DonorUA Improves Blood Donor Search Through Social Listening and NLP
According to WHO, based on samples of 1000 people, the blood donation rate is 32.6 donations in high-income countries, 15.1 donations in upper-middle-income countries, 8.1 donations in lower-middle-income countries and 4.4 donations in low-income countries. Social networks are full of posts from people and blood centers asking to donate blood. Most of these posts remain ignored. We have developed a solution that monitors social networks and identifies posts with requests for blood donation.
Organization:
DonorUA is a Ukrainian nonprofit organization that provides an automated blood donor recruitment and management system. It helps connect donors with patients in need and works to promote a culture of regular blood donation across Ukraine.
Ukraine
Social networks are full of posts from people and blood centers asking to donate blood.
Most of these posts remain ignored.
According to WHO, based on samples of 1000 people,
the blood donation rate is 32.6 donations in high-income countries,
15.1 donations in upper-middle-income countries, 8.1 donations in
lower-middle-income countries and 4.4 donations in low-income countries.
This study aims to optimize the recruitment of blood donors by leveraging
social media for DonorUA nonprofit organization. The real-time analysis of
donation requests across various platforms can offer invaluable insights,
enabling organizations like the Red Cross and WHO to respond promptly and
efficiently within specific regions or cities. Moreover, the historical
data accrued over time can facilitate predictive analysis to anticipate
and mitigate potential shortages in blood supply.
Here is an example of a post from Twitter with a request for blood donation:
Urgent:
— ALI SHAN (SATTO) (@SatoMexicanox) August 11, 2021
O+ blood needed for a patient ( kid ) at AEH, Addu City. Plz contact 7847565 if you can donate or can find a donor for the kid.
Plz share and help.
Solution
We have engineered an application on Microsoft Azure to meticulously
monitor and analyze blood donation requests on social media. The initial
phase of the project utilizes YouScan, a sophisticated social listening
tool, to identify and extract relevant posts from Twitter. Posts are
filtered based on specific keywords and phrases such as "blood donors
required" and "blood donors needed".
Our system is equipped with a robust classification model that discerns
actual donor requests from unrelated posts. Non-pertinent posts are
systematically excluded from the dataset. Additionally, we have integrated
the Language Understanding service from Microsoft to enhance the extraction of meaningful
and precise information from the collected data.
This service facilitates the
identification of key details such as the location of blood centers, the
specific blood type and Rh factor required, the quantity of blood units needed
and pertinent contact information.
Generative AI Update
Large language models allow better understanding of a context and perform named entity recognition.
As an example, we can extract all needed information just by using prompt engineering.
Given the following tweet:
Urgent: O+ blood needed for a patient ( kid ) at AEH, Addu City. Plz contact 7847565 if you can donate or can find a donor for the kid. Plz share and help.It can be transformed into named entities like:
| Attribute | Details |
|---|---|
| Urgency | Urgent |
| Blood Type | O+ |
| Location | Addu City |
| Hospital | AEH |
| Contact Details | 7847565 |
This data can be easily extracted and analysed to perform quick and professional support and healthcare services.
Business impact
- Requests no longer go unnoticed. Donation appeals scattered across social networks are detected and structured automatically instead of being ignored.
- Faster, targeted response. Extracted details — blood type, location, urgency, contacts — let DonorUA route each request to matching donors in the right region.
- Foundation for prevention. Historical request data enables predictive analysis to anticipate and mitigate blood supply shortages before they become critical.
Conclusion
This innovative approach aims to revolutionize blood donation recruitment
strategies by harnessing the power of social media analytics, facilitating
a more responsive and effective blood donation system. Through meticulous
data analysis, our model aspires to bolster the efforts of NGOs and global
health organizations in securing a consistent and reliable blood supply.
Technologies
Microsoft Azure
A cloud computing service created by Microsoft for building, testing, deploying, and managing applications and services.
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including the business impact you can expect.
Technology serves as our pivotal advantage, facilitating the automation of tasks and enabling rapid progression. This becomes critically important in fields like the social sector and essential life-saving services like DonorUA. Our commitment to leveraging cutting-edge technology ensures efficiency and effectiveness, particularly in areas where time and precision are of utmost importance.
Iryna Slavinska
CEO at DonorUA
Our team was pleased to offer our advanced social listening technology to DonorUA and DevRain. We are gratified to see its application in such a specialized yet vitally important domain, demonstrating the versatility and impact of our innovative solutions in critical sectors.
Oleksii Orap
CEO at YouScan