Mining the online social network data: Influence, summarization, and organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Mining the Online Social Network Data: Influence, Summarization, and Organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Mitigating Social Risk in the Extractive Sector: Developing Intercultural Competence as a Tool for Negotiating Western-Indigenous Perspectives within the Undergraduate Mining Engineering Curriculum

Drawing upon critical, communications, and educational theories, this thesis develops a novel framing of the problem of social risk in the extractive sector, as it relates to the building of respectful relationships with indigenous peoples. Building upon Bakhtin’s dialogism, the thesis demonstrates the linkage of this aspect of social risk to professional education, and specifically, to the undergraduate mining engineering curriculum, and develops a framework for the development of skills related to intercultural competence in the education of mining engineers. The knowledge of social risk, as well as the level of intercultural competence, of students in the mining engineering program, is investigated through a mixture of surveys and focus groups – as is the impact of specific learning interventions. One aspect of this investigation is whether development of these attributes alters graduates’ conception of their identity as mining engineers, i.e. the range and scope of responsibilities, and understanding of to whom responsibilities are owed, and their role in building trusting relationships with communities. Survey results demonstrate that student openness to the perspectives of other cultures increases with exposure to the second year curriculum. Students became more knowledgeable about social dimensions of responsible mining, but not about cultural dimensions. Analysis of focus group data shows that students are highly motivated to improve community perspectives and acceptance. It is observed that students want to show respect for diverse peoples and communities where they will work, but they are hampered by their inability to appreciate the viewpoints of people who do not share their values. They embrace benefit sharing and environmental protection as norms, but they mistakenly conclude that opposition to mining is rooted in a lack of education rather than in cultural values. Three, sequential, threshold concepts are identified as impeding development of intercultural competence: Awareness and Acknowledgement of Different Forms of Knowledge; Recognition that Value Systems are a Function of Culture; Respect for varied perceptions of Social Wellbeing and Quality of Life. Future curriculum development in the undergraduate mining engineering program, as well as in other educational programs relevant to the extractive sector, can be effectively targeted by focusing on these threshold concepts.

Corporate social responsibility reporting in the mining sector of Tanzania:(Lack of) government regulatory controls and NGO activism

Purpose – The purpose of this paper is to contribute to the ongoing debate on governance, accountability, transparency and corporate social responsibility (CSR) in the mining sector of a developing country context. It examines the reporting practices of the two largest transnational gold-mining companies in Tanzania in order to draw attention to the role played by local government regulations and advocacy and campaigning by nationally organised non-governmental organisations (NGOs) with respect to promoting corporate social reporting practices. Design/methodology/approach – The paper takes a political economy perspective to consider the serious implications of the neo-liberal ideologies of the global capitalist economy, as manifested in Tanzania’s regulatory framework and in NGO activism, for the corporate disclosure, accountability and responsibility of transnational companies (TNCs). A qualitative field case study methodology is adopted to locate the largely unfamiliar issues of CSR in the Tanzanian mining sector within a more familiar literature on social accounting. Data for the case study were obtained from interviews and from analysis of documents such as annual reports, social responsibility reports, newspapers, NGO reports and other publicly available documents. Findings – Analysis of interviews, press clips and NGO reports draws attention to social and environmental problems in the Tanzanian mining sector, which are arguably linked to the manifestation of the broader crisis of neo-liberal agendas. While these issues have serious impacts on local populations in the mining areas, they often remain invisible in mining companies’ social disclosures. Increasing evidence of social and environmental ills raises serious questions about the effectiveness of the regulatory frameworks, as well as the roles played by NGOs and other pressure groups in Tanzania. Practical implications – By empowering local NGOs through educational, capacity building, technological and other support, NGOs’ advocacy, campaigning and networking with other civil society groups can play a pivotal role in encouraging corporations, especially TNCs, to adopt more socially and environmentally responsible business practices and to adhere to international and local standards, which in turn may help to improve the lives of many poor people living in developing countries in general, and Tanzania in particular. Originality/value – This paper contributes insights from gold-mining activities in Tanzania to the existing literature on CSR in the mining sector. It also contributes to political economy theory by locating CSR reporting within the socio-political and regulatory context in which mining operations take place in Tanzania. It is argued that, for CSR reporting to be effective, robust regulations and enforcement and stronger political pressure must be put in place.

Improving matching process in social network

Online dating networks, a type of social network, are gaining popularity. With many people joining and being available in the network, users are overwhelmed with choices when choosing their ideal partners. This problem can be overcome by utilizing recommendation methods. However, traditional recommendation methods are ineffective and inefficient for online dating networks where the dataset is sparse and/or large and two-way matching is required. We propose a methodology by using clustering, SimRank to recommend matching candidates to users in an online dating network. Data from a live online dating network is used in evaluation. The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.

A social matching system for an online dating network : a preliminary study

Due to the change in attitudes and lifestyles, people expect to find new partners and friends via various ways now-a-days. Online dating networks create a network for people to meet each other and allow making contact with different objectives of developing a personal, romantic or sexual relationship. Due to the higher expectation of users, online matching companies are trying to adopt recommender systems. However, the existing recommendation techniques such as content-based, collaborative filtering or hybrid techniques focus on users explicit contact behaviors but ignore the implicit relationship among users in the network. This paper proposes a social matching system that uses past relations and user similarities in finding potential matches. The proposed system is evaluated on the dataset collected from an online dating network. Empirical analysis shows that the recommendation success rate has increased to 31% as compared to the baseline success rate of 19%.

The resource boom's underbelly : criminological impacts of mining development

Australia is currently in the midst of a major resources boom. Resultant growing demands for labour in regional and remote areas have accelerated the recruitment of non resident workers, mostly contractors, who work extended block rosters of 12-hour shifts and are accommodated in work camps, often adjacent to established mining towns. Serious social impacts of these practices, including violence and crime, have generally escaped industry, government and academic scrutiny. This paper highlights some of these impacts on affected regional communities and workers and argues that post-industrial mining regimes serve to mask and privatize these harms and risks, shifting them on to workers, families and communities.

A recommendation method for online dating networks based on social relations and demographic information

A new relationship type of social networks - online dating - are gaining popularity. With a large member base, users of a dating network are overloaded with choices about their ideal partners. Recommendation methods can be utilized to overcome this problem. However, traditional recommendation methods do not work effectively for online dating networks where the dataset is sparse and large, and a two-way matching is required. This paper applies social networking concepts to solve the problem of developing a recommendation method for online dating networks. We propose a method by using clustering, SimRank and adapted SimRank algorithms to recommend matching candidates. Empirical results show that the proposed method can achieve nearly double the performance of the traditional collaborative filtering and common neighbor methods of recommendation.

A fragment of the LG3 peptide of endorepellin is present in the urine of physically active mining workers : a potential marker of physical activity

Biomarker analysis has been implemented in sports research in an attempt to monitor the effects of exertion and fatigue in athletes. This study proposed that while such biomarkers may be useful for monitoring injury risk in workers, proteomic approaches might also be utilised to identify novel exertion or injury markers. We found that urinary urea and cortisol levels were significantly elevated in mining workers following a 12 hour overnight shift. These levels failed to return to baseline over 24h in the more active maintenance crew compared to truck drivers (operators) suggesting a lack of recovery between shifts. Use of a SELDI-TOF MS approach to detect novel exertion or injury markers revealed a spectral feature which was associated with workers in both work categories who were engaged in higher levels of physical activity. This feature was identified as the LG3 peptide, a C-terminal fragment of the anti-angiogenic / anti-tumourigenic protein endorepellin. This finding suggests that urinary LG3 peptide may be a biomarker of physical activity. It is also possible that the activity mediated release of LG3 / endorepellin into the circulation may represent a biological mechanism for the known inverse association between physical activity and cancer risk / survival.

Corporate, risk, mining camps and knowledge/power

Australia is currently in the midst of a major resources boom. However the benefits from the boom are unevenly distributed, with state governments collecting billions in royalties, and mining companies billions in profits. The costs are borne mostly at a local level by regional communities on the frontier of the mining boom, surrounded by thousands of men housed in work camps. The escalating reliance on non–resident workers housed in camps carries significant risks for individual workers, host communities and the provision of human services and infrastructure. These include rising rates of fatigue–related death and injuries, rising levels of alcohol–fuelled violence, illegally erected and unregulated work camps, soaring housing costs and other costs of living, and stretched basic infrastructure undermining the sustainability of these towns. But these costs have generally escaped industry, government and academic scrutiny. This chapter directs a critical gaze at the hopelessly compromised industry–funded research vital to legitimating the resource sector’s self–serving knowledge claims that it is committed to social sustainability and corporate responsibility. The chapter divides into two parts. The first argues that post–industrial mining regimes mask and privatise these harms and risks, shifting them on to workers, families and communities. The second part links the privatisation of these risks with the political economy of privatised knowledge embedded in the approvals process for major resource sector projects.

Established-outsider relations and fear of crime in mining towns

Using Elias and Scotson's (1994) account of established-outsider relations, this article examines how the organisational capacity of specific social groups is significant in determining the quality of crime-talk in isolated and rural settings. In particular, social 'oldness' and notions of what constitutes 'community' are significant in determining what activities and individuals are salient within crime-talk. Individual and gorup interviews, conducted in a West Australian mining town, revealed how crime-talk is an artefact of specific social figurations and the relative ability of groups to act as cohesive and integrated networks. We argue that anxieties regarding crime are a product of specific social figurations and the shifting power ratios of groups within such figurations.