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Emotional Text Mining and health psychology: the culture of organ donation in Spain

EasyChair Preprint no. 1368

4 pagesDate: August 7, 2019

Abstract

Organ donation is an extremely important issue in our society as patients on the waiting lists for transplantation die every year due to the lack of organs. The Spanish healthcare system is a best practice in Europe, reaching 48 donors per million people. A best practice compared to the Italian one in which only 28 donors for million people make this choice. In order to understand the cultural elements influencing the choice to donate, this paper presents the application of Emotional Text Mining (ETM) in the field of health psychology and, in particular, on organ donation. ETM is an unsupervised procedure aiming to profile media and social media discourses that can be considered a proxy of the Spanish culture. It is a fast and simple procedure to extract meaningful information from a large collection of texts. It is based on a bottom-up approach to classify unstructured data by means of a multivariate analysis for the identification of the representation, the cultural symbolization, and the sentiment of organ donation, as those elements influence people’s decision to donate. We collected all the articles (n= 342) of three most popular Spanish newspapers, the El Mundo, El Pais and Marca, published in the last ten years (2010-2019) containing the keyword “donacion de organos”. In order to check whether it was possible to statistically process data, we calculated two lexical indicators of the large size corpus, the type-token ratio and the percentage of hapax (TTR = 0.092; Hapax% = 0,515). Results show six representations characterizing the Spanish culture of organ donation. While one representation connects the donation to the death, all the other representations highlight positive elements associated to life, which could be a relevant factor explaining the high rate of the Spanish donors.

Keyphrases: Emotional Text Mining, ETM, Health Psychology, media, Organ Donation

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:1368,
  author = {Francesca Greco and Silvia Monaco and Michela Di Trani and Barbara Cordella},
  title = {Emotional Text Mining and health psychology: the culture of organ donation in Spain},
  howpublished = {EasyChair Preprint no. 1368},

  year = {EasyChair, 2019}}
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