1. Challenge: Communicating with
communities
Natural language processing?
International Rescue Committee
Toronto
December 4-5, 2018

2. Challenge
To collect and record and analyze and respond to
information, queries, and concerns from the affected
population.
When you are limited in terms of time, human resources, and financial
resources, what are non-traditional ways to do surveys, collect and
respond to feedback?

3. Our goals
To provide more ways to
provide input into a
humanitarian response-
throughout the duration of a
response
To receive feedback or
information about services in
a timely and comprehensive
manner
To respond more quickly to
feedback
To scale
feedback/engagement
mechanisms
To more quickly receive
information about the affected
population’s needs
For the affected
population:
For the humanitarian
actor:

4. Traditional methods
Hotline
HR intensive
Requires reliable
network coverage
Satisfaction box
Require literacy
Often go and unchecked
One-on-one surveys
or interviews
HR intensive
May require additional
data entry, translation
and analysis
Focus group
discussions or
community meetings
HR intensive
Infrequent
Require data entry,
transcription, translation, and
analysis
Comment cards
Require literacy
Require data entry and
translation

5. Why the need for alternatives to traditional
methods?
 Traditional methods for ongoing community engagement can be
human resource intensive
 Heavy dependence on literacy, phone ownership and network
coverage
 Considerable time is needed for data entry, translation and/or
transcription, and analysis
 The affected population may be geographically dispersed –
reaching them in-person may not be an option.

6. Challenge/Solution areas
Providing
Information about
available services
Surveys – needs
assessments,
satisfaction surveys,
focus group
discussions, key
informant interviews
Feedback collection
and response

7. Key features of a functional solution
Must offer anonymity to users
Must be simple enough to “learn” in a day or two (from
the NGO side)
Must work for multiple languages and/or dialects
Must be inclusive of or accessible by multiple “types” of
people (women, low literacy, etc.)

8. Possible solution: Natural Language
Processing
What is NLP? What could it do for us?
Automatic transcription
Automatic or machine translation
Sentiment analysis
Topic segmentation and recognition
.
Speech recognition
Suggestions Needs
Comments
Complaints
Clean, usable, data

9. Possible hurdles to overcome
Why do you
want to know?Bonjour ?
Hello?