Challenge 5 nlp
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#emergencydatascience Dec 4-5, 2018 | York University
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Challenge 5 nlp
- 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?
Editor's Notes
- This is about having a continuous conversation with emergency affected people. This cycle should include assessments, unsolicited feedback, post-assistance monitoring, etc. For the IRC – this ongoing engagement, not just one piece of it, is a struggle. This is, due to a lack of dedicated resources/easy methods. ... we are crap at it more than 50% of the time. Donors won’t fund humans to focus on this, and without the humans/funding, our team on the ground focuses on the service provision, not the ongoing engagement that is required to ensure that service provision is acceptable. There currently are not dedicated resources or funding for this side of the work- so having alternative solutions are key.
- Surveys- needs assessment, satisfaction surveys FGDs, KIIs, HHs (Needs assessment) Provision of information about services Feedback information collection and processing
- Cameroon: Cameroon is Franco and Anglophone. The IRC recently started a new response in the Anglophone region of the country. A phone line already existed in the Francophone region. The team is considering different options for feedback mechanisms. If they want to implement a hotline, the hotline will need to be separate from the existing phone line in order to make sure Also, currently, there are not sufficient funds to hire a full-time employee to answer the phone and record and respond to questions and inquiries. There is also a need to provide information about services offered. The response in Cameroon will be doing distributions soon and registering those who qualify for assistance. Many will not receive assistance and will want to know why they were not chosen. There needs to be an easy/wide-reaching way to share the selection criteria information and a way to field inquiries about the distributions. Yemen- is doing cash distributions. There is a need to have constant communication with the community, including those who are not selected to receive cash, to be transparent and to keep our staff safe. IRC is interested in supporting partners responding to the current economic and food/health crisis in Venezuela- we need to conduct periodic remote surveys with affected people to do so, to ensure the services we support are meeting needs and not causing harm.
- Surveys- needs assessment, satisfaction surveys FGDs, KIIs, HHs (Needs assessment) Provision of information about services Feedback information collection and processing
- Must offer anonymity Respond to/work with multiple languages or dialects Must be simple enough so that key staff can learn how to use it in a day or two
- Machine translation Automatically translate text from one (non-computer) language to another. Sentiment analysis Topic segmentation and recognition Separate text into segments each of which is devoted to a topic, and identify the topic of the segment. Speech recognition Given a sound clip of a person or people speaking, determine the textual representation of the speech
- Respond to/work with multiple languages or dialects Impersonality and fear of technology – will people trust tech? Lack of phone network in some contexts Phone ownership coverage Need to figure out tracking to follow up with people