Data-driven Computational Social Science: A Survey

Social science concerns issues on individuals, relationships, and the whole society. The complexity of research topics in social science makes it the amalgamation of multiple disciplines, such as economics, political science, and sociology, etc. For centuries, scientists have conducted many studies to understand the mechanisms of the society. However, due to the limitations of traditional research methods, there exist many critical social issues to be explored. To solve those issues, computational social science emerges due to the rapid advancements of computation technologies and the profound studies on social science. With the aids of the advanced research techniques, various kinds of data from diverse areas can be acquired nowadays, and they can help us look into social problems with a new eye. As a result, utilizing various data to reveal issues derived from computational social science area has attracted more and more attentions. In this paper, to the best of our knowledge, we present a survey on data-driven computational social science for the first time which primarily focuses on reviewing application domains involving human dynamics. The state-of-the-art research on human dynamics is reviewed from three aspects: individuals, relationships, and collectives. Specifically, the research methodologies used to address research challenges in aforementioned application domains are summarized. In addition, some important open challenges with respect to both emerging research topics and research methods are discussed.Comment: 28 pages, 8 figure

Sensing, Understanding, and Shaping Social Behavior

The ability to understand social systems through the aid of computational tools is central to the emerging field of computational social systems. Such understanding can answer epistemological questions on human behavior in a data-driven manner, and provide prescriptive guidelines for persuading humans to undertake certain actions in real-world social scenarios. The growing number of works in this subfield has the potential to impact multiple walks of human life including health, wellness, productivity, mobility, transportation, education, shopping, and sustenance. The contribution of this paper is twofold. First, we provide a functional survey of recent advances in sensing, understanding, and shaping human behavior, focusing on real-world behavior of users as measured using passive sensors. Second, we present a case study on how trust, which is an important building block of computational social systems, can be quantified, sensed, and applied to shape human behavior. Our findings suggest that:1) trust can be operationalized and predicted via computational methods (passive sensing and network analysis) and 2) trust has a significant impact on social persuasion; in fact, it was found to be significantly more effective than the closeness of ties in determining the amount of behavior change.U.S. Army Research Laboratory (Cooperative Agreement W911NF-09-2-0053

Social Data Mining for Crime Intelligence

With the advancement of the Internet and related technologies, many traditional crimes have made the leap to digital environments. The successes of data mining in a wide variety of disciplines have given birth to crime analysis. Traditional crime analysis is mainly focused on understanding crime patterns, however, it is unsuitable for identifying and monitoring emerging crimes. The true nature of crime remains buried in unstructured content that represents the hidden story behind the data. User feedback leaves valuable traces that can be utilised to measure the quality of various aspects of products or services and can also be used to detect, infer, or predict crimes. Like any application of data mining, the data must be of a high quality standard in order to avoid erroneous conclusions. This thesis presents a methodology and practical experiments towards discovering whether (i) user feedback can be harnessed and processed for crime intelligence, (ii) criminal associations, structures, and roles can be inferred among entities involved in a crime, and (iii) methods and standards can be developed for measuring, predicting, and comparing the quality level of social data instances and samples. It contributes to the theory, design and development of a novel framework for crime intelligence and algorithm for the estimation of social data quality by innovatively adapting the methods of monitoring water contaminants. Several experiments were conducted and the results obtained revealed the significance of this study in mining social data for crime intelligence and in developing social data quality filters and decision support systems

Infering trust in web-based social networks: an analysis from TidalTrust and T-SWEETS algorithms

This work presents an analysis between two approaches for inferring trust in social networks: TidalTrust and T-SWEETS. The first part of this research is composed by an experiment with the Epinions, Slashdot and Wikipedia datasets in order to define the most suitable type of trust value (integer or fractioned, positive or negative, and so on). Furthermore, the second part of this research reports a comparative analysis between both algorithms. The results indicate that T-SWEETS outperforms TidalTrust in terms of accuracy and maintains the transitivity principle, which is the basic principle of trust.f trust

Hidden Depths

In Hidden Depths, Professor Penny Spikins explores how our emotional connections have shaped human ancestry. Focusing on three key transitions in human origins, Professor Spikins explains how the emotional capacities of our early ancestors evolved in response to ecological changes, much like similar changes in other social mammals. For each transition, dedicated chapters examine evolutionary pressures, responses in changes in human emotional capacities and the archaeological evidence for human social behaviours. Starting from our earliest origins, in Part One, Professor Spikins explores how after two million years ago, movement of human ancestors into a new ecological niche drove new types of collaboration, including care for vulnerable members of the group. Emotional adaptations lead to cognitive changes, as new connections based on compassion, generosity, trust and inclusion also changed our relationship to material things. Part Two explores a later key transition in human emotional capacities occurring after 300,000 years ago. At this time changes in social tolerance allowed ancestors of our own species to further reach out beyond their local group and care about distant allies, making human communities resilient to environmental changes. An increasingly close relationship to animals, and even to cherished possessions, appeared at this time, and can be explained through new human vulnerabilities and ways of seeking comfort and belonging. Lastly, Part Three focuses on the contrasts in emotional dispositions arising between ourselves and our close cousins, the Neanderthals. Neanderthals are revealed as equally caring yet emotionally different humans, who might, if things had been different, have been in our place today. This new narrative breaks away from traditional views of human evolution as exceptional or as a linear progression towards a more perfect form. Instead, our evolutionary history is situated within similar processes occurring in other mammals, and explained as one in which emotions, rather than ‘intellect’, were key to our evolutionary journey. Moreover, changes in emotional capacities and dispositions are seen as part of differing pathways each bringing strengths, weaknesses and compromises. These hidden depths provide an explanation for many of the emotional sensitivities and vulnerabilities which continue to influence our world today

Therapeutic Alliance as Active Inference: The Role of Therapeutic Touch and Biobehavioural Synchrony in Musculoskeletal Care

Touch is recognised as crucial for survival, fostering cooperative communication, accelerating recovery, reducing hospital stays, and promoting overall wellness and the therapeutic alliance. In this hypothesis and theory paper, we present an entwined model that combines touch for alignment and active inference to explain how the brain develops “priors” necessary for the health care provider to engage with the patient effectively. We appeal to active inference to explain the empirically integrative neurophysiological and behavioural mechanisms that underwrite synchronous relationships through touch. Specifically, we offer a formal framework for understanding – and explaining – the role of therapeutic touch and hands-on care in developing a therapeutic alliance and synchrony between health care providers and their patients in musculoskeletal care. We first review the crucial importance of therapeutic touch and its clinical role in facilitating the formation of a solid therapeutic alliance and in regulating allostasis. We then consider how touch is used clinically – to promote cooperative communication, demonstrate empathy, overcome uncertainty, and infer the mental states of others – through the lens of active inference. We conclude that touch plays a crucial role in achieving successful clinical outcomes and adapting previous priors to create intertwined beliefs. The ensuing framework may help healthcare providers in the field of musculoskeletal care to use hands-on care to strengthen the therapeutic alliance, minimise prediction errors (a.k.a., free energy), and thereby promote recovery from physical and psychological impairments

Hidden Depths

In Hidden Depths, Professor Penny Spikins explores how our emotional connections have shaped human ancestry. Focusing on three key transitions in human origins, Professor Spikins explains how the emotional capacities of our early ancestors evolved in response to ecological changes, much like similar changes in other social mammals. For each transition, dedicated chapters examine evolutionary pressures, responses in changes in human emotional capacities and the archaeological evidence for human social behaviours. Starting from our earliest origins, in Part One, Professor Spikins explores how after two million years ago, movement of human ancestors into a new ecological niche drove new types of collaboration, including care for vulnerable members of the group. Emotional adaptations lead to cognitive changes, as new connections based on compassion, generosity, trust and inclusion also changed our relationship to material things. Part Two explores a later key transition in human emotional capacities occurring after 300,000 years ago. At this time changes in social tolerance allowed ancestors of our own species to further reach out beyond their local group and care about distant allies, making human communities resilient to environmental changes. An increasingly close relationship to animals, and even to cherished possessions, appeared at this time, and can be explained through new human vulnerabilities and ways of seeking comfort and belonging. Lastly, Part Three focuses on the contrasts in emotional dispositions arising between ourselves and our close cousins, the Neanderthals. Neanderthals are revealed as equally caring yet emotionally different humans, who might, if things had been different, have been in our place today. This new narrative breaks away from traditional views of human evolution as exceptional or as a linear progression towards a more perfect form. Instead, our evolutionary history is situated within similar processes occurring in other mammals, and explained as one in which emotions, rather than ‘intellect’, were key to our evolutionary journey. Moreover, changes in emotional capacities and dispositions are seen as part of differing pathways each bringing strengths, weaknesses and compromises. These hidden depths provide an explanation for many of the emotional sensitivities and vulnerabilities which continue to influence our world today