VTechWorks Administration

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Browsing VTechWorks Administration by Department "Business Information Technology"

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    Information privacy behavior in the use of Facebook apps: A personality-based vulnerability assessment
    van der Schyff, Karl; Flowerday, Stephen; Lowry, Paul Benjamin (Elsevier, 2020-08-01)
    The unauthorized use of personal information belonging to users of apps integrated with the Facebook platform affects millions of users. Crucially, although privacy concerns and awareness have increased, the use of these apps, and related privacy behaviors, remain largely unchanged. Given that such privacy behaviors are likely influenced by individuals' personality traits, it is imperative to better understand which personality traits make individuals more vulnerable to such unauthorized uses. We build on a recontextualized version of the theory of planned behavior (TPB) to evaluate the influence of the Big Five personality traits on attitudes toward Facebook privacy settings, social norms, and information privacy concerns (IPCs)—all within the context of Facebook app use. To evaluate this study's model, we analyzed 576 survey responses by way of partial least squares path modeling. Results indicate that highly extraverted individuals are particularly vulnerable to privacy violations (e.g., unauthorized use of personal information) because of their negative attitudes toward Facebook privacy settings. Our post hoc analysis uncovered interesting combinations of personality traits that make individuals particularly vulnerable to the unauthorized use of app-based information. In particular, the combination of extraversion and conscientiousness had a negative effect on individuals' attitude toward privacy settings. We also found a significant negative relationship between IPCs and intention to use Facebook apps. Finally, we found a positive relationship between social norms and intentions. Taken together, these results infer that individuals are likely to be influenced by their peers in the use of Facebook apps but that their intentions to use these apps declines as privacy concerns increase.
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    A Surrogate-based Generic Classifier for Chinese TV Series Reviews
    Ma, Yufeng; Xia, Long; Shen, Wenqi; Zhou, Mi; Fan, Weiguo (2016-11-21)
    With the emerging of various online video platforms like Youtube, Youku and LeTV, online TV series' reviews become more and more important both for viewers and producers. Customers rely heavily on these reviews before selecting TV series, while producers use them to improve the quality. As a result, automatically classifying reviews according to different requirements evolves as a popular research topic and is essential in our daily life. In this paper, we focused on reviews of hot TV series in China and successfully trained generic classifiers based on eight predefined categories. The experimental results showed promising performance and effectiveness of its generalization to different TV series.
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    Who’s winning in the game of attack and defend?
    Baker, Wade (Executive Media Pty Ltd, 2021-07-09)
    It’s often said that the ‘playing field’ of cyber security is heavily tilted in favour of attackers. Defenders must do everything perfectly, while attackers gain the upper hand if given the slightest opportunity. But is that an accurate depiction of the contest? Not exactly, according to recent research.