Introduction to Text Analytics
September 4, 9am-5pm
Hosted at Independent Evaluation Group (IEG) at the World Bank
“I” Building, (Room to be announced)
1850 I St NW, Washington, DC 20006
Join us for a one-day workshop to learn the basics of Text Analytics!
Quantitative data analysis has traditionally relied on computers and statistical software. Over the past 10 years, there has been an explosion of available data, and data analytics, machine learning and artificial intelligence have become important fields that now automate data analysis.
Approximately 80% of the available data is qualitative text, and qualitative data analysis techniques have traditionally relied on researchers reading, coding and distilling meaning from interviews, transcripts and documents, some using CAQDAS (Computer Assisted Qualitative Data Analysis Software).
Natural Language Processing and Text Analytics is a new field in machine learning and artificial intelligence that aims to make computers better at analyzing and understanding text data. This workshop will provide an introduction and overview of this field, and its (potential) applications for evaluators.
At this workshop, we will introduce participants to the basic concepts, techniques, and approaches of natural language processing and text analytics used to get text ready for more in-depth analysis. Participants will learn about automated document summarization, automatic qualitative theme discovery, and clustering using unsupervised machine learning (topic modelling) and sentiment analysis.
We’ll close out the day with a discussion on how these tools and approaches can be applied to evaluation.
After the workshop, the participants will:
- Have a basic understanding of natural language processing, and how to prepare text and documents for analysis and current constraints of practice.
- Have an understanding of concepts and approaches in text analytics and machine learning applied to text, including automated document summarization, topic modeling for theme/topic discovery and sentiment analysis.
- Be able to describe the place of text analytics in evaluation practice, and in their own work environment.
Kerry Bruce, DrPH, is the CEO and founder of of Clear Outcomes, a company that aims to draw on her 25+ years of experience working in the for-profit and non-profit sectors of development and more than 20 years of living in Asia and Africa. Kerry is a recognized global health expert and has managed large implementation projects on several continents. A recognized leader in the ICT field, Kerry has been spearheading the use of big data in project design, monitoring and evaluation for the field, is a regular guest lecturer for TechChange, and has been a co-organizer of the MERL Tech conference. She is an adjunct faculty member at Georgetown University’s International Health Department and teaches courses in mHealth and Implementation Science.
Dr. Joris Vandelanotte is a Medical Doctor and Specialist in Public Health Medicine with over 25 years’ experience in Sub-Saharan Africa in the fields of public health, health systems strengthening, primary health care, monitoring and evaluation, and operational research. Joris started his career with Médecins sans Frontières in Kenya and Chad, where he combined clinical practice with district and primary health care management. In Swaziland (2006-2012, ICAP, Columbia University) he led a team of clinicians and M&E staff at who supported the Ministry of Health in the provision of decentralized HIV care and treatment services, including HAART. As deputy director for Results and Measurement at Pact (2013-2014), Joris provided short-term technical assistance in monitoring, evaluation, and research to 9 country offices, and he was a key technical resource for statistics, geographic information systems, mobile health, and health information systems. More recently, he led a 5 year USAID funded HIV prevention and voluntary medical male circumcision (VMMC) project in Swaziland (2015-2017).
Co-hosted and sponsored by:
Questions? Contact Linda Raftree