences through higher order Markov Chains. We developed our model on top of a big data Lambda Architecture which combines high throughput Hadoop batch setup with low latency real-time framework over a large distributed cluster. Based on this approach, we developed an experimental setup for an optimized Storm topology and enhanced Cassandra database latency to achieve real-time responses. The theoretical claims are corroborated with several evaluations in Microsoft Azure HDInsight Apache Storm deployment and in the Datastax distribution of Cassandra. The paper demonstrates that the proposed techniques help user experience optimization, building recently viewed products list, market-driven analyses, and allocation of website resources.

The Effects of Non-Directional Online Behavior on Students’ Learning Performance: A User Profile Based Analysis Method

Network behavior analysis is an effective method to outline user requirements, and can extract user characteristics by constructing machine learning models. To protect the privacy of data, the shared information in the model is limited to non-directional network behavior information, such as online duration, traffic, etc., which also hides users’ unconscious needs and habits. However, the value density of this type of information is low, and it is still unclear how much student performance is affected by online behavior; in addition there is a lack of methods for analyzing the correlation between non-directed online behavior and academic performance. In this article, we propose a model for analyzing the correlation between non-directed surfing behavior and academic performance based on user portraits. Different from the existing research, we mainly focus on the public student behavior information in the campus network system and conduct in-depth research on it. The experimental results show that online time and online traffic are negatively correlated with academic performance, respectively, and student’s academic performance can be predicted through the study of non-directional online behavior.

Research on Internet Surfing Behavior of College Students Based on Big Data

With the rapid development of computer technology, the network behavior in the era of big data has become an important activity in students' campus life, which is quietly changing students' study and life. However, the behavior of students' network users directly reflects the purpose and demand of users and the state and performance of the network. The author analyzes the data of student users' online logs, and uses Apriori algorithm to analyze its association rules. Summarize the characteristics of student users' online behavior, including online time analysis, user's visit to websites and other user behavior analysis, which is of great significance for network optimization, personalizedj and differentiated design of services, standardized management, rational allocation of network bandwidth, enhancing information security, improving the efficiency of daily management of college counselors and network administrators, and ensuring the stability and efficiency of campus network environment.

Effects of Cognitive and Behavioural Therapies on Internet Surfing Behaviour and Text Messaging Behaviour of University Students

The study sought to examine the effects of cognitive and behavioural therapies on student’s internet surfing behaviour and text messaging behaviour at the University of Cape Coast. The sample comprised 60 undergraduate regular students from three Colleges in the University of Cape Coast (College of Health and Allied Sciences, College of Humanities and Legal studies, and College of Education studies) in the Central Region of Ghana. The study was conducted using a quasi-experimental pre-test, post-test (non-equivalent) control group design. Three groups made up of two experimental groups and a control group were involved in the study. Using an adapted form of Choliz (2012) Test of Mobile Phone Dependence, the data for the study was gathered. The instrument which was in the form of a structured questionnaire was on a 5-point Likert-type scale, comprising twenty-three items. One-way Analysis of Covariance (ANCOVA) at the alpha level of .05 was used to test the hypotheses. The result was that Cognitive and behavioural therapies had positive effects on Students’ Internet Surfing Behaviour and Students’ Text Messaging Behaviour. Students have the ability and capacity to succeed in readjusting and controlling their mobile phone addictive behaviours using cognitive and behavioural strategies. It was recommended that counsellors should be encouraged to use either of the therapies to reduce mobile phone addictive behaviours of students.

A unified numerical model for wetting of soft substrates

AbstractThe wetting of deformable elastic structures has been recently shown to comprise a rich variety of new physical phenomena (stick‐slip motion, durotaxis, Shuttleworth effect, etc.) whose fundamental understanding demands for numerical simulation tools. In this article, we develop a novel unified model and numerical method for this problem. As special features, the method includes exact incompressibility and a linear monolithic assembly of the Navier‐Stokes and Cahn‐Hilliard equations which stabilizes dominant surface tension at small interface lengths. Also, solid viscosity is included which offers the opportunity to simulate the surfing behavior of droplets on viscoelastic substrates for the first time. We show that the method is highly accurate and more robust than most previous approaches and illustrate its potential by numerical simulation examples.

Analysis and Portrait of College Students’ Online Behavior Habits

In the era of information technology, the popularity of college networks has brought great convenience to students. However some students indulge in the network and thus affect the quality of learning. In order to help college students make use of network resources properly, we analyze students’ surfing behavior from the perspective of data mining. 11 classes of web pages with high degree of attention are taken into consideration. the data of more than 100 million log records generated by students in universities within 20 days are collected. We also use Bisecting K-means algorithm to cluster students on different levels. For measuring every students’ behavior, we introduce a stability measure for web surfing behavior. we calculate this parameter for every student and analyse the results. Finally, according to the clustering results, cluster stability analysis results and other attributes, we draw a user portrait for every student. After practice, the method is simple and easy to use, providing reference for universities to organize network management activities and standardizing college students’ online behavior.

User behavior analysis-based smart energy management for webpage ranking: Learning automata-based solution

Search engines are widely used for surfing the Internet. Different search engines vary with respect to their accuracy and time to fetch the information from the distributed/centralized database repository across the globe. However, it has been found in the literature that webpage ranking helps in saving the user's surfing time which in turn saves considerable energy consumption during computation and transmission across the network. Most of the earlier solutions reported in the literature uses the hyperlink structure of graph which consume a lot of energy during the computation. It may lead to the link leakage problem with the occurrence of spam pages more often. Nowadays, hyperlink structure alone is inadequate for predicting webpage importance keeping in view of the energy consumption of various smart devices. User browsing behavior depicts its real importance. It is essential to demote the spam pages to increase the search engine accuracy and speed. Hence, user behavior analysis along with demotion of spam pages can improve Search Engine Result Pages (SERP) which in turn saves the energy consumption. In the proposed approach, web page importance score is computed by analyzing user surfing behavior attributes, dwell time, and click count. After computing the webpage importance score, the ranks are revised by implementing it in Learning Automata (LA) environment. Learning automaton is the stochastic system which learns from the environment and responds either with a reward or a penalty. With every response from the environment, the probability of visiting the webpage is updated. Probability computation is done using Normal and Gamma distribution functions. In the proposal, we have considered only the dangling pages for experiments. Inactive webpages are punished and degraded from the system. We have validated proposed approach with Microsoft Learning to Rank dataset. It has been found in the experiments performed that 3403 dangling pages out of 12211 dangling pages have been degraded using the proposed scheme. The objective of the proposed scheme is achieved by saving web energy and computational cost. It takes 100 iterations to convergence which executed in 21.88ms. However, the user behavior analysis helped in improving PageRank score of the webpages.

Analysis of Influences of Internet Surfing on Psychological Development of Children and Teenagers from the Positive Psychological and Management Perspectives

Internet education is a novel education mode and an individualized education mode. It is an extension of traditional education by giving online education to children and teenagers. Most researches about internet surfing of children and teenagers mainly focus on internet addiction, network security and network monitoring. In this paper, an empirical study of internet surfing behaviors of children and teenagers from a new perspective was conducted under the guidance of developmental psychology, positive psychology, constructivism and humanistic thinking, which exposed the positive influence of internet surfing behavior on psychological development of children and teenagers. Since influences of various favorable factors on internet surfing behaviors of children and teenagers are hierarchical, personality factors (e.g. possessiveness and self-confidence) influence internet surfing behaviors directly, while dynamic cognitive factors (e.g. motivation and interest) influence internet surfing behaviors indirectly through personality factors. The important psychological mechanism of healthy behaviors of internet surfing of children and teenagers or transition of internet addiction was disclosed, and the management method of high-quality internet surfing of children and teenagers was proposed.

Targeting the luxury consumer

PurposeBehavioral targeting has become a popular marketing strategy among brands as it enables advertisers to display ads to consumers based on their previous surfing behaviors. The purpose of this paper is to investigate the effectiveness of behaviorally targeted ads for luxury brands and to explore how and when behavioral targeting works.Design/methodology/approachA 2 (targeted vs non-targeted ads) ×2 (culture: China vs the Netherlands) between-subjects factorial design is conducted to test the hypothesis.FindingsThe result reveals that as for luxury brands, behavioral targeting can shorten the psychological distance and in turn lead to a more positive attitude toward the ad. However, the effect of behavioral targeting depends on the culture. In the Netherlands, behavioral targeting can enhance the attitude toward the ad by lowering the psychological distance. However, in China, these effects are mitigated.Practical implicationsThis study contributes to the research of online luxury marketing. First, luxury brands should adapt their marketing strategy to different regional markets. In addition, luxury marketers should not worry about a shorter distance with consumers caused by the use of internet. A shorter distance does not mean to reduce an aura of mystery, but to build up a closer relationship with consumers. Luxury brands are not necessary to be aloof and supercilious like an indifferent robot. A closer relationship with consumers brings more positive effects.Originality/valueThe current research makes important contributions both to the scientific literature and to the luxury industry. First, this research reveals the effectiveness and underlying mechanisms of behavioral targeting for luxury brands and also compares the effectiveness of behavioral targeting in two cultures, which contributes to the current cross-cultural studies and international marketing research. Second, this study also helps luxury marketers to realize the importance of behavioral targeting and to know how and when they can use this new marketing strategy in a global environment.

User-Friendly Website Design: A Combined Eye-Tracking Study

A simple and intuitive operation – the so-called usability analysis of websites – is indispensable in modern times. In particular, drop-out rates can be applied as an indicator of existing usability problems. Eye-tracking is a proven method for the evaluation of the usability of websites. The aim of the study was to improve the usability of the website of an educational institute for trainees in the region as the target group. For this purpose, the use of an eye-tracking technology was combined with a survey of 30 trainees. The eye-tracking study was task-oriented: subjects were asked to inform themselves of particular course offers, and to register for the relevant courses. This procedure and the subsequent survey provided tangible indications of the search and surfing behaviour of the target group as well as their assessment of the usability of the website. This combination of methods allows the development of recommendations for optimizing the website with regard to its orientation, structure and level of comprehensibility.

Taming the cookie monster with Dutch law – A tale of regulatory failure

Profiling the online behaviour of Internet users has become a defining feature of the Internet. Individual surfing behaviour is tracked by many enterprises for statistical purposes, but also for behavioural advertising and other personalisation services. Profiling implies the processing of personal data often facilitated by cookies and other markers placed on the terminal equipment of Internet users. The European rules for the regulation of cookies and similar technologies were modified in 2009 requiring prior consent of the user, in order to guarantee that the user has some control over the processing of their information. In 2013 the Netherlands introduced probably the strictest implementation of the European rules concerning the installation of cookies. However, in practice the new legal requirements resulted in neglect of the obligations regarding user information on the one hand and in the widespread deployment of annoying banners, popup screens and ‘cookie walls’ on the other. Not only the advertising industry, but also web publishers and even ordinary Internet users opposed the regulation. Furthermore, the regulation, certainly initially, did not lead to increased user control. These and other factors support the conclusion that the Dutch cookie regulation is a case of regulatory failure. This paper discusses the practices that were deployed in the Netherlands and assesses them based on a multi-site study that examined the practices of 100 Dutch websites with regard to the installation of cookies. It further reflects on the response of the Dutch regulator, who –under the pressure of industry and consumers outcry- amended the relevant provisions of the Dutch Telecommunications Act in 2014.

The Effects of Web Site Structure on Attitude: Moderating Effec t of Surfing Behavior

This study examines the effects of types of information on website in terms of advertising effectiveness – memory, attitude, cognitive thoughts. The primary research question for this study is whether information quality and quantity have different effects on consumers’ attitude toward the website. In this study, we manipulate information quality and quantity to see its impact on ad effectiveness. Also, we tested moderating effect by people’s surfing behavior.

Belgium ∙ Facebook Loses the First Round of Its Battle with the Belgian Privacy Commission

1. It all started in February 2015. University researchers, commissioned by the Belgian Privacy Commission, published a report containing a legal analysis, under Belgian law, of Facebook’s revised terms of use and privacy policy. Facebook had applied them as from 30 January 2015.1 These revised terms allowed Facebook to track both users and nonusers across websites and devices, by using social plug-ins and cookies. In particular, by using the socalled ‘datr’ cookie, Facebook was able to monitor both users and non-users in a variety of ways, on and off Facebook.2 The academic research report concluded that these ‘tracking’ activities violated both European and Belgian data protection legislation.3 2. On 13May 2015, the Privacy Commission issued a formal recommendation. It criticised Facebook’s tracking activities, and it formally requested Facebook to cease these activities.4 Although recommendations of the Belgian Privacy Commission are not legally binding, they should de facto be obeyed in order to avoid non-compliance issues. According to the Privacy Commission, Facebook’s tracking activities are more intrusive than other cases of so-called ‘third-party tracking’. It is indeed able to track surfing behaviour over a large number of websites, and to link this surfing behaviour to users’ real identity, social network interactions and even their medical information and religious, sexual and political preferences. To justify its collection of data through social plug-ins, Facebook relies upon the individual’s consent. The Privacy Commission, however, concluded that the conditions for valid (free and informed) consent were not met, and that there was no legal ground for Facebook’s tracking activities, particularly when it came to the tracking of nonusers. 3. After several months of negotiations, it was clear that no amicable solution could be found. The Privacy Commission consequently sued Facebook before the President of the Brussels Court of First Instance in summary proceedings. The relief sought was an injunction prohibiting the use by Facebook of the ‘datr’ cookie through social plugins to track non-users, without first giving them sufficient and adequate information in this re-

The effects of surfing behaviour on the development of external auditory canal exostosis

To examine how individual surfing behaviour affects the development of external auditory canal exostosis and to produce a model to predict exostosis severity. A standardised questionnaire was completed and each participant underwent an otoscopic examination. Surfers were recruited from August to October 2011 from surfing competitions and from colleges in the South West of England. 207 surfers were included, 53 % had evidence of external auditory canal; exostosis: grade 1, 23%; grade 2, 16%, grade 3, 16%. This risk of exostosis significantly increased with (1) surfing for 6 or more years, (2) surfing in the winter months, (3) surfing five or more times per month in the winter and (4) reported ear symptoms. Interestingly, participation in other water sports and wearing earplugs or a hood reduced the risk of developing exostosis. Surfers who surf in England are at significant risk of exostosis. A probability model was designed, incorporating different surfing behaviours and ear symptoms, the first of its kind in exostosis research. This model will be a useful tool for raising awareness of external ear canal exostosis in the surfing community and in assessing individual need for surgical intervention.

Understanding online behavioural advertising: User knowledge, privacy concerns and online coping behaviour in Europe

Online behavioural advertising (OBA) is a special form of targeted advertising. For OBA, it is necessary to collect data about online surfing behaviour, which is usually undertaken by installing ‘cookies’. The use of cookies is heavily debated by policy makers in the US and Europe. Central to this discussion is whether users should provide informed consent prior to the installation of cookies. However, to provide informed consent, it is vital that website users understand the mechanisms of OBA and cookies. This study investigates whether the existing knowledge is sufficient, whether website users are concerned about their privacy, and how they cope with OBA, cookies and the requested informed consent. An online questionnaire (N=2022) was fielded briefly after new European cookie regulations were enacted. The results confirmed that the knowledge is still insufficient to obtain good understanding of this new advertising technique. In addition, the results showed that groups of Internet users did not differ in terms of knowledge, although they did differ in terms of privacy concerns. A comparison of privacy-concerned groups showed that a dual approach is needed in communicating about OBA, not only to inform but also to reduce worries, especially in older and less-educated groups.

Portfolio

Different studies show that programmers are more interested in finding definitions of functions and their uses than variables, statements, or ordinary code fragments. Therefore, developers require support in finding relevant functions and determining how these functions are used. Unfortunately, existing code search engines do not provide enough of this support to developers, thus reducing the effectiveness of code reuse. We provide this support to programmers in a code search system called Portfolio that retrieves and visualizes relevant functions and their usages. We have built Portfolio using a combination of models that address surfing behavior of programmers and sharing related concepts among functions. We conducted two experiments: first, an experiment with 49 C/C++ programmers to compare Portfolio to Google Code Search and Koders using a standard methodology for evaluating information-retrieval-based engines; and second, an experiment with 19 Java programmers to compare Portfolio to Koders. The results show with strong statistical significance that users find more relevant functions with higher precision with Portfolio than with Google Code Search and Koders. We also show that by using PageRank, Portfolio is able to rank returned relevant functions more efficiently.