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Big Data Analytics | Tutorial #28 | Mining Social Network Graphs
 
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There is much information to be gained by analyzing the large-scale data that is derived from social networks. The best-known example of a social network is the “friends” relation found on sites like Facebook. However, as we shall see there are many other sources of data that connect people or other entities. #RanjiRaj #BigData #SocialNetworkGraph Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj ويستند هذا الفيديو على مفاهيم مثل الحافة بينغريس وجريفان نيومان خوارزمية في الرسوم البيانية الاجتماعية Este video se basa en conceptos como Edge entreess y el algoritmo de Grivan Newman en los gráficos sociales Это видео основано на таких понятиях, как Edge interess и Grivan Newman Algorithm в социальных графах Cette vidéo est basée sur des concepts tels que interess et Girvan bord Newman algorithme dans les graphiques sociaux Dieses Video basiert auf Konzepten wie Edge zwischeness und Grivan-Newman Algorithmus in den sozialen Graphen Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter 👉https://twitter.com/iamRanjiRaj Like TheStudyBeast on Facebook 👉https://www.facebook.com/thestudybeast/ For more videos LIKE SHARE SUBSCRIBE
Views: 3513 Ranji Raj
Big data and social mining
 
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Cosa sono i big data? in che modo sono utili allo studio sulla società? Dino Pedreschi, Fosca Giannotti e il gruppo di ricercatori del KDD Lab (Knowledge Discovery and Data Mining Laboratory) laboratorio congiunto del Dipartimento di Informatica dell'Università di Pisa e dell'istituto di Scienza e Tecnologie dell'Informazione ISTI-CNR) ci spiegano cosa sono le "briciole digitali" lasciate dagli utenti e come aiutano ad interpretare la complessità della vita sociale.
Views: 3799 VideoUNIPI
How Big Data Can Influence Decisions That Actually Matter | Prukalpa Sankar | TEDxGateway
 
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Its crazy how big data is used to solve some kinds of problems and not others. Prukalpa Sankar reimagines a world where we can catch criminals at the scene of the crime – not years later, reroute cars in real time to prevent traffic congestion that we all hate so much, predict if a child is going to drop out of school before they even knows it and eradicate a disease as it breaks, not 1000s of deaths later. Prukalpa is the co-founder of SocialCops, a data intelligence company. Their platform brings the entire decision-making process to one place — from collecting primary data and accessing secondary data to merging internal data and visualizing data via easy-to-use dashboards. They work with over 150 organizations in 7+ countries, including the Gates Foundation, Tata Trusts, Government of India, Unilever, and Frost & Sullivan. SocialCops was on the 2016 Forbes Asia 30 Under 30 and Fortune India 40 Under 40 lists. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 182406 TEDx Talks
Basics of Social Network Analysis
 
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Basics of Social Network Analysis In this video Dr Nigel Williams explores the basics of Social Network Analysis (SNA): Why and how SNA can be used in Events Management Research. The freeware sound tune 'MFF - Intro - 160bpm' by Kenny Phoenix http://www.last.fm/music/Kenny+Phoenix was downloaded from Flash Kit http://www.flashkit.com/loops/Techno-Dance/Techno/MFF_-_In-Kenny_Ph-10412/index.php The video's content includes: Why Social Network Analysis (SNA)? Enables us to segment data based on user behavior. Understand natural groups that have formed: a. topics b. personal characteristics Understand who are the important people in these groups. Analysing Social Networks: Data Collection Methods: a. Surveys b. Interviews c. Observations Analysis: a. Computational analysis of matrices Relationships: A. is connected to B. SNA Introduction: [from] A. Directed Graph [to] B. e.g. Twitter replies and mentions A. Undirected Graph B. e.g. family relationships What is Social Network Analysis? Research technique that analyses the Social structure that emerges from the combination of relationships among members of a given population (Hampton & Wellman (1999); Paolillo (2001); Wellman (2001)). Social Network Analysis Basics: Node and Edge Node: “actor” or people on which relationships act Edge: relationship connecting nodes; can be directional Social Network Analysis Basics: Cohesive Sub-group Cohesive Sub-group: a. well-connected group, clique, or cluster, e.g. A, B, D, and E Social Network Analysis Basics: Key Metrics Centrality (group or individual measure): a. Number of direct connections that individuals have with others in the group (usually look at incoming connections only). b. Measure at the individual node or group level. Cohesion (group measure): a. Ease with which a network can connect. b. Aggregate measure of shortest path between each node pair at network level reflects average distance. Density (group measure): a. Robustness of the network. b. Number of connections that exist in the group out of 100% possible. Betweenness (individual measure): a. Shortest paths between each node pair that a node is on. b. Measure at the individual node level. Social Network Analysis Basics: Node Roles: Node Roles: Peripheral – below average centrality, e.g. C. Central connector – above average centrality, e.g. D. Broker – above average betweenness, e.g. E. References and Reading Hampton, K. N., and Wellman, B. (1999). Netville Online and Offline Observing and Surveying a Wired Suburb. American Behavioral Scientist, 43(3), pp. 475-492. Smith, M. A. (2014, May). Identifying and shifting social media network patterns with NodeXL. In Collaboration Technologies and Systems (CTS), 2014 International Conference on IEEE, pp. 3-8. Smith, M., Rainie, L., Shneiderman, B., and Himelboim, I. (2014). Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. Pew Research Internet Project.
Views: 40215 Alexandra Ott
Social media data mining for counter-terrorism | Wassim Zoghlami | TEDxMünster
 
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Using public social media data from twitter and Facebook, actions and announcements of terrorists – in this case ISIS – can be monitored and even be predicted. With his project #DataShield Wassim shares his idea of having a tool to identify oncoming threats and attacks in order to protect people and to induce preventive actions. Wassim Zoghlami is a Tunisian Computer Engineering Senior focussing on Business Intelligence and ERP with a passion for data science, software life cycle and UX. Wassim is also an award winning serial entrepreneur working on startups in healthcare and prevention solutions in both Tunisia and The United States. During the past years Wassim has been working on different projects and campaigns about using data driven technology to help people working to uphold human rights and to promote civic engagement and culture across Tunisia and the MENA region. He is also the co-founder of the Tunisian Center for Civic Engagement, a strong advocate for open access to research, open data and open educational resources and one of the Global Shapers in Tunis. At TEDxMünster Wassim will talk about public social media data mining for counter-terrorism and his project idea DataShield. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 2207 TEDx Talks
How Facebook Data Mining, And Your Info, Is Influencing The 2016 Election | TODAY
 
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With the 2016 presidential election only 27 days away, we’re taking a look at how the campaigns are taking to social media in the hopes of trying to win the all-important millennial vote and how data mining on Facebook and other social platforms is influencing your view of the election. NBC News’ Jo Ling Kent reports for TODAY. Red, White and You is brought to you by Amazon. » Subscribe to TODAY: http://on.today.com/SubscribeToTODAY » Watch the latest from TODAY: http://bit.ly/LatestTODAY About: TODAY brings you the latest headlines and expert tips on money, health and parenting. We wake up every morning to give you and your family all you need to start your day. If it matters to you, it matters to us. We are in the people business. Subscribe to our channel for exclusive TODAY archival footage & our original web series. Connect with TODAY Online! Visit TODAY's Website: http://on.today.com/ReadTODAY Find TODAY on Facebook: http://on.today.com/LikeTODAY Follow TODAY on Twitter: http://on.today.com/FollowTODAY Follow TODAY on Google+: http://on.today.com/PlusTODAY Follow TODAY on Instagram: http://on.today.com/InstaTODAY Follow TODAY on Pinterest: http://on.today.com/PinTODAY How Facebook Data Mining, And Your Info, Is Influencing The 2016 Election | TODAY
Views: 6070 TODAY
Analyzing and modeling complex and big data | Professor Maria Fasli | TEDxUniversityofEssex
 
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This talk was given at a local TEDx event, produced independently of the TED Conferences. The amount of information that we are creating is increasing at an incredible speed. But how are we going to manage it? Professor Maria Fasli is based in the School of Computer Science and Electronic Engineering at the University of Essex. She obtained her BSc from the Department of Informatics of T.E.I. Thessaloniki (Greece). She received her PhD from the University of Essex in 2000 having worked under the supervision of Ray Turner in axiomatic systems for intelligent agents. She has previously worked in the area of data mining and machine learning. Her current research interests lie in agents and multi-agent systems and in particular formal theories for reasoning agents, group formation and social order as well as the applications of agent technology to e-commerce. About TEDx, x = independently organized event In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
Views: 141540 TEDx Talks
An introduction to Social Media Analytics
 
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Jigsaw Academy is an award winning premier online analytics training institute that aims to meet the growing demand for talent in the field of analytics by providing industry-relevant training to develop business-ready professionals.Jigsaw Academy has been acknowledged by blue chip companies for quality training Follow us on: https://www.facebook.com/jigsawacademy https://twitter.com/jigsawacademy http://jigsawacademy.com/
Views: 16758 Jigsaw Academy
Mining Online Data Across Social Networks
 
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Capturing Data, Modeling Patterns, Predicting Behavior. Capturing Data, Modeling Patterns, Predicting Behavior - Based on collecting more than 20 million blog posts and news media articles per day, Professor Jure Leskovec discusses how to mine such data to capture and model temporal patterns in the news over a daily time-scale --in particular, the succession of story lines that evolve and compete for attention. He discusses models to quantify the influence of individual media sites on the popularity of news stories and algorithms for inferring hidden networks of information flow. Learn more: http://scpd.stanford.edu/
Views: 20476 stanfordonline
Social Media Data Mining & Analysis with Raspberry Pi (Part 1: Setup)
 
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This video is the first in a series that walks through all necessary steps for social media data mining and analysis with Raspberry Pi. Part 1 describes all the necessary hardware for the project and how to set up that hardware in just five minutes. Recorded for the University of Maine at Augusta.
Views: 2549 James Cook
What future for Big Data mining?
 
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Policymakers are showing growing interest for real-time analysis of public opinion and Big Data. From finance to political campaigners, social media have become a primary source of information, especially when it comes to understanding public opinion trends. However, the potential of social media still needs to be fully exploited. With the explosion of structured and unstructured Big Data, the ability to harness information has become paramount for those who want to successfully use information originating from social media. On the regulatory side, the European Commission wants to promote the data-driven economy as part of its Digital Single Market strategy. The strategy includes better online access and digitalisation as a driver for growth.
Views: 966 SSIX Project
Mining Big Data to Understand the Link Between Facial Features and Personality
 
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This presentation features Michal Kosinski, Stanford University. It is one of four presentations from the Big Data: Vast Opportunities for Psychological Insight symposium, presented at the 16th Annual Society for Personality and Social Psychology Convention. The big data revolution is upon us. Enormous samples, even entire populations, are being studied through cheap and varied means, presenting a powerful new lens to understand human behavior. In this invited session, leading scholars in economics, computer science, and psychology provide a glimpse into what big data can reveal.
Data Mining with Big Data
 
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To get this project in ONLINE or through TRAINING Sessions, Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: [email protected], web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.
Views: 3771 jpinfotechprojects
Beyond Big Data
 
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The Oxford Internet Institute is excited to welcome Matthew J. Salganik from Princeton University Department of Sociology for his talk 'Beyond Big Data'. The event will be followed by a drinks reception. Abstract The digital age has transformed how we are able to study social behavior. Unfortunately, researchers have not yet taken full advantage of these opportunities because we are too focused on “big data,” such as digital traces of behavior. These big data can be wonderful for some research questions, but they have fundamental limitations for addressing many questions because they were never designed to be used for research. This talk will argue that rather than focusing on “found data”, researchers should use the capabilities of the digital age to create new forms of “designed data.” I’ll provide three templates that researchers can use to combine the strengths of found data and designed data, and I’ll illustrate these templates with recent empirical studies. This talk is based on my forthcoming book—Bit by Bit: Social Research in the Digital Age—which is currently in Open Review at http://www.bitbybitbook.com. About the speakers Matthew Salganik Affiliation: Princeton University Matthew Salganik is Professor of Sociology at Princeton University, and he is affiliated with several of Princeton’s interdisciplinary research centers: the Office for Population Research, the Center for Information Technology Policy, the Center for Health and Wellbeing, and the Center for Statistics and Machine Learning. His research interests include social networks and computational social science. He is the author of the forthcoming book Bit by Bit: Social Research in the Digital Age.
Data Mining and New Patterns Discovered Through Social Networking
 
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Interview conducted on 28 July 2009 by Jordan Brown for a documentary. Film recording and editing by Jordan Brown.
Views: 135 Katina Michael
Golden Opportunity: Mining Big Data and Social Media with GIS and Spatial Analytics
 
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Golden Opportunity: Mining Big Data and Social Media with GIS and Spatial Analytics
Ethical quandary in the age of big data | Justin Grace | TEDxUCL
 
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This talk was given at a local TEDx event, produced independently of the TED Conferences. Data is now everywhere. The ‘internet era’ has now passed and we are entering the era of data. Data use and misuse can lead to both powerful positive change or disaster. Here I discuss the questions we should ask about data and present three case studies where organisations have generated controversy from their data practices. I finish by touching on what we can do to take ownership of our data. Justin is a freelance data scientist who has worked in academia, technology, healthcare and most recently digital media with the Guardian. He is passionate about all things data and understanding how its use and misuse shapes the world we live in and how this affects our relationships with organisations and each other. About TEDx, x = independently organized event In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
Views: 6069 TEDx Talks
Enterprise Connectors - Social Media Data Mining
 
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This is a replay of the webinar covering using the CData Enterprise Connectors for FireDAC to connect to Twitter and Facebook to mine social media data. The examples are in Delphi, but they could also easily be adaptable for C++Builder too.
Social Networks for Fraud Analytics
 
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Data mining algorithms are focused on finding frequently occurring patterns in historical data. These techniques are useful in many domains, but for fraud detection it is exactly the opposite. Rather than being a pattern repeatedly popping up in a data set, fraud is an uncommon, well-considered, imperceptibly concealed, time-evolving and often carefully organized crime which appears in many types and forms. As traditional techniques often fail to identify fraudulent behavior, social network analysis offers new insights in the propagation of fraud through a network. Indeed, fraud is not something an individual would commit by himself, but is often organized by groups of people loosely connected to each other. The use of networked data in fraud detection becomes increasingly important to uncover fraudulent patterns and to detect in real-time when certain processes show some characteristics of irregular activities. Although analyses focus in the first place on fraud detection, the emphasis should shift towards fraud prevention, i.e. detecting fraud before it is even committed. As fraud is a time-evolving phenomenon, social network algorithms succeed to keep ahead of new types of fraud and to adapt to changing environment and surrounding effects.
Views: 9275 Bart Baesens
Social Media Data Mining With Raspberry Pi (Part 3: Operating Systems)
 
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This video is third in a series that walks through all the steps necessary to mine and analyze social media data using the inexpensive computer called a Raspberry Pi. Part 3 describes the two operating system environments of the Raspberry Pi: the Windows-like graphic user interface and the Linux text-based terminal environment.
Views: 1374 James Cook
15 Hot Trending PHD Research Topics in Data Mining 2018
 
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15 Hot Trending Data Mining Research Topics 2018 1. Medical Data Mining 2. Education Data Mining 3. Data Mining with Cloud Computing 4. Efficiency of Data Mining Algorithms 5. Signal Processing 6. Social Media Analytics 7. Data Mining in Medical Science 8. Government Domain 9. Financial Data Analysis 10. Financial Accounting Fraud Detection 11. Customer Analysis 12. Financial Growth Analysis using Data Mining 13. Data Mining and IOT 14. Data Mining for Counter-Terrorism Key Research Application Fields: • Crisp-DM • Oracle Data mining • Web Mining • Open NN • Data Warehousing • Text Mining WHY YOU NEED TO OUTSOURCE TO PhD Assistance: a) Unlimited revisions b) 24/7 Admin Support c) Plagiarism Generate d) Best Possible Turnaround time e) Access to High qualified technical coordinators and expertise f) Support: Skype, Live Chat, Phone, Email Contact us: India: +91 8754446690 UK: +44-1143520021 Email: [email protected] Visit Webpage: https://goo.gl/HwJgqQ Visit Website: http://www.phdassistance.com
Views: 5498 PhD Assistance
||DATA MINING|| Social Media Behind The Scenes! ||CodeFantasy|| #fightforprivacy
 
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|-CODEFANTASY-| Coding as Your Fantasy ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| Your Data is no more Private! Did you ever wonder how Whatsapp earns without publishing any ads on their platform? They tell that your data is Encrypted but seriously? it's Encrypted only for Third parties not for the Company! Watch the video to know how they are selling you and your data and share this as your Contribution for a Change #fightforprivacy We are the team that work and produce legendary tutorials, made and worked out by the processes of Scientific Learning. Please do subscribe and support us for amazing tutorials about to be published. The Name CODE_FANTASY is under copyright and cannot be used any where else!
Views: 465 Code_Fantasy
Socialytics - The 5 TOP trends in Social, Big Data and Analytics
 
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In this short presentation you'll learn just what are the biggest trends right now in Social, Big Data and Analytics. Want to learn more? Vote for an in-depth presentation on this topic at SXSW Interactive 2014. http://panelpicker.sxsw.com/vote/23035
Views: 807 Sandy Carter
A survey Big Data social media using data mining techniques | | Final Year Projects 2016 - 2017
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/clickmyproject Mail Us: [email protected]
Views: 158 Clickmyproject
The Logic of Data Mining in Social Research
 
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This video is a brief introduction for undergraduates to the logic (not the nitty-gritty details) of data mining in social science research. Four orienting tips for getting started and placing data mining in the broader context of social research are included.
Views: 401 James Cook
Golden Opportunity: Mining Big Data and Social Media with GIS and Spatial Analytics
 
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This is an edited version of the presentaion held on 09/12/13 by Dr. Ming-Hsiang (Ming) Tsou, Professor, Department of Geography, San Diego State University and CEO of PathGeo. The presentation was held at the University of Redlands, School of Business and hosted by the Center for Business GIS and Spatial Analysis (GISAB).
BI - Using Big Data & Social Mining in Value Chain Planning to reduce operational costs
 
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BI - Using Big Data & Social Mining in Value Chain Planning to reduce operational costs - Salil Amonkar, Bodhtree
Views: 217 SuperAI
Analysis for Social Networking Sites - Data Mining.
 
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in this video I will show you how to analyse the Social networking sites.
Views: 103 HashTech Coders
Data mining in social media
 
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I used screencast-o-matic to record my presentation.
Views: 430 Bryan Russowsky
Data mining of social | Anna Dubovik | TEDxYouth@Tomsk
 
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Do You know what is really interesting for everyone? Future. In 1968, Arthur C. Clarke in his novel "2001: A Space Odyssey" predicted boom of space traveling and the development of artificial intelligence. He described the future in many ways and it has become real. In 2001, the computer was able to beat a man at chess, and in the early 2000s the company started to create a space tourism industry. What is the forecast of today? TEDYouth 2015 is an opportunity for young people to think about the world in 2035, to create their own view of future reality. Tomsk is among more than 150 cities around the globe gathered to explore the event's theme, "Made in the Future" on the 14-15 November 2015. During these two days more than 900 speakers of various professions will talk about their version of the key changes that await humanity in the perspective of 15-20 years. Graduated Skolkovo Institute of Science and Technology, analyst in the Information-Analytical Center of Moscow City Health Departments, Big Data analyst This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 427 TEDx Talks
Social Media Data Mining with Raspberry Pi (Part 7: Saving Data as CSV)
 
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This video is seventh in a series for **absolute beginners** who would like to use an inexpensive, accessible computer called the Raspberry Pi in order to carry out social media data mining and analysis. In this installment, I walk through the process for storing social media data you've collected in the universally-accessible delimited format called CSV. We use the Python library CSV and consider ways to make a CSV format better organized and more useful. Coming up in installment number 8: working with Twitter and the csv.writer command to form data into appropriate shapes to characterize links, hashtags and relationships.
Views: 1045 James Cook
Quantitative Methods in Social Media Research: Big Data
 
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Ralph Schroeder (OII) discusses very large datasets during a seminar on quantitative methods in social media research held at the OII on 26 September 2012. What do we gain and lose with big data? How is big data changing the way we do research? Recorded: 26 September 2012.
A survey Big Data social media using data mining techniques | | Final Year Projects 2016 - 2017
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/clickmyproject Mail Us: [email protected]
Views: 10 Support EGC
Data on Purpose Panel: Data Mining for Social Impact
 
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Experts discuss how data mining can help organizations effectively measure impact and optimize their work.
Views: 586 stanfordsocialinnov
Data Mining Techniques to Prevent Credit Card Fraud
 
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Includes a brief introduction to credit card fraud, types of credit card fraud, how fraud is detected, applicable data mining techniques, as well as drawbacks.
Views: 13736 Ben Rodick
Mining Social Media Data for Understanding Students’ Learning Experiences
 
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Abstract—Students’ informal conversations on social media (e.g. Twitter, Facebook) shed light into their educational experiences—opinions, feelings, and concerns about the learning process. Data from such uninstrumented environments can provide valuable knowledge to inform student learning. Analyzing such data, however, can be challenging. The complexity of students’ experiences reflected from social media content requires human interpretation. However, the growing scale of data demands automatic data analysis techniques. In this paper, we developed a workflow to integrate both qualitative analysis and large-scale data mining techniques. We focused on engineering students’ Twitter posts to understand issues and problems in their educational experiences. We first conducted a qualitative analysis on samples taken from about 25,000 tweets related to engineering students’ college life. We found engineering students encounter problems such as heavy study load, lack of social engagement, and sleep deprivation. Based on these results, we implemented a multi-label classification algorithm to classify tweets reflecting students’ problems. We then used the algorithm to train a detector of student problems from about 35,000 tweets streamed at the geo-location of Purdue University. This work, for the first time, presents a methodology and results that show how informal social media data can provide insights into students’ experiences. Index Terms—Education, computers and education, social networking, web text analysis
SpiegelMining – Reverse Engineering von Spiegel-Online (33c3)
 
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Wer denkt, Vorratsdatenspeicherungen und „Big Data“ sind harmlos, der kriegt hier eine Demo an Spiegel-Online. Seit Mitte 2014 hat David fast 100.000 Artikel von Spiegel-Online systematisch gespeichert. Diese Datenmasse wird er in einem bunten Vortrag vorstellen und erforschen. David Kriesel
Views: 809077 media.ccc.de
How Big Data Is Used In Amazon Recommendation Systems | Big Data Application & Example | Simplilearn
 
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This Big Data Video will help you understand how Amazon is using Big Data is ued in their recommendation syatems. You will understand the importance of Big Data using case study. Recommendation systems have impacted or even redefined our lives in many ways. One example of this impact is how our online shopping experience is being redefined. As we browse through products, the Recommendation system offer recommendations of products we might be interested in. Regardless of the perspectives, business or consumer, Recommendation systems have been immensely beneficial. And big data is the driving force behind Recommendation systems. Subscribe to Simplilearn channel for more Big Data and Hadoop Tutorials - https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Check our Big Data Training Video Playlist: https://www.youtube.com/playlist?list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ Big Data and Analytics Articles - https://www.simplilearn.com/resources/big-data-and-analytics?utm_campaign=Amazon-BigData-S4RL6prqtGQ&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Big Data and Hadoop, check our Big Data Hadoop and Spark Developer Certification Training Course: http://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=Amazon-BigData-S4RL6prqtGQ&utm_medium=Tutorials&utm_source=youtube #bigdata #bigdatatutorialforbeginners #bigdataanalytics #bigdatahadooptutorialforbeginners #bigdatacertification #HadoopTutorial - - - - - - - - - About Simplilearn's Big Data and Hadoop Certification Training Course: The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. You will also learn the various interactive algorithm in Spark and use Spark SQL for creating, transforming, and querying data form. As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. The projects included are in the domains of Banking, Telecommunication, Social media, Insurance, and E-commerce. This Big Data course also prepares you for the Cloudera CCA175 certification. - - - - - - - - What are the course objectives of this Big Data and Hadoop Certification Training Course? This course will enable you to: 1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames - - - - - - - - - - - Who should take up this Big Data and Hadoop Certification Training Course? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals: 1. Software Developers and Architects 2. Analytics Professionals 3. Senior IT professionals 4. Testing and Mainframe professionals 5. Data Management Professionals 6. Business Intelligence Professionals 7. Project Managers 8. Aspiring Data Scientists - - - - - - - - For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 31827 Simplilearn
Data Privacy: Good or Bad? | Mark Farid | TEDxWarwick
 
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In October 2015, artist Mark Farid shared with the world login details to all his online accounts — both personal and private — in an attempt to live without a digital footprint for 6 months. Through this practice, he examines the formation of our projected-self, and how our constructed identity is shaped by societal expectations. http://www.data-shadow.com 1st - 30th September 2016, Mark broadcast all of his personal and professional emails, text and Facebook messages, phone and Skype calls, web browsing, and Social Media activity, in real-time, online. Any pictures or videos he captured appeared on his 'newsfeed', and his phones’ location was updated every 20 minutes. In addition, any adverts generated by websites he visited were also broadcast. http://www.poisonous-antidote.com This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
Views: 8736 TEDx Talks
Golden Opportunity: Mining Big Data and Social Media with GIS and Spatial Analytics
 
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This is an edited version of a presentation held on 09_18_13 by Dr. Ming Tsou, held at the University of Redlands, School of Business, Center for Business GIS and Spatial Analysis (GISAB). This video explains how _Social Media is the digital extension of collective human minds and ideas, the future of business marketing channels, and the source of real-time customer feedback...Geographic Information Systems (GIS) and spatial analytics can provide effective geo-targeting, real-time, and impact analysis by interpreting the interconnected information components (TIME, PLACE, and MESSAGES). This talk will introduce this analytical framework - Knowledge Discovery in Cyberspace (KDC) - for mining big data and social media..._ To read the entire speaker's bio and abstract, please visit www.redlands.edu_businessGIS
Fuqua DECISION 618 — Data Mining
 
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The course DECISION 618 Data Mining (a.k.a Big Data Analytics) derives business decisions based on (big) data analytics. The course aims to address one of the most transformational developments in modern business era -- exponential growth and availability of data. We will explore core ideas behind data mining, practical opportunities associated with big data, and the interplay between data science and business decisions. We will discuss real life examples from variety of concepts such as customer retention, health risk prediction, social media analysis, systemic risk, real-time online advertisement, text mining, and data mining contests. We will investigate how data can impact business decisions by focusing on (i) general principles that are long lasting despite of the rapid changing technology (ii) specific algorithms/technologies that are relevant today and are being used in many industries; and (iii) "hands-on" analyses of actual datasets to develop practical methodologies. The video has taken from Big Data Analytics: The Revolution Has Just Begun video.
Views: 126 Irakli Mindadze
Course Trailer | MIT SA+P Big Data and Social Analytics
 
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Visit the course page to find out more: https://www.getsmarter.com/courses/us/mit-sap-big-data-and-social-analytics-online-short-course If you're ready to join the program, go straight to the online registration form: https://www.getsmarter.com/courses/mit-sap-big-data-and-social-analytics-online-short-course/course_registrations/step_1
Views: 1473 GetSmarter Global
The human insights missing from big data | Tricia Wang
 
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Why do so many companies make bad decisions, even with access to unprecedented amounts of data? With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on "thick data" -- precious, unquantifiable insights from actual people -- to make the right business decisions and thrive in the unknown. Check out more TED talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
Views: 105535 TED
Social Media Data Privacy Awareness
 
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Learn more about how social media platforms, businesses, and marketers, use your personal information and posts to social media to build profiles about you.
Text and Data Mining in the Humanities and Social Sciences—Strategies and Tools
 
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Peter Leonard and Lindsay King of Yale University discuss reasons for current interest in TDM, what makes a good project, and implications for libraries. They also demonstrate Yale’s Robots Reading Vogue platform, showing projects based on the ProQuest database.
Views: 2055 CRLdotEDU
Data mining, social media, kids and security
 
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Matt Kelly chats to Rihanna Patrick on ABC Radio Brisbane about the recent revelations that Google is tracking the activities of kids online, and using this data to target advertising.
Views: 122 justmediadesign
Dr. Pippa Malmgren: Social Media Data Mining is the new Geopolitical Frontier
 
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Erik Townsend and Patrick Ceresna welcome Dr. Pippa Malmgren to MacroVoices. Erik and Pippa discuss Trump, art of the deal, trade wars and North Korea. They further discuss Russia, Syria, US and chemical warfare and global de-dollarization. They finally end discussing Facebook’s impact on geo-politics and financial markets, social media data mining and the Leadership Lab: Understanding Leadership in the 21st century
Views: 1737 Macro Voices
Social Big Data: la nueva tendencia del Marketing Digital
 
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Hoy la gran base de datos e información que se crea entre la empresa y el mercado crece alimentada por las interacciones en redes sociales y se puede saber qué se dice de la marca en twitter, facebook, pinterest... etc. Hoy nos acompaña Juan Carlos Mejía(@JuanCMejiaLlano), gerente de comunidades virtuales de INVAMER, quien dialoga con nuestro director Juan Carlos Yepes (@Juancarlosy) y nos explica una nueva tendencia: Social Big Data, que permite procesar la información para la toma de decisiones inteligentes. Juan Carlos Mejía habla inicialmente del Big Data, aquella área del marketing que trabaja, procesa y analiza grandes cantidades de datos y que hoy en día se ha aumentado gracias a la creciente interacción en la internet y en especial en las redes sociales. Hoy la gente está expresando en redes sociales lo que piensa y siente sobre un producto, servicio e incluso lo que siente alrededor de un gobierno. Esta información se toma de sus fuentes, se analiza y a partir de esto se pueden tomar decisiones sobre productos y servicios. NEGOCIOS EN TELEMEDELLÍN - Para disfrutar y aprender del mundo empresarial -- FACEBOOK https://www.facebook.com/negociosenTM TWITTER https://www.twitter.com/negociosentm Etiqueta: #negociosentm @juancarlosy (Juan Carlos Yepes - Director y presentador) @paolaruedalopez (Paola Rueda - Subdirectora y presentadora) SEÑAL EN DIRECTO VÍA WEB: http://www.telemedellin.tv/Paginas/senalenvivo.aspx SEÑAL DISPOSITIVOS MÓVILES: http://m.telemedellin.tv Lunes a Jueves 11: 00 p.m. (Hora colombiana) NEGOCIOS EN TELEMEDELLÍN es una realización de: SCITECH MEDIA - Agencia de Comunicaciones y Relaciones Públicas http://www.agenciastm.com
Views: 2049 Negocios En Tu Mundo