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The purpose of this paper is to address the problem of profiling human behaviour patterns captured in surveillance videos for the application of online normal behaviour recognition and anomaly detection.

A novel framework is developed for automatic behaviour profiling and online anomaly detection without any manual labeling of the training dataset.

Experimental results demonstrate the effectiveness and robustness of the authors' approach using noisy and sparse datasets collected from one real surveillance scenario.

To discover the topics, co‐clustering topic model not only captures the correlation between words, but also models the correlations between topics. The major difference between the conventional co‐clustering algorithms and the proposed CCMT is that CCMT shows a major improvement in terms of recall, i.e. interpretability.

Entrepreneurial trait and behaviour approaches are used to identify differing entrepreneurial profiles. Specifically, this study aims to determine which entrepreneurial competencies (ECs) can predict entrepreneurial action (EA) for distinct profiles, such as male versus female, start-up versus established and for entrepreneurs within different age groups and educational levels.

The research was conducted using a survey method on a large sample of 1,150 South African entrepreneurs. Chi-squared automatic interaction detection (CHAID) algorithms were used to build decision trees to illustrate distinct entrepreneurial profiles.

Each profile has a different set of ECs that predict EA, with a growth mindset being the most significant predictor of action. Therefore, this study confirms that a “one-size-fits-all” approach cannot be applied when profiling entrepreneurs.

From a pedagogical standpoint, different combinations of these ECs for each profile provide priority information for identification of appropriate candidates (e.g. the highest potential for success) and training initiatives, effective pedagogies and programme design (e.g. which individual ECs should be trained and how should they be trained).

Previous work has mostly focused on demographic variables and included a single sample to profile entrepreneurs. This study maintains much wider applicability in terms of examining profiles in a systematic way. The large sample size supports quantitative analysis of the comparisons between different entrepreneurial profiles using unconventional analyses. Furthermore, as far as can be determined, this represents the first CHAID conducted in a developing country context, especially South Africa, focusing on individual ECs predicting EA.

The article aims to present a holistic approach to analysis of patterns on complex online profiles, demonstrated on profiles of European scientists.

An existing analytical framework was developed to incorporate a holistic understanding of online profiles. The framework was applied to a sample of 188 online profiles belonging to 48 European scientists. The profile data were studied on three levels (content‐unit level, profile‐instance level, and profile‐network level), using methods of the qualitative comparative analysis to derive profiling patterns.

The approach developed in this work generated profiling patterns for European scientists. The patterns exist on all three levels, forming a hierarchy. This pattern structure shows the variety of ways in which scientists can use the internet for self‐presentation.

The study was based on a holistic understanding of online self‐presentation, acknowledging that personal presentation can be spread across different platforms. The study presented shows how this understanding can be used when analysing online profiling behaviour. The profiling patterns of European scientists identified in this study supplement existing typologies. The study serves as a foundation to structure further research as well as to inform practitioners.

Wawasan Open University Library undertook a survey study, based on the Wilson’s revised model of information behaviour (1999), to profile information-seeking behaviour of their distance students in using library resources in their research and learning activities. The paper aims to discuss these issues.

Using random sampling method, samples were selected to ensure proper representation of the population across four schools of studies and five regional centres. A total of 550 questionnaires were sent to undergraduate and postgraduate students, and 435 completed questionnaires were returned with a success response rate of 79 per cent.

Findings indicated significant differences between undergraduate and postgraduate students in using the university’s MyDigital Library and physical library for their information needs. Findings also indicated significant difference between first-year and post-first-year students in using internet search engines as part of their information-seeking process.

Students improving on their information-seeking behaviour in the learning and research work paved way for them to better experience university vivacity and not isolate themselves from distance learning.

This paper acknowledges the importance of promoting good information-seeking behaviour among distance learners in the scholarship of learning and research work. The paper also amplifies the important role library plays in minimizing students’ sense of isolation in university learning experience.

The purpose of this paper is to propose that “social demarketing” campaigns need to recognize unique sub segments of individuals engaging in behaviours having substantial negative societal impacts.

Volume segmentation and extremely frequent behaviour theory is applied to examining several unique sub segments among survey data (n=6,393) of Americans not engaging and engaging in anti‐social behaviour (“giving‐the‐finger”) to other motorists while driving.

Less than 2 percent of Americans are estimated to enact 40 percent of the total incidences of “giving‐the‐finger” to other motorists; three unique sub segments of the chronic anti‐social actors participate in different lifestyles (including media usage behaviours) and each has unique demographic profiles.

The study is based on two years of a national survey taken in one country and self‐reports only. The implications support the propositions of a general theory of extremely frequent consumption behaviour.

Government demarcating programs are likely to increase in effectiveness through tailoring a few strategies, rather than one, to influence unique segments of chronic anti‐social actors.

The paper provides individual‐level analysis of chronic anti‐social actors engaging in road‐rage related behaviours and compares them to one another as well as non‐equivalent comparison groups of actors not engaging in such behaviour; the paper describes the merits of experience frequency segmentation.

The development and reinforcement of context‐specific behaviors support the implementation of marketing strategy. Discusses the limitations of traditional strategy implementation pursuits and then proceeds to report the results of two independent but related studies that consider two methods of behavior management – market orientation profiling, and behavioral repertoires – and their effect on marketing strategy and organizational performance. Results indicate that these methods provide a context for the implementation of specific marketing strategies by serving as a moderator of employee behavior and can be used strategically by organizations to guide service applications. Concludes by providing prescriptive steps that managers can consider in efforts to adopt these approaches to marketing strategy implementation.

The paper aims at a multi‐faceted review of scholarly work, analyzing the current state of empirical studies dealing with privacy and online social networking (OSN) as well as the theoretical “puzzle” of privacy approaches related to OSN usage from the background of diverse disciplines. Drawing on a more pragmatic and practical level, aspects of privacy management are presented as well.

Based on individual privacy concerns and also publicly communicated threats, information privacy has become an important topic of public and scholarly discussion. Beside diverse positive aspects of OSN sites for users, their information is for example also being used for data mining and profiling, pre‐recruiting information as well as economic espionage. This review highlights information privacy mainly from an individual point‐of‐view, focusing on the usage of OSN sites (OSNs).

This analysis of scholarly work shows the following findings: first, adults seem to be more concerned about potential privacy threats than younger users; second, policy makers should be alarmed by a large part of users who underestimate risks of their information privacy on OSNs; third, in the case of using OSNs and its services, traditional one‐dimensional privacy approaches fall short. Hence, findings of this paper further highlight the necessity to focus on multidimensional and multidisciplinary frameworks of privacy, for example considering a so‐called “privacy calculus paradigm” and rethinking “fair information practices” from a more and more ubiquitous environment of OSNs.

The results of the work presented in this paper give new opportunities for research as well as suggestions for privacy management issues for OSN providers and users.

The purpose of this paper is to develop information behaviour profiles for nursing students, to help inform information literacy programmes.

The methods include further analysis of quantitative findings (previously reported in part 1), together with qualitative research data collection and analysis. Critical incident type interviews with 11 students were transcribed and analysed using an interpretative categorisation method that used dendrograms for data display and analysis. From the regression analysis of the quantitative data, the micro-processes for information seeking were linked to learning styles, and then to personality traits to generate information seeking profiles. Integration of the qualitative findings led to development of a task-based information search model.

The start list of seven categories for qualitative analysis (derived from a literature review) was refined (one category added, one removed, with some relabelling). The quantitative data analysis revealed seven profiles (deep adventurer, deep identifier, deep investigator, strategic all-rounder, strategic collector, surface co-ordinator, surface skimmer, each linked to a particular learning style, personality trait, and preferred information seeking micro-processes).

The data were collected at only one university and the profiles and the model need to be validated with data from other groups of nursing students. The findings on micro-processes consolidate and extend previous research.

The profiles should inform information literacy programmes as they show that information search profiles may be more varied than assumed. The information search model extends previous task-based information search models.

The information search profiles have not been identified previously.