Includes bibliography. / With new political developments breeding opportunities for crises, proliferation of new media types increasing exposure to crises, there is a growing awareness of the potential, influence, impact and capabilities of social media. Focusing on South Africa's Secrecy Bill, a crisis with implications on access to information and media freedom, this study provides a discussion of the dynamics of crisis communication online. By undertaking an analysis of the uses of social media during deliberations of the Secrecy Bill and its implications, the study sought to explore how young South Africans have embraced social media as a communication tool. An examination of the literature reveals that younger generations are frequent bloggers and users of Twitter, a popular social media site. Focusing on these two platforms, through a qualitative content analysis, findings show that their contribution to deliberations was mainly to make sense of the crisis and distribute relevant materials relating to the debate.

The idea would be to unify it into a system where people from different countries can provide information on their hometowns, helping people who are interested in them. The system created is a collaborative Web system in which people can access and edit contents by entering information about their hometowns, and this information will help other people who decide to move to the different cities.

The introduction of social media presented a significant challenge to the often secretive culture of the U.S. military. DoD struggled with publishing a social media policy forcing the armed services to develop their own policies, which were all inconsistent. When DoD finally established a social media policy in 2007, certain social media sites were banned from the Services' networks for a variety of reasons -- the one most often quoted was risk. In February 2010, DoD completely reversed its policy and embraced social media. The new policy required the military to allow open access on the networks to social media for all employees, despite much resistance from internal stakeholders. In this dissertation, I research three significant events during the development of the DoD Social Media Policy: (1) the pre-policy environment, including actions to restrict social media on the DoD networks (2) coming to closure on the current policy and how DoD made its decision to open the networks to social media, and (3) the post-closure period and its ongoing and new tensions. This research project is a qualitative study of the evolution of social media (pre- and post a formal policy) within the DoD through the lens of social construction of technology (SCOT) and a discourse analysis of the policy formulation. My findings indicated that references to security and privacy risk, sociotechnological inevitability, responsible online behavior and youth were particularly important to the military discourse on social media. The study concludes the risk is worth to benefit to service members who want to use social media. Service members accept the sociotechnological inevitability of social media and feel they are responsible enough to use it wisely. The issue of youth was found to be not really a concern and leadership emerged as a discourse and is often referenced to solve any issue that may arise from the use of social media within the military environment. / Ph. D.

Social networking includes social networking sites (SNSs) as well as apps. The purpose of this thesis was to investigate the impact of social networking tech-nology on students.  The  research questions  focused  how university students experience  their  interaction  with  social  networking  regarding  advantages and disadvantages, and for what purposes they are using it personal, professional or study). A quantitative surveys study was used and data was collected through online questionnaires delivered via SNSs, e-mails and through delivery and col-lection  method. 122  valid  responses  were collected  and 17 invalid responses were discarded. The questionnaire framework was built by means of the con-cept of ease of use from Technology Acceptance Model (TAM) and the five values of Uses and Gratification Theory; “purposive value”, “self-discovery”, “maintaining interpersonal interconnectivity”, “social enhancement value” and “entertainment value”. The findings showed that 64% considered themselves to be positively influenced by SNSs and 27% to be neither positively or nega-tively influenced. Only 11 % considered that SNSs influenced them negatively. According to our findings, some of the most frequent advantages are keeping in touch with family and friends, cost and time efficient, easy to use and entertaining. And for the disadvantages, the responses were mostly time consuming, health  issues,  privacy  issues,  addiction  to  technology  and  cyber  bulling.  The majority of respondents reported using SNS firstly for personal use, secondly for study use and the professional use was the least selected. 88% of the respondents thought that it is easy to use SNSs. The purposive value of SNS use was to get information, the self-discovery value to learning about oneself and others, for the maintaining interpersonal connectivity, to stay in touch, and for the entertainment value, it was to pass time away when bored. The results indicated  that  the  social  enhancement  value  was  not  very  important  for  the  respondents.

M Phil / Since the establishment of the Internet, innovative technologies have evolved rapidly and 'social networking' technologies specifically have gained value from the recent surge in popularity and increased use of these networked technologies. The exposure and growth that social networking technologies have experienced in recent history has created a phenomenal following by individuals from diverse walks of life. However, the negative press that currently surrounds online social networks is ardent and in some cases valid, overshadowing the opportunities that Online Social Networking may present to organisations. The focus of this study fell on the possible effect of employee participation in Online Social Networking on productivity. In current workplaces that rely on intellectual capital to be successful in business, employees are a key source of knowledge and mainly responsible for intellectual capital growth. It was therefore argued in this study that organisations should critically investigate the relevance of collaborative technology such as online social networking in order to support employees in the processes required for knowledge creation. This study provided an overview of the literature review findings as well as the relevant empirical research findings with regard to what Online Social Networking entails; what the possible consequences could be if employees were allowed access to online social networks without restriction; and how online social networks could contribute to the productivity of an organisation. This study aimed to serve as a foundation on which the University of Johannesburg could build a strategy that aspired to incorporate online social networking within this institution, in order to promote a knowledge sharing culture.

Facebook is the reigning king of Social Networking Sites (SNSs). Due to Facebook’s impact on current culture, researchers have been focused on how it interacts with its members on a variety of issues including well-being, personal identity, personality type, and motivation. While the topics of personality type and motivation have been investigated separately, their possible relationship has not been examined until now. Participants consisted of 415 students from the University of Central Florida were surveyed with an International Personality Item Pool (IPIP), a Facebook Intensity Survey, and a Facebook Motivation Scale. Results showed that the personality traits of agreeableness, conscientiousness, and emotional stability were positively related to intrinsic and extrinsic motivation to make posts on Facebook, extraversion was found to be related to extrinsic motivation to make posts, and intellect was found to have almost no relationship to motivation. In addition, participants who were higher in the traits of agreeableness, conscientiousness, and emotional stability were more likely to be more intensely involved in Facebook than those who were high in extraversion and intellect. Finally, I found that participants who were more intensely involved in Facebook experienced more motivation to make posts on Facebook.

Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter face two problems 1) their online social friendships and activities are scattered across SNSs. It is difficult for them to keep track of all their friends and the information about their friends online social activities. 2) they are often overwhelmed by the huge amount of social data (friends updates and other activities). To solve these two problems, this research proposes an approach, named SocConnect. Soc- Connect allows users to create personalized social and semantic contexts for their social data. Users can blend their friends across different social networking sites and group them in different ways. They can also rate friends and/or their activities as favourite, neutral or disliked. SocConnect also can recommend unread friend updates to the user based on user previous ratings on activi- ties and friends, using machine learning techniques. The results from one pilot studies show that users like SocConnects functionalities are needed and liked by the users. An evaluation of the effectiveness of several machine learning algorithms demonstrated that , and machine learning can be usefully applied in predicting the interest level of users in their social network activities, thus helping them deal with the network overload.

Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter face two problems 1) their online social friendships and activities are scattered across SNSs. It is difficult for them to keep track of all their friends and the information about their friends online social activities. 2) they are often overwhelmed by the huge amount of social data (friends updates and other activities). To solve these two problems, this research proposes an approach, named SocConnect. Soc- Connect allows users to create personalized social and semantic contexts for their social data. Users can blend their friends across different social networking sites and group them in different ways. They can also rate friends and/or their activities as favourite, neutral or disliked. SocConnect also can recommend unread friend updates to the user based on user previous ratings on activi- ties and friends, using machine learning techniques. The results from one pilot studies show that users like SocConnects functionalities are needed and liked by the users. An evaluation of the effectiveness of several machine learning algorithms demonstrated that , and machine learning can be usefully applied in predicting the interest level of users in their social network activities, thus helping them deal with the network overload.

Faculty of Criminology, Justice and Policy Studies

Users of Social Networking Sites (SNSs) like Facebook, MySpace, LinkedIn, or Twitter face two problems 1) their online social friendships and activities are scattered across SNSs. It is difficult for them to keep track of all their friends and the information about their friends online social activities. 2) they are often overwhelmed by the huge amount of social data (friends updates and other activities). To solve these two problems, this research proposes an approach, named SocConnect. Soc- Connect allows users to create personalized social and semantic contexts for their social data. Users can blend their friends across different social networking sites and group them in different ways. They can also rate friends and/or their activities as favourite, neutral or disliked. SocConnect also can recommend unread friend updates to the user based on user previous ratings on activi- ties and friends, using machine learning techniques. The results from one pilot studies show that users like SocConnects functionalities are needed and liked by the users. An evaluation of the effectiveness of several machine learning algorithms demonstrated that , and machine learning can be usefully applied in predicting the interest level of users in their social network activities, thus helping them deal with the network overload.