Monitoring Blood Donor Search Requests at DonorUA

We used the power of intelligent social listening and natural language processing to develop a solution that monitors social networks and identifies posts with requests for blood donation.
The Ukrainian nonprofit organization that provides an automated blood donor recruitment and management system.
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:
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.
DonorUA social listeniing schema
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.
ChatGPT Update
ChatGPT, a new tool from OpenAI, allows better understanding of a context and perform named entity recognition. As an example, we can extract all needed information just by using prompt engineering.
For example, 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. can be transformed into named entities like:
Urgency Blood Type Location Hospital Contact Details
Urgent O+ Addu City AEH 7847565
This data can be easily extracted and analysed to perform quick and professional support and healthcare services.
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.
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
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
Oleksii Orap
CEO at YouScan