Alle Publikationen
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2018
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(2018) : Into the wild: Big data analytics in moral psychology. In: Gray, Kurt James; Graham, Jesse (Hg.): Atlas of moral psychology: What do we evaluate when we evaluate moral character? - Helzer, Erik G.; Critcher, Clayton R.: New York, NY: The Guilford Press, S. 525-536, zuletzt geprüft am 25.04.2018
Abstract: How can we investigate moral values in the real world? We propose that naturally generated linguistic data, such as social media content, can be used to study morality outside of the laboratory. Moral values are culturally variable entities that emerge from dynamic, hierarchical interactions between individual- and group level phenomena. Human-generated unstructured data from sources such as social media offer an unprecedented opportunity to observe these phenomena in a natural habitat, which is an essential vantage point for understanding moral values and their role in moral judgment and behavior. We believe it is vital that researchers supplement traditional methodologies with alternative approaches that have greater ecological and external validity and that are better able to capture the full social–functional range of morality. In this chapter, we argue that a range of computationally intensive methods, drawn predominantly from computer science and computational linguistics , can help researchers do just this. By mining psychologically relevant information from large-scale, human-generated, online data such as blog posts, news articles, tweets, Facebook status updates, and social network structures—collectively referred to as 'big data'—researchers can use these methods to investigate morally relevant phenomena in the real world. These methods enable researchers to investigate large-scale, diachronic moral phenomena such as the diffusion of moral values through populations and the moralization of specific topics. They also offer researchers new opportunities to investigate the relationship between moral values and moral behavior, which is both notoriously difficult to study in the laboratory and deeply important for understanding how morality functions. (PsycINFO Database Record (c) 2018 APA, all rights reserved) zitiert von: 2
Keywords: Data Mining, Medien, Interaktionsforschung, Moral, Judgment, Morality, social media, VALUES 2014
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Jamshidi, Mo (2014): Advance Trends in Soft Computing. Proceedings of WCSC 2013, December 16-18, San Antonio, Texas, USA. Wcsc; World Conference on Soft Computing. Cham: Springer (Studies in Fuzziness and Soft Computing)
DOI: https://doi.org/10.1007/978-3-319-02675-6 Abstract: This book is the proceedings of the 3rd World Conference on Soft Computing (WCSC), which was held in San Antonio, TX, USA, on December 16-18, 2013. It presents start-of-the-art theory and applications of soft computing together with an in-depth discussion of current and future challenges in the field, providing readers with a 360 degree view on soft computing. Topics range from fuzzy sets, to fuzzy logic, fuzzy mathematics, neuro-fuzzy systems, fuzzy control, decision making in fuzzy environments, image processing and many more. The book is dedicated to Lotfi A. Zadeh, a renowned specialist in signal analysis and control systems research who proposed the idea of fuzzy sets, in which an element may have a partial membership, in the early 1960s, followed by the idea of fuzzy logic, in which a statement can be true only to a certain degree, with degrees described by numbers in the interval [0,1]. The performance of fuzzy systems can often be improved with the help of optimization techniques, e.g. evolutionary computation, and by endowing the corresponding system with the ability to learn, e.g. by combining fuzzy systems with neural networks. The resulting “consortium” of fuzzy, evolutionary, and neural techniques is known as soft computing and is the main focus of this book
2012
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(2012): The Interaction Between Culture, Health and Psychological Well-Being. Data Mining from the Italian Culture and Well-Being Project. In: Journal of Happiness Studies 13 (1), S. 129-148. DOI: 10.1007/s10902-011-9254-x
DOI: https://doi.org/10.1007/s10902-011-9254-x Abstract: The purpose of this study is to understand the impact of health status and cultural participation upon psychological well-being, with special attention to the interaction between patterns of cultural access and other factors known to affect psychological well-being. Data for this report were collected from a sample of 1,500 Italian citizens. A multi-step random sampling method was adopted to draw a large representative sample from the Italian population. Subjects underwent a standard questionnaire for psychological well-being [the Italian short form of the Psychological General Well Being Index (PGWBI)], and a questionnaire related to the frequency of participation to 15 different kinds of cultural activities during the previous year. The results show that, among the various potential factors considered, cultural access unexpectedly rankes as the second most important determinant of psychological well-being, immediately after the absence or presence of diseases, and outpe rforming factors such as job, age, income, civil status, education, place of living and other important factors. According to a semantic map generated by a powerful data mining algorithm, it turns out that different factors (among which cultural access and health status in particular) may be viewed as concurrent elements of a complex multi-causal scheme that seems to play a primary role in determining psychological distress or well-being. In particular, distress seems to be tightly connected with: living in the Southern part of Italy, average income level, living in semi-urban and urban areas, age group 46–60, presence of more than two concomitant diseases and a low level of cultural access. Well being, on the other hand, is tightly connected with: male gender, high cultural access, and absence of diseases. Some of these associations are confirmed by Principal Component Analysis. (PsycINFO Database Record (c) 2016 APA, all rights reserved) zitiert vin 68
2008
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(2008) : IslEnquirer: Social user model acquisition through network analysis and interactive learning: 2008 IEEE Spoken Language Technology Workshop: Goa, India: IEEE, S. 117-120
DOI: https://doi.org/10.1109/SLT.2008.4777854 Abstract: We present an approach to introduce social awareness in interactive systems. The IslEnquirer is a system which automatically builds social user models. It initializes the models by social network analysis of available offline data. These models are then verified and extended by interactive learning which is carried out by a robot initiated spoken dialog with the user.
Keywords: Automatic speech recognition, Automation, Cognitive robotics, Context modeling, Data Mining, Humanoid Robots, Humans, ieee xplore, Information retrieval, interactive learning, interactive system, interactive systems, IslEnquirer, Künstliche Intelligenz, learning (artificial intelligence), Robot, Robotics, social awareness, social network analysis, Social network services, social networking (online), social networks, social user model acquisition, spoken dialog, spoken dialog system, user modeling, user modelling
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