04389nam 22006255 450 991030058480332120251116195856.03-319-78196-010.1007/978-3-319-78196-9(CKB)4100000004243845(DE-He213)978-3-319-78196-9(MiAaPQ)EBC5390240(EXLCZ)99410000000424384520180510d2018 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierSocial Network Based Big Data Analysis and Applications /edited by Mehmet Kaya, Jalal Kawash, Suheil Khoury, Min-Yuh Day1st ed. 2018.Cham :Springer International Publishing :Imprint: Springer,2018.1 online resource (X, 249 p. 89 illus., 77 illus. in color.)Lecture Notes in Social Networks,2190-54283-319-78195-2 Chapter1. Twitter as a Source for Time and Domain Dependent Sentiment Lexicons -- Chapter2. Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook -- Chapter3. Extraction and Analysis of Dynamic Conversational Networks from TV Series -- Chapter4. Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia -- Chapter5. Timelines of Prostate Cancer Biomarkers -- Chapter6. Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks -- Chapter7. Influence and Extension of the Spiral of Silence in Social Networks: A Data-driven Approach -- Chapter8. Prepaid or Postpaid? That is the question.\\ Novel Methods of Subscription Type Prediction in Mobile Phone Services -- Chapter9. Dynamic Pattern Detection for Big Data Stream Analytics -- Chapter10. Community-based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation -- Chapter11. Combining Feature Extraction and Clustering for Better Face Recognition.This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.Lecture Notes in Social Networks,2190-5428Social sciences—Data processingSocial sciences—Computer programsBig dataData miningPhysicsComputational Social Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/X34000Big Datahttps://scigraph.springernature.com/ontologies/product-market-codes/I29120Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Applications of Graph Theory and Complex Networkshttps://scigraph.springernature.com/ontologies/product-market-codes/P33010Social sciences—Data processing.Social sciences—Computer programs.Big data.Data mining.Physics.Computational Social Sciences.Big Data.Data Mining and Knowledge Discovery.Applications of Graph Theory and Complex Networks.302.30285Kaya Mehmetedthttp://id.loc.gov/vocabulary/relators/edtKawash Jalaledthttp://id.loc.gov/vocabulary/relators/edtKhoury Suheiledthttp://id.loc.gov/vocabulary/relators/edtDay Min-Yuhedthttp://id.loc.gov/vocabulary/relators/edtBOOK9910300584803321Social Network Based Big Data Analysis and Applications1927998UNINA