Abstract
Approximately 22 people die every day in the USA due to a lack of organs for transplant. Research suggests that the most effective solution is to increase organ donor rates; current, proposals range from expanding the donor eligibility criteria (donor pool) to performing mass media campaigns. However, little is known about the extent in which activities on social media are associated with aspects (e.g. awareness) of organ donation. Our hypothesis is that social media can be utilized as a sensor to characterize organ donation awareness and population engagement in donation for each different organ. In this sense, we collected Twitter messages (tweets) regarding organ donation, and characterized organ awareness by aggregating tweets from users who mostly mentioned that organ. Similarly, we assessed the relative risk between the cumulative incidence of organrelated conversations inside and outside geographical regions to characterize them regarding organ donation awareness. Our characterization suggests that organ-related conversations on social media seems to be indeed associated with aspects of organ donation such as the co-occurrence of organ transplantations. Also, we found variations regarding the specific organs that are prominently discussed in each geographical region, and that such variations seem to be associated with aspects of organ donation in that region; for instance, the abnormal amount of conversations about kidneys in Kansas. Our findings suggest that the proposed approach has the potential to characterize the awareness of organ donation in real-Time.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 |
| Publisher | IEEE Computer Society |
| Pages | 1541-1548 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781509065431 |
| DOIs | |
| State | Published - May 16 2017 |
| Externally published | Yes |
| Event | 33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States Duration: Apr 19 2017 → Apr 22 2017 |
Publication series
| Name | Proceedings - International Conference on Data Engineering |
|---|---|
| ISSN (Print) | 1084-4627 |
Conference
| Conference | 33rd IEEE International Conference on Data Engineering, ICDE 2017 |
|---|---|
| Country | United States |
| City | San Diego |
| Period | 4/19/17 → 4/22/17 |
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ASJC Scopus subject areas
- Software
- Signal Processing
- Information Systems
Cite this
Characterizing organ donation awareness from social media. / Pacheco, Diogo F.; Pinheiro, Diego; Cadeiras, Martin; Menezes, Ronaldo.
Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017. IEEE Computer Society, 2017. p. 1541-1548 7930122 (Proceedings - International Conference on Data Engineering).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Characterizing organ donation awareness from social media
AU - Pacheco, Diogo F.
AU - Pinheiro, Diego
AU - Cadeiras, Martin
AU - Menezes, Ronaldo
PY - 2017/5/16
Y1 - 2017/5/16
N2 - Approximately 22 people die every day in the USA due to a lack of organs for transplant. Research suggests that the most effective solution is to increase organ donor rates; current, proposals range from expanding the donor eligibility criteria (donor pool) to performing mass media campaigns. However, little is known about the extent in which activities on social media are associated with aspects (e.g. awareness) of organ donation. Our hypothesis is that social media can be utilized as a sensor to characterize organ donation awareness and population engagement in donation for each different organ. In this sense, we collected Twitter messages (tweets) regarding organ donation, and characterized organ awareness by aggregating tweets from users who mostly mentioned that organ. Similarly, we assessed the relative risk between the cumulative incidence of organrelated conversations inside and outside geographical regions to characterize them regarding organ donation awareness. Our characterization suggests that organ-related conversations on social media seems to be indeed associated with aspects of organ donation such as the co-occurrence of organ transplantations. Also, we found variations regarding the specific organs that are prominently discussed in each geographical region, and that such variations seem to be associated with aspects of organ donation in that region; for instance, the abnormal amount of conversations about kidneys in Kansas. Our findings suggest that the proposed approach has the potential to characterize the awareness of organ donation in real-Time.
AB - Approximately 22 people die every day in the USA due to a lack of organs for transplant. Research suggests that the most effective solution is to increase organ donor rates; current, proposals range from expanding the donor eligibility criteria (donor pool) to performing mass media campaigns. However, little is known about the extent in which activities on social media are associated with aspects (e.g. awareness) of organ donation. Our hypothesis is that social media can be utilized as a sensor to characterize organ donation awareness and population engagement in donation for each different organ. In this sense, we collected Twitter messages (tweets) regarding organ donation, and characterized organ awareness by aggregating tweets from users who mostly mentioned that organ. Similarly, we assessed the relative risk between the cumulative incidence of organrelated conversations inside and outside geographical regions to characterize them regarding organ donation awareness. Our characterization suggests that organ-related conversations on social media seems to be indeed associated with aspects of organ donation such as the co-occurrence of organ transplantations. Also, we found variations regarding the specific organs that are prominently discussed in each geographical region, and that such variations seem to be associated with aspects of organ donation in that region; for instance, the abnormal amount of conversations about kidneys in Kansas. Our findings suggest that the proposed approach has the potential to characterize the awareness of organ donation in real-Time.
UR - http://www.scopus.com/inward/record.url?scp=85021251880&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85021251880&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2017.225
DO - 10.1109/ICDE.2017.225
M3 - Conference contribution
AN - SCOPUS:85021251880
T3 - Proceedings - International Conference on Data Engineering
SP - 1541
EP - 1548
BT - Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017
PB - IEEE Computer Society
ER -