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020 _a9783031078699
024 7 _a10.1007/978-3-031-07869-9
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
245 1 0 _aDisease Control Through Social Network Surveillance
_cedited by Thirimachos Bourlai, Panagiotis Karampelas, Reda Alhajj
250 _a1st edition 2022
264 1 _aCham
_bSpringer International Publishing
_c2022
300 _a1 recurso en línea (XVI, 225 páginas)
_b1 illus
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aLecture Notes in Social Networks
_x2190-5436
505 0 _aChapter 1. Analysis of public perceptions towards the COVID-19 vaccination drive: A case study of Tweets with Machine Learning classifiers (Kaushal Kumar) -- Chapter 2. Spreader-centric Fake News Mitigation framework based on Epidemiology (Bhavtosh Rath) -- Chapter 3. Understanding How Readers Determine the Legitimacy of Online Medical News Articles in the Era of Fake News (Srihaasa Pidikiti) -- Chapter 4. Trends, Politics, Sentiments, and Misinformation: Understanding People's Reactions to COVID-19 During its Early Stages (Omar Abdel) -- Chapter 5. Citation Graph Analysis and Alignment between Citation Adjacency and Themes or Topics of Publications in the Area of Disease Control through Social Network Surveillance (Moses Boudourides) -- Chapter 6. Privacy in Online Social Networks: A Systematic Mapping Study and a Classification Framework (Sarah Bouraga) -- Chapter 7. Beyond Influence Maximization: Volume Maximization in Social Networks (Abhinav Choudhury) -- Chapter 8. Concerns of Indian Population on Covid-19 Vaccine Shortage amidst second wave infection rate spikes: A Social Media Opinion Analysis (Remya Lathabhavan) -- Chapter 9. Effects of Face Masks on the performance of Modern Face Detectors (Victor Philippe) -- Chapter 10. Multispectral Face Mask Compliance Classification During a Pandemic (Jacob Rose) -- Chapter 11. On the Effectiveness of Periocular-Based Human Authentication when Wearing Face Masks to Slow the Spread of COVID-19 (Ananya Zabin).
520 _aThis book examines modern paradigms of disease control based on social network surveillance applications, including electronic sentinel surveillance and wireless application-based surveillance science. It also highlights topics that integrate statistical and epidemiological sciences with surveillance practice and, in order to reflect the evolution of social networking practices, discusses topics concerning the challenges for surveillance theory and practice. In turn, the book goes a step further by providing insights on how we need to analyse epidemiological trends by following best practices on distinguishing useful information from noise, namely fake news, false reporting of disease incidents and events, etc. At the same time, we need to be able to protect health-focused applications and communication tools via cybersecurity technologies and to ensure that anonymity of reporting and privacy are preserved. In closing, the book discusses the role and impact of social media on disease surveillance, as well as the current role of communities in infectious disease surveillance and control.
700 1 _aBourlai, Thirimachos
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKarampelas, Panagiotis
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aAlhajj, Reda
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
776 0 8 _iPrinted edition:
_z9783031078682
776 0 8 _iPrinted edition:
_z9783031078705
776 0 8 _iPrinted edition:
_z9783031078712
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-07869-9
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
988 _aSpringer_Computer_2022
999 _c393914
_d393914