This paper seeks to understand how the micro-blogging tool, Twitter, can be used effectively by marketers and advertisers by incorporating the attributes of information quality, information usefulness and source credibility into their tweets. Case analyses of five of the most popular Twitter accounts were conducted with regards to the appearance of each account and the content of their tweets. Recommendations for improving the quality of each Twitter account were also provided. / text

Crowdsourcing systems enable new opportunities for requesters with limited funds to accomplish various tasks using human computation. However, the power of human computation is abused by malicious requesters who create malicious campaigns to manipulate information in web systems such as social networking sites, online review sites, and search engines. To mitigate the impact and reach of these malicious campaigns to targeted sites, we propose and evaluate a machine learning based classification approach for detecting malicious campaigns in crowdsourcing platforms as a first line of defense, and build a malicious campaign blacklist service for targeted site providers, researchers and users. Specifically, we (i) conduct a comprehensive analysis to understand the characteristics of malicious campaigns and legitimate campaigns in crowdsourcing platforms, (ii) propose various features to distinguish between malicious campaigns and legitimate campaigns, (iii) evaluate a classification approach against baselines, and (iv) build a malicious campaign blacklist service. Our experimental results show that our proposed approaches effectively detect malicious campaigns with low false negative and false positive rates.

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abstract: The rapid advancements of technology have greatly extended the ubiquitous nature of smartphones acting as a gateway to numerous social media applications. This brings an immense convenience to the users of these applications wishing to stay connected to other individuals through sharing their statuses, posting their opinions, experiences, suggestions, etc on online social networks (OSNs). Exploring and analyzing this data has a great potential to enable deep and fine-grained insights into the behavior, emotions, and language of individuals in a society. This proposed dissertation focuses on utilizing these online social footprints to research two main threads – 1) Analysis: to study the behavior of individuals online (content analysis) and 2) Synthesis: to build models that influence the behavior of individuals offline (incomplete action models for decision-making). A large percentage of posts shared online are in an unrestricted natural language format that is meant for human consumption. One of the demanding problems in this context is to leverage and develop approaches to automatically extract important insights from this incessant massive data pool. Efforts in this direction emphasize mining or extracting the wealth of latent information in the data from multiple OSNs independently. The first thread of this dissertation focuses on analytics to investigate the differentiated content-sharing behavior of individuals. The second thread of this dissertation attempts to build decision-making systems using social media data. The results of the proposed dissertation emphasize the importance of considering multiple data types while interpreting the content shared on OSNs. They highlight the unique ways in which the data and the extracted patterns from text-based platforms or visual-based platforms complement and contrast in terms of their content. The proposed research demonstrated that, in many ways, the results obtained by focusing on either only text or only visual elements of content shared online could lead to biased insights. On the other hand, it also shows the power of a sequential set of patterns that have some sort of precedence relationships and collaboration between humans and automated planners. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

Thesis (MPhil)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: The primary purpose of this study is to explore the social media habits of South African previously disadvantaged entrepreneurs and the way in which the activity of online social networking through social networking sites (SNS) results in the outcome of building social capital for a business venture. At the heart of addressing the research topic is the concept of selfefficacy, which is explored as a key component of human motivation and behaviour. The study explores how self-efficacy beliefs are developed with regard to social media usage and their potential to influence positive outcomes for a business. Based on the research topic, the study which is empirical in nature, has applied a qualitative research design in order to interpret rather than measure self-efficacy behaviours related to social media usage. A purposive non-probability sampling procedure has been adopted to select twelve previously disadvantaged South African entrepreneurs for the study. Semi-structured interviews provide for an interactive and insightful data collection process. As a qualitative study, attention is given to guidelines which establish reliability and validity. Key findings from the study support and refine established Internet selfefficacy research (Eastin & LaRose, 2000) based on Social Cognitive Theory (Bandura, 1986). Based on the established relationships between various constructs and self-efficacy beliefs, the results of the study have been interpreted positively. The findings of the study contribute to the current digital divide debate, and point to a narrowing of the access and participation gap. According to the sample, social media has become embedded in their daily lives for both social and business purposes, and is contributing towards building social capital. This study provides scope to further explore social media as a new opportunity for previously disadvantaged entrepreneurs in South Africa.

The study investigates the influence of online and social media in HIV prevention, with a focus on young women and HIV risk perception related to age-disparate relationships. The study was conducted using an existing online prevention HIV prevention platform by means of a self-administered online questionnaire. Convenience sampling was used to recruit between 250 and 500 users between the ages of 18 to 24 years. The results revealed poor HIV risk perception in 46% of respondents, which seemed influenced by their perception (38%) that older men are safer sexual partners than younger men. In addition, this poor risk perception is seemingly influenced by the fact that many young women (77%) involved in these relationships, viewed these as primarily based on love and affection and as being “safe”, challenging the commonly held perception that these are primarily transactional in nature. Further respondents reported at rates of between 38% and 44% that the platform had improved their HIV risk perception related to these relationships. In summary, the research resulted in several recommendations to improve the platform, including improving ways of getting more and on-going feedback from users on their HIV risk perceptions and designing content and engagement strategies to address these. / Sociology / M. A. (Social Behaviour Studies in (HIV/AIDS)

This study presents insights on career management in the creative and cultural industries in Scotland with detailed exploration into practices and strategies employed by cultural workers. Following a phenomenological approach, the study has used subjective data of individual career experiences and interpreted them into objective patterns of career management. Using qualitative research interviews and thematic analysis, the doctoral study explored the career management experiences of thirty six cultural workers and identified particular strategies adopted in the self-management of precarious and unpredictable careers. Employment in the creative and cultural industries is with precarious which constitutes a specific environment for career management and career progression. Not enough is known about the ways in which cultural workers manage their careers in these circumstances. The aim of this study was to understand the realities of contemporary career management in the creative and cultural industries and to identify particular practices and strategies in which creative careers might be managed. Beyond the scholars in this field, this research is of interest to cultural workers, policy makers in the creative and cultural industries more broadly and higher education institutions preparing graduates for work in the creative and cultural industries. The empirical evidence gathered can better inform cultural workers of effective career management strategies and propose policy interventions that would facilitate effective career management and career management education. Key findings focus on the use of online / social media within creative careers and how such activity takes place; the development of a new harmony between art and economic logics and the application of development based career strategies in creative careers, with cultural workers being more managerial than they even recognise themselves. The findings from this study offers confirmation to what is already known about careers in the creative and cultural industries, greater depth and detail to what is already known and extend understanding about the relationship disconnect between individual career Career Management in the Creative and Cultural Industries Abstract management strategies and the policies designed to support cultural workers – policies which focus on growth and development of the industry but not those individuals who make up the industry. Exploration of the phenomenon of career management in the creative and cultural industries requires further research, which could include: alternative methodologies to elicit perceptions based on the findings from this study, deeper exploration into both the difference in career management within the creative and cultural industries and the emerging relationship between art and economic logic.