Big data, Bigger privacy concern?

In light of the rapid growth of big data applications in times where the internet of things is taking over personal privacy, this paper studies the area where data analytics and privacy concerns overlap. Identifying that anonymization and consent frequently do not suffice for user data, this paper also points out the weaknesses of regulations. A survey with 200 respondents showed that the awareness of big data capabilities caused significant privacy concern and willingness for (counter-) action, thus emphasizing that big data-driven firms should take a possible shift in user perception and behavior into account when formulating their strategy

Alike people, alike interests? Inferring interest similarity in online social networks

Understanding how much two individuals are alike in their interests (i.e., interest similarity) has become virtually essential for many applications and services in Online Social Networks (OSNs). Since users do not always explicitly elaborate their interests in OSNs like Facebook, how to determine users' interest similarity without fully knowing their interests is a practical problem. In this paper, we investigate how users' interest similarity relates to various social features (e.g. geographic distance); and accordingly infer whether the interests of two users are alike or unalike where one of the users' interests are unknown. Relying on a large Facebook dataset, which contains 479,048 users and 5,263,351 user-generated interests, we present comprehensive empirical studies and verify the homophily of interest similarity across three interest domains (movies, music and TV shows). The homophily reveals that people tend to exhibit more similar tastes if they have similar demographic information (e.g., age, location), or if they are friends. It also shows that the individuals with a higher interest entropy usually share more interests with others. Based on these results, we provide a practical prediction model under a real OSN environment. For a given user with no interest information, this model can select some individuals who not only exhibit many interests but also probably achieve high interest similarities with the given user. Eventually, we illustrate a use case to demonstrate that the proposed prediction model could facilitate decision-making for OSN applications and services.This work has been funded by the European Union under the project eCOUSIN (EU-FP7-318398) and the project SITAC (ITEA2-11020). This work has also been partially funded by the Ministerio de Economía y Competitividad of SPAIN through the project BigDatAAM (FIS2013-47532-C3-3-P).Publicad

Three Essays on Individuals’ Vulnerability to Security Attacks in Online Social Networks: Factors and Behaviors

With increasing reliance on the Internet, the use of online social networks (OSNs) for communication has grown rapidly. OSN platforms are used to share information and communicate with friends and family. However, these platforms can pose serious security threats to users. In spite of the extent of such security threats and resulting damages, little is known about factors associated with individuals’ vulnerability to online security attacks. We address this gap in the following three essays. Essay 1 draws on a synthesis of the epidemic theory in infectious disease epidemiology with the social capital theory to conceptualize factors that contribute to an individual’s role in security threat propagation in OSN. To test the model, we collected data and created a network of hacked individuals over three months from Twitter. The final hacked network consists of over 8000 individual users. Using this data set, we derived individual’s factors measuring threat propagation efficacy and threat vulnerability. The dependent variables were defined based on the concept of epidemic theory in disease propagation. The independent variables are measured based on the social capital theory. We use the regression method for data analysis. The results of this study uncover factors that have significant impact on threat propagation efficacy and threat vulnerability. We discuss the novel theoretical and managerial contributions of this work. Essay 2 explores the role of individuals’ interests in their threat vulnerability in OSNs. In OSNs, individuals follow social pages and post contents that can easily reveal their topics of interest. Prior studies show high exposure of individuals to topics of interest can decrease individuals’ ability to evaluate the risks associated with their interests. This gives attackers a chance to target people based on what they are interested in. However, interest-based vulnerability is not just a risk factor for individuals themselves. Research has reported that similar interests lead to friendship and individuals share similar interests with their friends. This similarity can increase trust among friends and makes individuals more vulnerable to security threat coming from their friends’ behaviors. Despite the potential importance of interest in the propagation of online security attacks online, the literature on this topic is scarce. To address this gap, we capture individuals’ interests in OSN and identify the association between individuals’ interests and their vulnerability to online security threats. The theoretical foundation of this work is a synthesis of dual-system theory and the theory of homophily. Communities of interest in OSN were detected using a known algorithm. We test our model using the data set and social network of hacked individuals from Essay 1. We used this network to collect additional data about individuals’ interests in OSN. The results determine communities of interests which were associated with individuals’ online threat vulnerability. Moreover, our findings reveal that similarities of interest among individuals and their friends play a role in individuals’ threat vulnerability in OSN. We discuss the novel theoretical and empirical contributions of this work. Essay 3 examines the role addiction to OSNs plays in individuals’ security perceptions and behaviors. Despite the prevalence of problematic use of OSNs and the possibility of addiction to these platforms, little is known about the functionalities of brain systems of users who suffer from OSN addiction and their online security perception and behaviors. In addressing these gaps, we have developed the Online addiction & security behaviors (OASB) theory by synthesizing dual-system theory and extended protection motivation theory (PMT). We collected data through an online survey. The results indicate that OSN addiction is rooted in the individual’s brain systems. For the OSN addicted, there is a strong cognitive-emotional preoccupation with using OSN. Our findings also reveal the positive and significant impact of OSN addiction on perceived susceptibility to and severity of online security threats. Moreover, our results show the negative association between OSN addiction and perceived self-efficacy. We discuss the theoretical and practical implications of this work

Conceptualizing the Electronic Word-of-Mouth Process: What We Know and Need to Know About eWOM Creation, Exposure, and Evaluation

Electronic word of mouth (eWOM) is a prevalent consumer practice that has undeniable effects on the company bottom line, yet it remains an over-labeled and under-theorized concept. Thus, marketers could benefit from a practical, science-based roadmap to maximize its business value. Building on the consumer motivation–opportunity–ability framework, this study conceptualizes three distinct stages in the eWOM process: eWOM creation, eWOM exposure, and eWOM evaluation. For each stage, we adopt a dual lens—from the perspective of the consumer (who sends and receives eWOM) and that of the marketer (who amplifies and manages eWOM for business results)—to synthesize key research insights and propose a research agenda based on a multidisciplinary systematic review of 1050 academic publications on eWOM published between 1996 and 2019. We conclude with a discussion of the future of eWOM research and practice

An architecture for evolving the electronic programme guide for online viewing

Watching television and video content is changing towards online viewing due to the proliferation of content providers and the prevalence of high speed broadband. This trend is coupled to an acceleration in the move to watching content using non-traditional viewing devices such as laptops, tablets and smart phones. This, in turn, poses a problem for the viewer in that it is becoming increasingly difficult to locate those programmes of interest across such a broad range of providers. In this thesis, an architecture of a generic cloud-based Electronic Programme Guide (EPG) system has been developed to meet this challenge. The key feature of this architecture is the way in which it can access content from all of the available online content providers and be personalized depending on the viewer’s preferences and interests, viewing device, internet connection speed and their social network interactions. Fundamental to its operation is the translation of programme metadata adopted by each provider into a unified format that is used within the core system. This approach ensures that the architecture is extensible, being able to accommodate any new online content provider through the addition of a small tailored search agent module. The EPG system takes the programme as its core focus and provides a single list of recommendations to each user regardless of their origins. A prototype has been developed in order to validate the proposed system and evaluate its operation. Results have been obtained through a series of user trials to assess the system’s effectiveness in being able to extract content from several sources and to produce a list of recommendations which match the user’s preferences and context. Results show that the EPG is able to offer users a single interface to online television and video content providers and that its integration with social networks ensures that the recommendation process is able to match or exceed the published results from comparable, but more constrained, systems