If you were not able to join the SAS presentation on Suicide prevention yesterday at the Data Innovation Summit, feel free to check-out the slides here. All comments, suggestions and questions are very welcome!
This document discusses communicating effectively with data by taking both a problem-driven and data-driven approach. It emphasizes understanding the problem behind the data as well as the information behind the problem to generate business insights. Both the problem and data should inform each other.
Using data from twenty-one speed dating events to create a new dating app, we can connect two individuals based on their interest and preferences thus expediting the dating process. The app will direct the user to rate other users’ profiles based on not only the user’s image but also how much he/she likes the other user based on their profile information. The profiles will include demographic information, shared Interests, and other attributes such as fun factor, attractiveness, etc. After evaluating each user’s preferences and rating, the app will suggest partners who have similar interests and matching preferences.
This document provides an overview of a workshop on data literacy and visualization. It outlines that participants will critically analyze data sources, define data visualization practices, and apply those practices to their own data. It discusses evaluating data sources, analyzing data for deception or bias, investigating sources, avoiding scale distortions, and mapping data visualizations. The workshop is led by Nicole Branch from the university library and Brian Larkin from academic technology.
Nyc open data meetup wasserstein presentationVivian S. Zhang
It is a talk given by Wasserstein, Ronald L(Executive Director of American Statistical assosication). NYC Open Data meetup are honored to host this event on Mar 3rd. You can find more information at www.meetup.com/nyc-open-data and www.nycopendata.com
Data Mining and Text Mining in Educational ResearchQiang Hao
This document discusses data mining in education. It begins by outlining the goals of understanding what data mining is, what tools and knowledge are required, and the basic process. It then provides examples of educational questions that can be answered through data mining, such as predicting student performance or recommending courses. The document discusses the data collection, cleaning, processing, analysis, and sharing stages of the data mining process. It also recommends several textbooks and software tools useful for performing data mining.
Engage Talent April 2018 Webinar - Major LinkedIn Changes Ahead! Robby Gulri
There are lots of major changes coming to LinkedIn. If you are a recruiter or talent acquisition professional, you need to be aware of these changes and adjust your tactics.
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts! Lisa Lang
This is a panel/workshop session developed for NEXT 2014 in Berlin.
Guests:
Lisa Lang (Twilio) Anke Domscheit-Berg (Opengov.me) Olga Steidl (Linko ) Ivan P. Yamshchikov (Yandex) Felienne Hermans (TU Delft)
----
Content:
Everyone is talking about Big Data – but what’s really behind it and how can you make data work for your business?
Collecting data is just one part of the puzzle. To source the right information, read it so it makes sense and -finally- how to execute on it is the most important task for successful big data management.
At this panel workshop we’ll listen to a lot of examples from big companies who’re dealing with massive amount of data on a daily basis. Each panel member will give a short demo and insight to their strategies and might revile some surprising facts.
This workshop is organised in cooperation with Berlin Geekettes.
DWS16 - Plenary - Earning digital trust - Vesselin Popov, University of Cambr...IDATE DigiWorld
The document summarizes the work of the University of Cambridge Psychometrics Centre, which was founded in 1989 to establish Cambridge as an international leader in computational behavioral science. The Centre has expertise in areas like psychological assessment, digital footprint analysis, and machine learning. Researchers at the Centre have shown that traits like personality, political views, and life satisfaction can be accurately predicted using digital and social media data. The Centre advocates for using personalization and big data analytics to empower users, enable dialogue around data use, and build more transparent and trustworthy artificial intelligence.
This document discusses communicating effectively with data by taking both a problem-driven and data-driven approach. It emphasizes understanding the problem behind the data as well as the information behind the problem to generate business insights. Both the problem and data should inform each other.
Using data from twenty-one speed dating events to create a new dating app, we can connect two individuals based on their interest and preferences thus expediting the dating process. The app will direct the user to rate other users’ profiles based on not only the user’s image but also how much he/she likes the other user based on their profile information. The profiles will include demographic information, shared Interests, and other attributes such as fun factor, attractiveness, etc. After evaluating each user’s preferences and rating, the app will suggest partners who have similar interests and matching preferences.
This document provides an overview of a workshop on data literacy and visualization. It outlines that participants will critically analyze data sources, define data visualization practices, and apply those practices to their own data. It discusses evaluating data sources, analyzing data for deception or bias, investigating sources, avoiding scale distortions, and mapping data visualizations. The workshop is led by Nicole Branch from the university library and Brian Larkin from academic technology.
Nyc open data meetup wasserstein presentationVivian S. Zhang
It is a talk given by Wasserstein, Ronald L(Executive Director of American Statistical assosication). NYC Open Data meetup are honored to host this event on Mar 3rd. You can find more information at www.meetup.com/nyc-open-data and www.nycopendata.com
Data Mining and Text Mining in Educational ResearchQiang Hao
This document discusses data mining in education. It begins by outlining the goals of understanding what data mining is, what tools and knowledge are required, and the basic process. It then provides examples of educational questions that can be answered through data mining, such as predicting student performance or recommending courses. The document discusses the data collection, cleaning, processing, analysis, and sharing stages of the data mining process. It also recommends several textbooks and software tools useful for performing data mining.
Engage Talent April 2018 Webinar - Major LinkedIn Changes Ahead! Robby Gulri
There are lots of major changes coming to LinkedIn. If you are a recruiter or talent acquisition professional, you need to be aware of these changes and adjust your tactics.
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts! Lisa Lang
This is a panel/workshop session developed for NEXT 2014 in Berlin.
Guests:
Lisa Lang (Twilio) Anke Domscheit-Berg (Opengov.me) Olga Steidl (Linko ) Ivan P. Yamshchikov (Yandex) Felienne Hermans (TU Delft)
----
Content:
Everyone is talking about Big Data – but what’s really behind it and how can you make data work for your business?
Collecting data is just one part of the puzzle. To source the right information, read it so it makes sense and -finally- how to execute on it is the most important task for successful big data management.
At this panel workshop we’ll listen to a lot of examples from big companies who’re dealing with massive amount of data on a daily basis. Each panel member will give a short demo and insight to their strategies and might revile some surprising facts.
This workshop is organised in cooperation with Berlin Geekettes.
DWS16 - Plenary - Earning digital trust - Vesselin Popov, University of Cambr...IDATE DigiWorld
The document summarizes the work of the University of Cambridge Psychometrics Centre, which was founded in 1989 to establish Cambridge as an international leader in computational behavioral science. The Centre has expertise in areas like psychological assessment, digital footprint analysis, and machine learning. Researchers at the Centre have shown that traits like personality, political views, and life satisfaction can be accurately predicted using digital and social media data. The Centre advocates for using personalization and big data analytics to empower users, enable dialogue around data use, and build more transparent and trustworthy artificial intelligence.
The banking sector in Vietnam has benefited from strong monetary policy and economic growth over the past year. However, loan growth has not met targets due to subdued credit demand and banks working through legacy non-performing loans. The State Bank of Vietnam has been active in developing new banking legislation, but implementation has posed challenges for banks. Overall reforms to resolve bad debts, streamline documentation requirements, and develop the financial system are ongoing.
Oracle ICS Best Practises - 1st Presented at Oracle Partner PaaS Forum by Phi...Phil Wilkins
Robert van Molken & Phil Wilkins presented a short brief presentation on some good practices related to the use of Oracle ICS. This was 1st presented at the Oracle EMEA Partner Forum in Split, Croatia, 27th March 2017
The first of 5 summary presentations around our Habit Fundamentals™ training. A brief look at the four stages of learning, with a voiceover from me to give some context.
This document provides information and guidance on being an ally to trans* people. It defines important terms like trans*, cisgender, and gender binary. It explains that trans* people experience discrimination and need allies to help make society more inclusive. The document offers dos and don'ts for being a good ally, such as using preferred pronouns and names, challenging transphobia, and listening without objectifying trans* people. The overall message is that everyone can play a role in promoting trans* inclusion and preventing transphobia.
Engagement is key to member loyalty and volunteering is the stickiest form of engagement - so lets optimize volunteer opportunity in your association through #VolunteerLove. Tips and ideas. Samples.
Deben elegirse a 2 comisionados del Instituto de Acceso a la Información Públ...FUSADES
El Grupo Promotor LAIP expresa su preocupación por el retraso en la elección de dos comisionados del Instituto de Acceso a la Información Pública (IAIP). Se ha realizado una tercera convocatoria debido a que no se presentaron suficientes candidatos en las dos convocatorias anteriores. El IAIP lleva un mes funcionando de forma irregular sin los nuevos comisionados. El Grupo Promotor sugiere medidas como agilizar la emisión de documentos requeridos para los candidatos y realizar la asamblea de elección una vez concluya el pl
LegalThings was born from a common pain to almost everyone who has worked in a corporate environment: despite working with smart and organised people, we are still spending too much time on process management and reproduction of the same content.
DISUMMIT - Jos Polfliet - Suicide prevention using text analyticsDigitYser
Jos Polfliet
Making the AI revolution happen - Faction XYZ
In my daily job, I help companies translate their business problems to questions that can be answered by data, using AI, machine learning, data mining, predictive modeling and sensor analytics. This way companies can improve their business processes by making data-driven decisions, with often impressive and insightful results.
Faction XYZ is an applied artificial intelligence engineering service provider, with headquarters in Antwerp (Belgium). We serve clients with a vision and budget for a future where data science and machine learning will continue to drive our client’s core business in a rapidly transforming economic reality. Our in-depth knowledge of artificial intelligence, conversational agents, and an array of emerging technologies make us the first choice for companies with a vision and budget. We advance your strategic goals by imagining, developing, and implementing the technology stack you need to stay ahead.
For years, the focus of ML work has been to push frontiers, develop new capabilities, and achieve increased accuracy on a variety of tasks. So, where do we go from here? Bigger, faster, more accurate? Or do we take a step back and dig into transparent, fair, and explainable?
Ethical AI is rapidly being forced on industry as a key concern. Yet despite the significant investments, organizations struggle to operationalize ethical AI. We realized that we had to start doing things differently. In this talk I will share Pandata’s journey to incorporating Ethical AI into our practice.
• Understanding what it means to be an ethical data science practice, and why it is easier said than done
• Learning to have hard conversations among ourselves and our clients about bias & risk, and to articulate the importance of these conversations as practical and not just academic
• Moving from ethics as a value to ethics as a virtue. How we went from ethics as an aspirational thing we say to an actual way of working
• Some tools and processes we've adopted along the way to help, including our hiring processes
The result is more fulfilled and representative data science teams and better than industry average retention while fostering pro-active risk management.
First delivered as a Learning Solutions 'Data and Measurement' Track Conference Session on March 22, 2017 by Janet Laane-Effron and Sean Putman.
Find out more about HT2 Labs' research and development at HT2Labs.com
This document provides an overview of information architecture (IA) and its importance. It discusses the key elements and goals of IA, including organizing content, designing navigation, and classifying information. The document also stresses the importance of understanding user, business, technology, and content requirements through research and interviews. It presents an exercise for practicing requirements gathering and introduces the concept of personas as a way to represent different types of users.
Decoding Social Data Employing Non Discriminatory Analytics in Creating New D...Mahmoud Dasser
7th Enterprise Innovation CXO Forum | Questex Events
SINGAPORE , 28 February 2019
Decoding Social Data Employing Non Discriminatory Analytics in
Creating New Differentiators for Digital Enterprise
Key Talking points:
Competitive advantage from Social Data continues to grow
Combine Social Data with more Data Sources to:
• Improve relationship & Customer Experience
• Gain market insights and Innovate Faster
• Drive operational Efficiency
• Improve Brand Health
• Generate New revenue
• Improve marketing effectiveness
Denver Event - 2013 - Floodlight and Data Engine User SurveyKDMC
This document provides a summary of findings from a survey of 530 respondents representing 313 organizations regarding their use of data and storytelling. Key challenges identified included lack of time, staffing, and resources to effectively collect, analyze, and use data to tell stories. The document analyzes crosstabs of survey questions and provides recommendations for a follow up study.
This document summarizes an interactive master class on putting the human context into business using big data perspectives. The class covered various topics:
1. Datafication and analyzing social media data like tweets, Instagram posts, and blogs to understand human behaviors and motivations.
2. Tools for linguistic analysis of text like LIWC, RID, and Twitter analysis to study personality, deception, and predict marketing based on word usage.
3. Developing a predictive, empathetic organization using social listening and recognizing distress signals to improve customer experience.
4. An ongoing study of baby feeding experiences analyzing video signals of joy to understand communication and develop recommender systems.
"H-factor Human Amplification". Talk at Social Media Week 2016 - Milan - Piet...Pietro Leo
Pietro Leo shared insights on digital transformation, artificial intelligence, and cognitive computing. He noted that 63% of CEOs will increase investment in digital in 2015 to survive, investment in fintech companies has increased 10x in the past 5 years, and AI patents have more than tripled in 10 years. Leo emphasized that wisdom is needed to help cope with cognitive overload as data and insights expand exponentially. IBM's Watson platform can help scale expertise and expand what's possible through cognitive computing.
Diamonds in the Rough (Sentiment(al) AnalysisScott K. Wilder
Gary Angel and Scott K. Wilder presented on sentiment analysis. Gary is the president of Semphonic, a web analytics consultancy, and Scott is a digital strategist. They discussed how sentiment analysis works, its limitations, and best practices for using it. Specifically, they noted that sentiment analysis provides anecdotal, not primary, insights and that the most accurate approach combines automated tools with manual review of verbatim comments.
Panel Discussion – Grooming Data Scientists for Today and for TomorrowHPCC Systems
In this session, we will explore the talent gap for data scientists including the potential causes and what academia and the private sector are doing to develop the necessary talent. Will the skills which are in such explosive demand today still be in demand in the future? This panel of professors and practitioners will engage in a conversation about the talent issues facing companies across the country and around the world and what they are doing about it.
The banking sector in Vietnam has benefited from strong monetary policy and economic growth over the past year. However, loan growth has not met targets due to subdued credit demand and banks working through legacy non-performing loans. The State Bank of Vietnam has been active in developing new banking legislation, but implementation has posed challenges for banks. Overall reforms to resolve bad debts, streamline documentation requirements, and develop the financial system are ongoing.
Oracle ICS Best Practises - 1st Presented at Oracle Partner PaaS Forum by Phi...Phil Wilkins
Robert van Molken & Phil Wilkins presented a short brief presentation on some good practices related to the use of Oracle ICS. This was 1st presented at the Oracle EMEA Partner Forum in Split, Croatia, 27th March 2017
The first of 5 summary presentations around our Habit Fundamentals™ training. A brief look at the four stages of learning, with a voiceover from me to give some context.
This document provides information and guidance on being an ally to trans* people. It defines important terms like trans*, cisgender, and gender binary. It explains that trans* people experience discrimination and need allies to help make society more inclusive. The document offers dos and don'ts for being a good ally, such as using preferred pronouns and names, challenging transphobia, and listening without objectifying trans* people. The overall message is that everyone can play a role in promoting trans* inclusion and preventing transphobia.
Engagement is key to member loyalty and volunteering is the stickiest form of engagement - so lets optimize volunteer opportunity in your association through #VolunteerLove. Tips and ideas. Samples.
Deben elegirse a 2 comisionados del Instituto de Acceso a la Información Públ...FUSADES
El Grupo Promotor LAIP expresa su preocupación por el retraso en la elección de dos comisionados del Instituto de Acceso a la Información Pública (IAIP). Se ha realizado una tercera convocatoria debido a que no se presentaron suficientes candidatos en las dos convocatorias anteriores. El IAIP lleva un mes funcionando de forma irregular sin los nuevos comisionados. El Grupo Promotor sugiere medidas como agilizar la emisión de documentos requeridos para los candidatos y realizar la asamblea de elección una vez concluya el pl
LegalThings was born from a common pain to almost everyone who has worked in a corporate environment: despite working with smart and organised people, we are still spending too much time on process management and reproduction of the same content.
DISUMMIT - Jos Polfliet - Suicide prevention using text analyticsDigitYser
Jos Polfliet
Making the AI revolution happen - Faction XYZ
In my daily job, I help companies translate their business problems to questions that can be answered by data, using AI, machine learning, data mining, predictive modeling and sensor analytics. This way companies can improve their business processes by making data-driven decisions, with often impressive and insightful results.
Faction XYZ is an applied artificial intelligence engineering service provider, with headquarters in Antwerp (Belgium). We serve clients with a vision and budget for a future where data science and machine learning will continue to drive our client’s core business in a rapidly transforming economic reality. Our in-depth knowledge of artificial intelligence, conversational agents, and an array of emerging technologies make us the first choice for companies with a vision and budget. We advance your strategic goals by imagining, developing, and implementing the technology stack you need to stay ahead.
For years, the focus of ML work has been to push frontiers, develop new capabilities, and achieve increased accuracy on a variety of tasks. So, where do we go from here? Bigger, faster, more accurate? Or do we take a step back and dig into transparent, fair, and explainable?
Ethical AI is rapidly being forced on industry as a key concern. Yet despite the significant investments, organizations struggle to operationalize ethical AI. We realized that we had to start doing things differently. In this talk I will share Pandata’s journey to incorporating Ethical AI into our practice.
• Understanding what it means to be an ethical data science practice, and why it is easier said than done
• Learning to have hard conversations among ourselves and our clients about bias & risk, and to articulate the importance of these conversations as practical and not just academic
• Moving from ethics as a value to ethics as a virtue. How we went from ethics as an aspirational thing we say to an actual way of working
• Some tools and processes we've adopted along the way to help, including our hiring processes
The result is more fulfilled and representative data science teams and better than industry average retention while fostering pro-active risk management.
First delivered as a Learning Solutions 'Data and Measurement' Track Conference Session on March 22, 2017 by Janet Laane-Effron and Sean Putman.
Find out more about HT2 Labs' research and development at HT2Labs.com
This document provides an overview of information architecture (IA) and its importance. It discusses the key elements and goals of IA, including organizing content, designing navigation, and classifying information. The document also stresses the importance of understanding user, business, technology, and content requirements through research and interviews. It presents an exercise for practicing requirements gathering and introduces the concept of personas as a way to represent different types of users.
Decoding Social Data Employing Non Discriminatory Analytics in Creating New D...Mahmoud Dasser
7th Enterprise Innovation CXO Forum | Questex Events
SINGAPORE , 28 February 2019
Decoding Social Data Employing Non Discriminatory Analytics in
Creating New Differentiators for Digital Enterprise
Key Talking points:
Competitive advantage from Social Data continues to grow
Combine Social Data with more Data Sources to:
• Improve relationship & Customer Experience
• Gain market insights and Innovate Faster
• Drive operational Efficiency
• Improve Brand Health
• Generate New revenue
• Improve marketing effectiveness
Denver Event - 2013 - Floodlight and Data Engine User SurveyKDMC
This document provides a summary of findings from a survey of 530 respondents representing 313 organizations regarding their use of data and storytelling. Key challenges identified included lack of time, staffing, and resources to effectively collect, analyze, and use data to tell stories. The document analyzes crosstabs of survey questions and provides recommendations for a follow up study.
This document summarizes an interactive master class on putting the human context into business using big data perspectives. The class covered various topics:
1. Datafication and analyzing social media data like tweets, Instagram posts, and blogs to understand human behaviors and motivations.
2. Tools for linguistic analysis of text like LIWC, RID, and Twitter analysis to study personality, deception, and predict marketing based on word usage.
3. Developing a predictive, empathetic organization using social listening and recognizing distress signals to improve customer experience.
4. An ongoing study of baby feeding experiences analyzing video signals of joy to understand communication and develop recommender systems.
"H-factor Human Amplification". Talk at Social Media Week 2016 - Milan - Piet...Pietro Leo
Pietro Leo shared insights on digital transformation, artificial intelligence, and cognitive computing. He noted that 63% of CEOs will increase investment in digital in 2015 to survive, investment in fintech companies has increased 10x in the past 5 years, and AI patents have more than tripled in 10 years. Leo emphasized that wisdom is needed to help cope with cognitive overload as data and insights expand exponentially. IBM's Watson platform can help scale expertise and expand what's possible through cognitive computing.
Diamonds in the Rough (Sentiment(al) AnalysisScott K. Wilder
Gary Angel and Scott K. Wilder presented on sentiment analysis. Gary is the president of Semphonic, a web analytics consultancy, and Scott is a digital strategist. They discussed how sentiment analysis works, its limitations, and best practices for using it. Specifically, they noted that sentiment analysis provides anecdotal, not primary, insights and that the most accurate approach combines automated tools with manual review of verbatim comments.
Panel Discussion – Grooming Data Scientists for Today and for TomorrowHPCC Systems
In this session, we will explore the talent gap for data scientists including the potential causes and what academia and the private sector are doing to develop the necessary talent. Will the skills which are in such explosive demand today still be in demand in the future? This panel of professors and practitioners will engage in a conversation about the talent issues facing companies across the country and around the world and what they are doing about it.
This document summarizes an introductory presentation on data science. It introduces the presenter and their background in data and analytics. The goals of the presentation are to define what a data scientist is, how the field has emerged, and how to become one. It discusses the growing demand and salaries for data scientists. Examples are given of how data science has been applied at companies like LinkedIn and Netflix. The presentation covers big data, Hadoop, data processing techniques, machine learning algorithms, and tools used in data science. Finally, attendees are encouraged to consider Thinkful's data science bootcamp program.
Getting started in Data Science (April 2017, Los Angeles)Thinkful
The document discusses the rise of data science and the skills needed for data scientists. It defines data science as the intersection of engineering, statistics, and communication. Data scientists analyze large datasets to answer important business questions. The document uses LinkedIn in 2006 as a case study, outlining how a data scientist there framed questions, collected and processed user data, explored patterns, and communicated results to improve the user experience and growth. It highlights tools like SQL, analytics software, and machine learning that data scientists use and stresses the importance of curiosity, technical skills, and strong communication for those interested in the field.
Thinkful - Intro to Data Science - Washington DCTJ Stalcup
This document discusses an introductory session on data science. It begins with introductions and an outline of the session's goals, which are to define what a data scientist is, how the field has emerged, and how to become one. It then discusses the growing demand and high salaries for data scientists. Examples are given of how data science has been applied at companies like LinkedIn, Netflix, and for fighting Ebola. Key aspects of data science like big data, Hadoop, MapReduce, and machine learning algorithms are explained. The document concludes by discussing the data science process and tools used, and encourages the audience that it is possible for them to become data scientists with the right knowledge, skills, and learning approach.
You've heard the news, Data Science is the cool new career opportunity sweeping the world. Come learn from Thinkful Mentors all about this new and exciting industry.
2017 06-14-getting started with data scienceThinkful
The document provides an overview of getting started with a career in data science. It introduces the author Jasjit Singh and discusses what a data scientist does, how the field has emerged to analyze big data. Examples are given of how companies like LinkedIn and Uber use data science. The data science process is explained through the steps of framing a question, collecting and processing data, exploring patterns in the data, and communicating findings. Tools used include SQL, data visualization software, and machine learning algorithms. The document encourages the reader that becoming a data scientist is achievable through learning statistics, algorithms, and software skills.
This document provides an introduction to data science, including what it is, how the field has emerged due to big data, and the roles and skills of data scientists. It discusses how data scientists at LinkedIn used data analysis to improve their product's user connections feature. The data science process of framing questions, collecting and processing data, exploring for patterns, and communicating results is also outlined. Finally, the document discusses tools used in data science like SQL, data visualization software, and machine learning algorithms.
This document discusses various topics related to survey research methods. It covers forms of survey research like face-to-face, mail, telephone and internet surveys. It also discusses interviewing, validity, reliability, sampling, data collection and analysis procedures. Common survey design errors and ways to improve response rates are outlined. The advantages and disadvantages of different data collection modes are compared.
This document provides an overview of data science as a career field. It discusses how data science emerged to address the rise of "big data" and the shortage of people with analytical skills. It uses LinkedIn as a case study to outline the data science process of framing questions, collecting and processing data, exploring for patterns, and communicating results. Finally, it discusses the tools used in data science like SQL, data visualization software, and machine learning algorithms. It promotes Thinkful's data science bootcamp program for transitioning into a data science career.
Lisa Joy Rosner (NetBase): The New Market ResearchIABC Louisville
The document discusses the rise of social media and how it has changed market research. Some key points made include: (1) Over 90% of consumers mention brands weekly in conversations; (2) 53% of Twitter users recommend products, with 48% intending to purchase; (3) Social data can be used to track brand and competitor performance, generate hypotheses, and profile audiences. The future of market research involves analyzing social media data along with traditional methods to better understand customers.
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STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
1. Jos Polfliet
Specialist Data Sciences at SAS Institute - @JosPolfliet
Data Innovation Summit
March, 30 2017
#DIS2017
Suicide prevention using text
analytics
2. can someone with my number please text me because i have nobody to
talk to and i just want to hut myself so badly and i’m scared
my own father told me I deserved being killed. I hate him
there's not one day I don’t think of killing myself
4. 1.1M tweets
Feelings: 106k ≈ 10%
Bullying: 11k ≈ 1%
Suicide: 382 ≈ 0.035% of tweets
39% correlation between
suicide and bullying
5. Data Impact Challenge
Question 3
What proportion of Canadian youth (13-17) post about their mental health, and
describe experiencing bullying or suicidal thoughts in the past 12 months on social
media?
Our submission
Won $10,000
donated to mental health charities
mind your mind and Rise Asset Development
Canada Health Infoway
$95,000 in awards
6. Download Language Age Topic Analyze
Tweets
in Canada
during a specific
time frame
Detect language
Filter English
Build predictive
model for Age
Filter teenagers
Detect topic
• Aggression
• Alcohol
• Bullying
• Family
• Feelings
• Relationships
• …
Analyze
relationships
between topics
Contextual
analysis of topics
Python crawler for
Twitter API
SAS Text Analytics SAS Enterprise Miner
SAS Text Analytics
SAS Text Analytics SAS Visual Analytics
7. How can we predict “At-Risk”
social media users (for
suicide and self-harm)?
8.
9.
10. Data Science Project Funnel
Idea Define Prove Decide Build Deploy
Data available?
Does this make sense?
Done before?
Input variables?
Target variable?
Expected value?
Is performance as we
expect?
Data Quality?
Offline evaluation
Potential value?
Accuracy measures?
How difficult?
Feasibility?
Data sources
(internal/external)?
Time?
Priority?
Budget?
Executive buy-in?
Business process
redesign?
Architecture
Technical
Performance
Change mgmt.
Resources
Actual value?
Live Evaluation
WE ARE HERE
12. Call Center Notes Survey Feedback
Online Forums Blogs Consumer Reviews Online News Social Networks
Associate Comments Claims & Case NotesResearch & Publications
Live Chat Factory/Technician Notes HR data Medical/Health Records Contracts & Applications
13. If anybody knows Maggie, let me know! [I’m serious]
@JosPolfliet
14. Jos Polfliet
Specialist Data Sciences at SAS Institute - @JosPolfliet
Data Innovation Summit
March, 30 2017
#DIS2017
Suicide prevention using text
analytics