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Behavior Computing
'Behavior' is an increasingly important concept in the scientific, societal, economic, cultural, political, military, living and virtual worlds. Behavior computing, or behavior informatics, consists of methodologies, techniques and practical tools for examining and interpreting behaviours in these various worlds. Behavior computing contributes to the in-depth understanding, discovery, applications and management of behavior intelligence. With contributions from leading researchers in this emerging field Behavior Computing: Modeling, Analysis, Mining and Decision includes chapters on: representation and modeling behaviors; behavior ontology; behaviour analysis; behaviour pattern mining; clust...
Modeling and Data Mining in Blogosphere
This book offers a comprehensive overview of the various concepts and research issues about blogs or weblogs. It introduces techniques and approaches, tools and applications, and evaluation methodologies with examples and case studies. Blogs allow people to express their thoughts, voice their opinions, and share their experiences and ideas. Blogs also facilitate interactions among individuals creating a network with unique characteristics. Through the interactions individuals experience a sense of community. We elaborate on approaches that extract communities and cluster blogs based on information of the bloggers. Open standards and low barrier to publication in Blogosphere have transformed ...
Twitter: A Digital Socioscope
A resource for social scientists on how Twitter data can be used to study individual behavior and social interaction.
Social, Cultural, and Behavioral Modeling
This book constitutes the proceedings of the 12th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2019, held in Washington, DC, USA, in July 2019. The total of 28 papers presented in this volume was carefully reviewed and selected from 72 submissions. The papers in this volume show, people, theories, methods and data from a wide number of disciplines including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science. Numerous types of computational methods are used include, but not limited to, machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics.
Machine Learning and Knowledge Discovery in Databases
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.
Twitter Data Analytics
This brief provides methods for harnessing Twitter data to discover solutions to complex inquiries. The brief introduces the process of collecting data through Twitter’s APIs and offers strategies for curating large datasets. The text gives examples of Twitter data with real-world examples, the present challenges and complexities of building visual analytic tools, and the best strategies to address these issues. Examples demonstrate how powerful measures can be computed using various Twitter data sources. Due to its openness in sharing data, Twitter is a prime example of social media in which researchers can verify their hypotheses, and practitioners can mine interesting patterns and build their own applications. This brief is designed to provide researchers, practitioners, project managers, as well as graduate students with an entry point to jump start their Twitter endeavors. It also serves as a convenient reference for readers seasoned in Twitter data analysis.
Social Computing, Behavioral-Cultural Modeling, and Prediction
This book constitutes the refereed proceedings of the 8th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2015, held in Washington, DC, USA, in March/April 2015. The 24 full papers presented together with 36 poster papers were carefully reviewed and selected from 118 submissions. The goal of the conference was to advance our understanding of human behavior through the development and application of mathematical, computational, statistical, simulation, predictive and other models that provide fundamental insights into factors contributing to human socio-cultural dynamics. The topical areas addressed by the papers are social and behavioral sciences, health sciences, engineering, computer and information science.
Advances in Social Computing
Social computing is concerned with the study of social behavior and social context based on computational systems. Behavioral modeling provides a representation of the social behavior, and allows for experimenting, scenario planning, and deep und- standing of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies by humans in everyday life provides an unprecedented en- ronment of various social activities that, due to the platforms under which they take place, generate large amounts of stored data as a by-product, often in systematically organized form. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, a...
Mining Human Mobility in Location-Based Social Networks
In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook Places, which have attracted an increasing number of users and greatly enriched their urban experience. Typical location-based social networking sites allow a user to "check in" at a real-world POI (point of interest, e.g., a hotel, restaurant, theater, etc.), leave tips toward the POI, and share the check-in with their online friends. The check-in action bridges the gap between real world and online social networks, resulting in a new type of social networks, namely location-based social networks (LBSNs). Compared to traditional GPS data, location-based social network...
Trust in Social Media
Social media greatly enables people to participate in online activities and shatters the barrier for online users to create and share information at any place at any time. However, the explosion of user-generated content poses novel challenges for online users to find relevant information, or, in other words, exacerbates the information overload problem. On the other hand, the quality of user-generated content can vary dramatically from excellence to abuse or spam, resulting in a problem of information credibility. The study and understanding of trust can lead to an effective approach to addressing both information overload and credibility problems. Trust refers to a relationship between a t...
